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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Solutions Network Formulation Report. Integration of OMI and TES Aerosol Products into the EPA Regional Planning Organizations' FASTNET Aerosol Tracking and Analysis Tool

Every year, more than 280 million visitors tour our Nation s most treasured parks and wilderness areas. Unfortunately, many visitors are unable to see the spectacular vistas they expect because of white or brown haze in the air. Most of this haze is not natural; it is air pollution, carried by the wind often hundreds of miles from its origin. Some of the pollutants have been linked to serious health problems, such as asthma and other lung disorders, and even premature death. In addition, nitrates and sulfates contribute to acid rain formation, which contaminates rivers and lakes and erodes buildings and historical monuments. The U.S. Environmental Protection Agency RPOs (Regional Planning Organizations) have been tasked with monitoring and determining the nature and origin of haze in Class I scenic areas, and finding ways to reduce haze in order to improve visibility in these areas. The RPOs have developed an Internet-based air quality DST (Decision Support Tool) called FASTNET (Fast Aerosol Sensing Tools for Natural Event Tracking). While FASTNET incorporates a few satellite datasets, most of the data utilized by this DST comes from ground-based instrument networks. The problem is that in many areas the sensors are sparsely located, with long distances between them, causing difficulties in tracking haze over the United States, determining its source, and analyzing its content. Satellite data could help to fill in the data gaps and to supplement and verify ground-recorded air quality data. Although satellite data are now being used for air quality research applications, such data are not routinely used for environmental decision support, in part because of limited resources, difficulties with interdisciplinary data interpretation, and the need for advanced inter-agency partnerships. As a result, the validation and verification of satellite data for air quality operational system applications has been limited This candidate solution evaluates the usefulness of OMI (Ozone Monitoring Instrument) and TES (Tropospheric Emission Spectrometer) air quality data for the RPOs by comparing OMI and TES data with ground-based data that are acquired during identified episodes of air pollution. The air quality data from OMI and TES are of different spectral ranges than data from satellites currently included in FASTNET, giving them potential advantages over the existing satellites. If the OMI and TES data are shown to be useful to the RPOs, they would then be integrated into the FASTNET DST for use on an operational basis.

Knowlton, Kelly↗
DOE OSTI2020

Chromatographic Modeling of 1-Foot Detritiation Test Column Results for the Optimization of Regeneration Time

This report documents the methods and results of a modeling study on a series of data generated by 1-foot test columns for the Water Detritiation project. In order to compliment modeling work already in progress on this project, a purely empirical curve-fitting approach is used in this study to determine chromatographic performance indicators such as retention time, curve width, and the number of chromatographic stages. The data used in this study comes from four sets of chromatographic test separations performed in March through May of 2017 using 1-foot columns. All are using the same flow rates and temperature (room temperature, nominally 25 C°). The first set of data (referred to in this report as the Column 1 data) is a series of twelve breakthrough curve measurements. Prior to each of these twelve runs, the column was regenerated by flowing hydrogen gas through the column, for increasing amounts of time, ranging from 2 hours to 25 hours. The second set of data (referred to as the Column 2 data) is comprised of five measurements of breakthrough curves measured in similar fashion as the Column 1 data, across a range of regeneration times from 2 to 21 hours. The third set of data (referred to as the Purge data) is of three breakthrough curves, measured after a regeneration time of 8 hours, which takes place after a nitrogen purge of 15, 30, or 45 minutes. The fourth data set is a series of five breakthrough curve measurements using a 2 nd batch of stationary phase, taken after regeneration times ranging from 2 to 20 hours. The overall modeling approach is as follows. First, the data is pre-processed for formatting, artifact removal, and is normalized. The data is then fit by integrated versions of four common chromatographic models. The best model is chosen based on the predictive performance of the model, and chromatographic performance values are calculated based on the best model’s fit parameters. Each of these processes are detailed below.

42 ENGINEERING↗
NASA NTRS1994

Light transmission and reflection in perennially ice-covered Lake Hoare, Antarctica

We have investigated the transmission and albedo of the perennial ice cover on Lake Hoare, Antarctica. Our database consists of year-round measurements of the photosynthetically active radiation (400-700 nm) under the ice, measurements of the spatial variation of the under-ice light in midsummer, and spectrally resolved measurements from 400 to 700 nm of the albedo and transmission of the ice cover in early (November) and in midsummer (January). Our results show that the transmission decreases in the first part of summer, dropping by a factor of approximately 4 from November to January. We suggest that this is due to heating in the upper layers of the ice cover and the formation of Tyndall figures. Later in the summer when a significant liquid water fraction occurs within the ice cover, the transmission increases. In the fall when the ice cover freezes solid the transmission drops markedly. The spectrally resolved measurements from 400 to 700 nm show that approximately 2-5% of the incident light in this spectral region penetrates the 3.5-m thick ice cover. We have analyzed the spectral data using a two-stream scattering solution to the radiative transfer equation with three vertical layers in the ice cover. A surficial glaze of scattering ice 1 cm thick overlies a layer of sandy, bubbly ice about a meter thick, and below this is a thick layer of sand-free ice with bubbles. We find that the ice cover is virtually opaque at wavelengths longer than 800 nm. The net transmission of solar energy is approximately 2%. Significant changes in the thickness of the ice cover have been reported at Lake Hoare. These are due primarily to changes in the thickness of the bottom layer only. Because this layer is relatively clear, the effect on the transmission through the ice cover from these changes is less than would be predicted assuming a homogeneous ice cover.

Mckay, C. P.↗
DOE OSTI2025

Hot Droughts and Forest Tree Dynamics in the Amazon - Statistical Models, Scripts, Data, and Outputs

This package contains data, outputs, equations, and R scripts for analyses for manuscript entitled "Hot droughts in the Amazon: A window to a future hypertropical climate" by J. Chambers et al., in particular it contains statistical models and analyses for the INPA BIONTE tree mortality study. The Models folder contains details for all statistical models in PDF files. The Scripts folder contains the R scripts for Bayesian Hierarchical Models (two text files) and SEMs (one text file) are separate and reasonably annotated. All data associated with these scripts are in the data folder. The Data folder contains two of the three CSV files used for the analyses and are called by the R scripts. Two of them are part of published datasets (`BIONTE_mortality-rates.csv` from Lima et al. 2024, DOI:10.15486/ngt/1898910 and `SPEI.csv` from Pastorello et al. 2023 DOI:10.15486/ngt/1958257) and also provided in this package for convenience (please see the corresponding datasets for usage and citation terms). The third dataset (`BIONTE_gapfilled_wd.csv`) contains sensitive information and can be obtained by contacting the manuscript lead author. The Outputs folder contains the two output files that provide extra information about the analyses. The file `figuresFeb2025d.pdf` contains all the figures from the manuscript - captions are in the manuscript. The file `ChambersMS.pdf` contains primary results from Bayesian statistical models, regression analyses, and validation steps applied to the tree mortality data from the INPA experiments. The document includes visual summaries, model diagnostics, and leave-one-out (LOO) validation results. A breakdown of file contents can be found in the README file that is part of this package.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from soil samples in control and warming plots in Blodgett Forest, CA (2014-2021)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of LBNL (Lawrence Berkeley National Laboratory) TES (Terrestrial Ecosystem Science) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization.Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community from soil depth profiles collected from 2014 to 2021 from three paired control and warming plots. We collected soil samples across a range of depth profiles (spanning surface to 90 cm deep) from three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. 101 soil metagenomes were sequenced at JGI (Joint Genome Institute) and UCSF (University of California San Francisco) Center for Advanced Technology and can be found under the JGI (Joint Genome Institute) GOLD (Genomes Online Database) Sequencing project Gs0151586 and NCBI (National Center for Biotechnology Information) Projects PRJNA1225762 and PRJEB39497. Metagenomes were assembled using JGI (Joint Genome Institute) Metagenome Workflow (10.1128/mSystems.00804-20). For each metagenome, the assembled contigs were binned into genomes using 3 binning algorithms (cocacola, metabat, and maxbin) and the resulting bins were consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>50%) and contamination (<25%), and dereplicated at 99% ANI (average nucleotide identity) using dRep (https://github.com/MrOlm/drep).The dataset includes a zip file of 2321 MAG (Metagenome Assembled Genome) fasta files, the accession numbers for the underlying metagenomes, and a csv file with MAG (Metagenome Assembled Genome) quality metrics and taxonomic classification (GTDB -Genome Taxonomy Database-RS220). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Implications of Aerosol Physicochemical Properties Including Ice Nucleation at ARM Mega Sites for Improved Understanding of Microphysical Atmospheric Cloud Processes (Final Technical Report)

Continuous, long-term measurements of atmospheric ice-nucleating particles (INPs) that influence clouds and precipitation were conducted to investigate the abundance and variability of ground-level INPs across the world. Three field campaigns were organized by the DOE Atmospheric Radiation Measurement (ARM) program, including Examining INP from Southern Great Plains (ExINP-SGP, 2019), Examining INP from Eastern North Atlantic (ExINP-ENA, 2020 – 2021), and Examining INP from North Slope of Alaska (ExINP-NSA, 2021 – 2024). Additional small-scale supporting field experiments were performed in 2019 and 2021 to collect airborne particulate matter at SGP for complementary laboratory characterization of the particles’ physical and chemical properties [Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY), 2019; ExINP-SGP II, 2021]. In these studies, the PI’s team measured INP concentration with both real-time and laboratory measurements in a wide range of freezing temperatures ($T$ from 0 °C to about –30 °C). This project elucidated spatial variability and seasonality in the abundance of immersion mode active INPs across three ARM sites using a single instrument, a Portable Ice Nucleation Experiment (PINE) chamber version 03 (PINE-03 hereafter). Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient INP abundance, air mass origin region, and meteorological variability. Our findings suggest very high freezing efficiency of INPs at the NSA site across the measured temperatures (ice nucleation active surface site density, $n_s(T)$, $\approx 2 \times 10^{8} - 10^{10}$ m -2 for from –16 to –31 °C), which is a factor of 10 – 1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in autumn using the same instrument; surprisingly high INP abundance ($\ge 1 \text{ L}^{-1}$ at –25 °C) for the examined temperatures throughout the year that PINE-03 did not measure at other sites; and high INP concentration in spring, possibly related to arctic haze episodes.

58 GEOSCIENCES↗
NASA NTRS2020

Flow Simulations for Martian and Lunar Lander Plume-Surface Interaction Prediction

Landing vehicle propulsive systems introduce several risks associated with plume/surface interactions (PSI) during the final stages of descent. For example, view obscuration during descent due to the liberation of dust driven by the rocket plume’s interaction with the lunar surface was reported on several Apollo missions. Plume-driven debris impacts on vehicle and nearby assets as well as landing instabilities due to crater formation are also potential risks associated with plume/surface interactions. The importance of studying these plume/surface interactions has been elevated due to NASA’s mission to land humans on the Moon by 2024. Existing and under-development predictive simulation tools are currently being brought to application readiness under a project awarded by the NASA Space Technology Mission Directorate (STMD) Game Changing Development (GCD) program. This tool development is divided into four tasks: (1) simulating plume structure in low-pressure environments, (2) simulating crater development and ejecta, (3) regolith particle phase modeling, and (4) gas-particle interaction modeling. Recent efforts under task 1 include demonstrating existing computational fluid dynamics (CFD) tools for simulating plume structure in low pressure environments similar to those found on Mars. The results of these demonstrative simulations are compared to available experimental data. Emerging capability being developed under task 2 is also presented, demonstrating simulations of crater formation in Lunar conditions.

Thomas P Shurtz↗
DOE OSTI2022

Integrating Very-High-Resolution UAS Data and Airborne Imaging Spectroscopy to Map the Fractional Composition of Arctic Plant Functional Types in Western Alaska: Supporting Data

Remote sensing maps of plant functional type (PFT) fractional cover (FCover), dominant PFT, and FCover uncertainty derived from NASA's Airborne Visible / Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG). The AVIRIS-NG imaging spectroscopy data (380-2510 nm) was collected as a part of the collaboration between NASA's Arctic-Boreal Vulnerability Experiment (ABoVE; Miller et al., 2019) and DOE's Next Generation Ecosystem Experiment in the Arctic (NGEE-Arctic). This package includes maps of the NGEE-Arctic Council watershed on the Seward Peninsula, Alaska, created using AVIRIS-NG imagery collected on July 9th, 2019. The map data and metadata are provided as GeoTIFF (*.tif), ENVI image (*.dat), and text (*.txt, *hdr) formats. Additional map quicklooks are provided as *.pdf files and GIS *.kml files. These datasets are provided in support of Yang et al., (2023), "Integrating Very-High-Resolution UAS Data and Airborne Imaging Spectroscopy to Map the Fractional Composition of Arctic Plant Functional Types in Western Alaska".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

WHONDRS Surface Water and Sediment Geochemistry and Organic Matter Characterization Data from Streams across HJ Andrews Experimental Forest, Oregon (v2)

This dataset supports a broader study developing conceptual models for river corridor critical zone processes across spatial scales and was generated in collaboration with the HJ Andrews River Corridor Critical Zone Workshop in 2025. The dataset provides surface water geochemistry (dissolved organic carbon, total dissolved nitrogen) from 48 sites across the HJ Andrews Experimental Forest, Oregon (https://andrewsforest.oregonstate.edu). Some of the sites have been impacted by the Holiday Farm Fire and the Lookout Fire in 2020 and 2023, respectively. Related data were collected as part of the workshop and will be published separately in collaboration with other workshop attendees and available at http://www.hydroshare.org/resource/b274c4a234bf4b12b7cb8a54a696c629. Related genomic data can be found on the National Center for Biotechnology Information (NCBI) under BioProject PRJNA1503030 (see critical details section below for more information). Additional related data collected in 2016 from a similar effort can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3377027 and http://www.hydroshare.org/resource/ea6c0832885a46c3939e7bb22e48e754 and are described within https://doi.org/10.5194/essd-11-1-2019 (Ward et al., 2019). This data package was originally published in March 2026. It was updated in August 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos, (2) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data, (3) a data checks report, (4) a folder of sample data, (5) file-level metadata, (6) data dictionary, (7) field metadata, (8) readme, (9) international generic sample number (IGSN) mapping file; and (10) field protocol. The sample data subfolder contains surface water and sediment (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages, (2) total dissolved nitrogen data and averages, (3) methods codes, (4) FTICR-MS methods; and (5) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the CoreMS processed data and seven subfolders, thee containing .xml files for each sample type (sediment, surface water and blank samples), three containing the sediment CoreMS output files for each sample type (sediment, surface water and blank samples), and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .Rmd, .py, .cal, .json, .jpg, or .jpeg.

Biogeochemistry↗
DOE OSTI2023

Carbon flux measurements from chambers collected between July to October 2022 at Old Woman Creek, Huron, Ohio.

This dataset contains carbon dioxide and methane flux measurements collected via chamber sampling at Old Woman Creek National Estuarine Research Reserve in Huron, OH. These data were generated to understand temporal and vegetation patterns associated with wetland carbon cycling. Specifically, this dataset intends to answer how carbon dioxide and methane fluxes change monthly and hourly across sites with vegetation and without vegetation. Data includes chamber measurements that were measured in both sites with vegetation and without vegetation and that were collected hourly, for 12 hours, and monthly, for four months. The file soilrespiration_data.csv contains these data, and the metadata file (soilrespiration_chammetadata.csv) and location metadata file (soilrespiration_locationmetadata.csv) have information on locations where the chambers were placed and sampled in the wetland. Data processing was done on raw methane fluxes (Flux_CH4) to remove the influence of ebullition (Flux_CH4_ebullition) to get a diffusive flux (Flux_CH4_diffusive).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Temperature, Humidity, and Time-Lapse Video Data from Yosemite National Park, Water Year 2024

This dataset contains time-lapse imagery and distributed measurements of air temperature, relative humidity, dew point, and soil temperature across Yosemite National Park from October 2023 to September 2024. Instruments were deployed at 10 sites in two cross-valley transects as part of the DOE Grant: Seasonal Cycles Unravel Mysteries of Missing Mountain Water organized by Jessica Lundquist (University of Washington), Rosemary Carroll (Desert Research Institute), and Ethan Gutmann (National Center for Atmospheric Research). The data are intended to support hydrologic modeling efforts to better resolve the fate of mountain water, and are published to support studies of surface climate or hydrologic processes in complex terrain. Measurements were collected with low-cost data loggers installed 2 m high on evergreen trees or buried just below the soil surface. A time-lapse camera at one site captures valley-scale seasonal snow cover variability.Dataset files are organized by site and variable (air measurements, ground measurements, or time-lapse video). Air and ground measurements are packaged in LoggerData.zip, and time-lapse imagery is compiled into a short video stored in TimelapseVideos.zip. File-level metadata contains details for each file included in the dataset. A data dictionary provides units and descriptions for column or row names in all files. The locations metadata file describes site characteristics, locations, and associated GPS methods.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Airborne lidar measurements of El Chichon stratospheric aerosols, May 1983

An experimental survey flight to determine the spatial distribution and aerosol characteristics of the El Chichon-produced stratospheric aerosol was conducted in May 1983. The mission included several different sensors flown abroad the NASA Convair 990 at latitudes between 72 deg. and 56 deg. S. This report presents the lidar data from that flight mission. Representative profiles of lidar backscatter ratio, plots of integrated backscattering function versus latitude, and contours of backscatter mixing ratio versus altitude and latitude are given. In addition, tables containing numerical values of the backscatter ratio and backscattering function versus altitude are supplied for each profile. By May 1983, material produced by the El Chichon eruptions of late March-early April 1982 had spread throughout the latitudes covered by this mission. However, the most massive portion of the material resided north of 33 deg. N and was concentrared below 21 km. In this latitude region (33 deg. N to 72 deg. N), peak backscatter ratios at a wavelength of 0.6943 microns varied between 3.5 and 4.5, and the peak integratred backscattering function was about 18 X 10 to the -4 power/sr, corresponding to a peak optical depth calculated to be approximately 0.08. This report presents the results of this mission in a ready-to-use format for atmospheric and climatic studies.

Mccormick, M. P.↗
NASA NTRS1987

Broad-band properties of the CfA Seyfert Galaxies. II - Infrared to millimeter properties

IR and mm observations of the 48 Seyfert 1 and 2 galaxies (SG1s and SG2s) of the CfA sample (Huchra and Berg, 1987) are reported. Data obtained (1) in the NIR using the 1.55-m reflector at Stewart Observatory and the 3-m IRTF during 1984-1986, (2) in the FIR with IRAS, and (3) at 1.3 mm using the 12-m NRAO telescope at KPNO in June 1984 are presented in extensive tables and graphs and characterized in detail. None of the objects was detected at 1.3 mm, and the IR spectra of the SG2s are found to be significantly steeper (indicating thermal emission) than those of SG1s and QSOs (nonthermal emission). Turnover in the IR emission below 100 microns (in half of the objects detected at three or more IRAS wavelengths) is shown to be consistent with an accretion disk in dust-free SG1s and with unusually warm (35-65 K) dust in SG2s. It is inferred that a 60-100-micron cool excess is masking turnover in the other SGs, so that a general association of SG nuclei with strong star formation can be confirmed.

Edelson, R. A.↗
NASA NTRS1999

The Transport of Solar Ions Through the Earth's Magnetosphere

This report covers the initial phase of an investigation that was originally selected by NASA Headquarters for funding by a grant but was later transferred to NASA GSFC for continued funding under a new and separate contract. The principal objective of the investigation, led by Dr. O.W. Lennartsson, is to extract information about the solar origin plasma in Earth's magnetosphere, specifically about the entry and transport of this plasma, using energetic (10 eV/e to 18 keV/e) ion composition data from the Lockheed Plasma Composition Experiment on the NASA/ESA International Sun-Earth Explorer One (ISEE 1) satellite. These data were acquired many years ago, from November 1977 through March of 1982, but, because of subsequent failures of similar experiments on several other spacecraft, they are still the only substantial ion composition data available from Earth's magnetotail, beyond 10 R(sub E), in the critically important sub-kev to keV energy range. All of the Lockheed data now exist in a compacted scientific format, suitable for large-scale statistical investigations, which has been archived both at Lockheed Martin in Palo Alto and at the National Space Science Data Center (NSSDC) in Greenbelt. The completion of the archiving, by processing the remaining half of the data, was made possible by separate funding through a temporary NASA program for data restoration and was given priority over the data analysis by a no-cost extension of the subject grant. By chance, the period of performance coincided with an international study of source and loss processes of magnetospheric plasma, sponsored by the International Space Science Institute (ISSI) in Bern, Switzerland, for which Dr. Lennartsson was invited to serve as one of 12 co-chairs. This study meshed well with the continued analysis of the NASA/Lockheed ISEE ion composition data and provided a natural forum for a broader discussion of the results from this unique experiment. What follows is arranged, for the most part, in the context of the ISSI project.

Lennartsson, O. W.↗
DOE OSTI2021

A Self-Synchronizing Underwater Acoustic Network for Mooring Load Monitoring of a Wave Energy Converter

This paper reports on the development of a self-synchronizing underwater acoustic network developed for remote monitoring of mooring loads in Wave Energy Converters (WECs). This network uses Time Division Multiple Access and operates self-contained with the ability for users to remotely transmit commands to the network as needed. Each node is a self-contained unit, consisting of a protocol adaptor board, an FAU-DPAM underwater acoustic modem and a battery pack. A node can be connected to a load cell, to a topside user or to the WEC. Every node is swapable. The protocol adaptor board, named Protocol Adaptor for Digital LOad Cell (PADLOC) supports a variety of digital load cell message formats (CAN, MODBUS, custom ASCII) and underwater acoustic modem serial formats. PADLOC enables topside users to connect to separate load cells through a user-specific command. This is especially important if the user is monitoring multiple load cells during deployment or maintenance, when the primary data system may be offline. Each PADLOC board handles formatting, buffering and has a one-on-one serial connection with each pair (node) of a digital load cell and acoustic modem. In addition, each PADLOC board handles the timekeeping and power saving features for each node. The only limitation is the data bit rate and delay limitations associated with the underwater acoustic modem. A four node self-synchronizing network has been developed to demonstrate the load cell monitoring capability using the PADLOC technology on the CalWave WEC.

acoustic↗
DOE OSTI2023

Chemical and genetic characterization of the ungrouped pallasite Lieksa

The meteorite Lieksa was found in 2017 in Löpönvaara, Finland, and later donated to the Finnish Museum of Natural History. Here, we report siderophile element concentrations, genetic isotopic data, and a metal–silicate segregation age for the meteorite. The ~280 g Lieksa is ~80% metal and ~20% silicate and oxide inclusions by volume, with the inclusions consisting primarily of Fe-rich olivine. Due to Lieksa's silicate content, coupled with a texture characterized by metal enclosing the silicates, it has been classified as a pallasite. Lieksa's olivine and bulk chemical characteristics are distinct from those of the known pallasite and iron meteorite groups, consistent with its classification as ungrouped. The meteorite exhibits a flat, chondrite-normalized highly siderophile element pattern, consistent with an origin as an early crystallization product from a metallic melt with chondritic relative abundances. Molybdenum, Ru, and 183 W isotopic data indicate that Lieksa formed in the non-carbonaceous (NC) domain of the solar nebula. Radiogenic 182 W abundances for Lieksa yield a model metal–silicate segregation age of 1.5 ± 0.8 Myr after calcium-aluminum-rich inclusion formation, which is within the range established for other NC-type pallasite and iron meteorite parent bodies.

58 GEOSCIENCES↗