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At least 811 records · Page 45

Evaluation of a Singular Value Decomposition Approach for Impact Dynamic Data Correlation

Impact dynamic tests are used in the automobile and aircraft industries to assess survivability of occupants during crash, to assert adequacy of the design, and to gain federal certification. Although there is no substitute for experimental tests, analytical models are often developed and used to study alternate test conditions, to conduct trade-off studies, and to improve designs. To validate results from analytical predictions, test and analysis results must be compared to determine the model adequacy. The mathematical approach evaluated in this paper decomposes observed time responses into dominant deformation shapes and their corresponding contribution to the measured response. To correlate results, orthogonality of test and analysis shapes is used as a criterion. Data from an impact test of a composite fuselage is used and compared to finite element predictions. In this example, the impact response was decomposed into multiple shapes but only two dominant shapes explained over 85% of the measured response

Horta, Lucas G.↗

Measurement of heat conduction through stacked screens

This paper describes the experimental apparatus for the measurement of heat conduction through stacked screens as well as some experimental results taken with the apparatus. Screens are stacked in a fiberglass-epoxy cylinder, which is 24.4 mm in diameter and 55 mm in length. The cold end of the stacked screens is cooled by a Gifford-McMahon (GM) cryocooler at cryogenic temperature, and the hot end is maintained at room temperature. Heat conduction through the screens is determined from the temperature gradient in a calibrated heat flow sensor mounted between the cold end of the stacked screens and the GM cryocooler. The samples used for these experiments consisted of 400-mesh stainless steel screens, 400-mesh phosphor bronze screens, and two different porosities of 325-mesh stainless steel screens. The wire diameter of the 400-mesh stainless steel and phosphor bronze screens was 25.4 micrometers and the 325-mesh stainless steel screen wire diameters were 22.9 micrometers and 27.9 micrometers. Standard porosity values were used for the experimental data with additional porosity values used on selected experiments. The experimental results showed that the helium gas between each screen enhanced the heat conduction through the stacked screens by several orders of magnitude compared to that in vacuum. The conduction degradation factor is the ratio of actual heat conduction to the heat conduction where the regenerator material is assumed to be a solid rod of the same cross sectional area as the metal fraction of the screen. This factor was about 0.1 for the stainless steel and 0.022 for the phosphor bronze, and almost constant for the temperature range of 40 to 80 K at the cold end.

NASA Discipline Environmental Health↗

Addressing and Presenting Quality of Satellite Data via Web-Based Services

With the recent attention to climate change and proliferation of remote-sensing data utilization, climate model and various environmental monitoring and protection applications have begun to increasingly rely on satellite measurements. Research application users seek good quality satellite data, with uncertainties and biases provided for each data point. However, different communities address remote sensing quality issues rather inconsistently and differently. We describe our attempt to systematically characterize, capture, and provision quality and uncertainty information as it applies to the NASA MODIS Aerosol Optical Depth data product. In particular, we note the semantic differences in quality/bias/uncertainty at the pixel, granule, product, and record levels. We outline various factors contributing to uncertainty or error budget; errors. Web-based science analysis and processing tools allow users to access, analyze, and generate visualizations of data while alleviating users from having directly managing complex data processing operations. These tools provide value by streamlining the data analysis process, but usually shield users from details of the data processing steps, algorithm assumptions, caveats, etc. Correct interpretation of the final analysis requires user understanding of how data has been generated and processed and what potential biases, anomalies, or errors may have been introduced. By providing services that leverage data lineage provenance and domain-expertise, expert systems can be built to aid the user in understanding data sources, processing, and the suitability for use of products generated by the tools. We describe our experiences developing a semantic, provenance-aware, expert-knowledge advisory system applied to NASA Giovanni web-based Earth science data analysis tool as part of the ESTO AIST-funded Multi-sensor Data Synergy Advisor project.

Leptoukh, Gregory↗

Datalist: A Value Added Service to Enable Easy Data Selection

Imagine a user wanting to study hurricane events. This could involve searching and downloading multiple data variables from multiple data sets. The currently available services from the Goddard Earth Sciences Data and Information Services Center (GES DISC) only allow the user to select one data set at a time. The GES DISC started a Data List initiative, in order to enable users to easily select multiple data variables. A Data List is a collection of predefined or user-defined data variables from one or more archived data sets. Target users of Data Lists include science teams, individual science researchers, application users, and educational users. Data Lists are more than just data. Data Lists effectively provide users with a sophisticated integrated data and services package, including metadata, citation, documentation, visualization, and data-specific services, all available from one-stop shopping. Data Lists are created based on the software architecture of the GES DISC Unified User Interface (UUI). The Data List service is completely data-driven, and a Data List is treated just as any other data set. The predefined Data Lists, created by the experienced GES DISC science support team, should save a significant amount of time that users would otherwise have to spend.

Datalist↗

OpenNEX: An open collaboration platform for the earth science community

Satellite data from the past several decades provide the most consistent record of land-surface processes that form the basis for scientific assessments of the impacts of climate variations and changes on the environment and human social-economical activities. During this time, scientific research on the characterization and assessment of environmental changes had tended to focus on large-scale land-surface changes with significant social-economic impacts. Increasingly, attention is shifting toward changes that occur more locally and that most directly relate to the everyday life of the majority of the population. In addition, there has been needs to develop management and policy decision support systems that are based on local environmental information. Almost at the same time, the advancement in sensor technology has allowed us to collect an unprecedented volume of environmental data. These data must be curated and analyzed to extract useful information for research and decision support purposes. Established in 2013 and funded by NASA, the Open NASA Earth eXchange (OpenNEX; https://opennex.org/ , Jia et al., 2019 ) project partnered with Amazon Web Services (AWS) to make available a large amount of Earth observing data, modeling results, and analysis tools on the AWS. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of NASA data assets and software tools. To encourage the public's engagement in this project, NASA ran virtual workshops and prize competitions. The virtual workshops provided online lectures and tutorials about how prominent scientists used the data in their research and the tutorials gave examples how to use the tools to interrogate the data in the Amazon cloud. Finally, the prize competitions allowed much wider participation in the OpenNEX project and enable testing the non-traditional projects and out-of-box ideas. OpenNEX has continued to evolve and mature. Here, we highlight new features and functionalities available to the community.

Jian Zhang↗

GeoNEX: A Geostationary Earth Observatory

The latest generation of geostationary satellites (Himawari 8/9, GOES-16/17, FY-4, GK-2A) carries sensors that closely mimic the spatial and spectral characteristics of widely used polar-orbiting, global monitoring sensors such as MODIS and VIIRS. When combined, data from various currently operating/planned geostationary platforms provide a geo-ring of hyper-temporal (5-10 minutes), multispectral observations at spatial resolutions as high as 500 m. These high frequency observations offer exciting new possibilities for monitoring our planet, including better retrievals of geophysical variables by overcoming cloud cover, enabling studies of diurnally varying phenomena in the atmosphere, land, and the oceans, and support operational decision-making in agriculture, hydrology and disaster management. The NASA Earth Exchange (NEX) team, in collaboration with scientists from JAXA, KARI, NOAA and other international institutions, created the GeoNEX (www.nasa.gov/geonex) pipeline to integrate data from all available geostationary platforms and produce and distribute spatially, temporally, and radiometrically consistent data for the earth science community. We envision various institutions adapting the Geo component (e.g., GeoNOAA, GeoKARI, GeoChiba, GeoJAXA, GeoCMA) and customizing the pipeline and downstream products to serve the local/regional research and applied science communities. To facilitate collaborative work among the partners, we have established the OpenNEX platform on the public cloud. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of GeoNEX data assets and software tools.

GeoNEX↗

Dissolved Inorganic Carbon and Dissolved Organic Carbon Data for the East River Watershed, Colorado (2015-2025)

This data package contains mean values for dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) for water samples taken from the East River Watershed in Colorado. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. DOC and DIC concentrations in water samples were determined using a TOC-VCPH analyzer (Shimadzu Corporation, Japan). DOC was analyzed as non-purgeable organic carbon (NPOC) by purging HCl-acidified samples with carbon-free air to remove DIC prior to measurement. After the acidified sample has been sparged, it is injected into a combustion tube filled with oxidation catalyst heated to 680 oC. The DOC in samples is combusted to CO2 and measured by a non-dispersive infrared (NDIR) detector. The peak area of the analog signal produced by the NDIR detector is proportional to the DOC concentration of the sample. DIC was determined by acidifying the samples with HCl first, and then purging with carbon-free air to release CO2 for analysis by NDIR detector. Total dissolved nitrogen (TDN) was analyzed using a Shimadzu Total Nitrogen Module (TNM-L) combined with the TOC-L analyzer (Shimadzu Corporation, Japan). TNM-L is a non-specific measurement of total nitrogen (TN). All nitrogen species in samples are combusted to nitrogen monoxide and nitrogen dioxide, then reacted with ozone to form an excited state of nitrogen dioxide. Upon returning to ground state, light energy is emitted. Then, TDN is measured using a chemiluminescence detector. All data reported are the mean values upon minimum of three replicate measurements, with a relative standard deviation < 3%. All samples were analyzed under a rigorous quality assurance and quality control (QA/QC) process. This data package contains (1) a zip file (dic_npoc_data_2014-2025.zip) containing a total of 337 files: 336 data files of DIC and NPOC data from across the Lawrence Berkeley National Laboratory (LBNL) Watershed Function Scientific Focus Area (SFA) which is reported in .csv files per location and a locations.csv (1 file) with latitude and longitude for each location; (2) a file-level metadata (v6_20250901_flmd.csv) file that lists each file contained in the dataset with associated metadata; (3) a data dictionary (v6_20250901_dd.csv) file that contains terms/column_headers used throughout the files along with a definition, units, and data type; and (4) PDF and docx files for the determiniation of Method Detection Limits (MDLs) for DIC and NPOC data, which has been updated in 2026-08. Missing values within the anion data files are noted as either "-9999" or "0.0" for not detectable (N.D.) data. There are a total of 113 locations containing DIC/NPOC data. Update on 2020-10-07: Updated the data files to remove times from the timestamps, so that only dates remain. The data values have not changed. Update on 2021-04-11: Added Determination of Method Detection Limits (MDLs) for DIC, NPOC and TDN Analyses document, which can be accessed as a PDF or with Microsoft Word.Update on 6/10/2022: versioned updates to this dataset was made along with these changes: (1) updated dissolved inorganic carbon and dissolved organic carbon data for all locations up to 2021-12-31, (2) removal of units from column headers in datafiles, (3) added row underneath headers to contain units of variables, (4) restructure of units to comply with CSV reporting format requirements, (5) added -9999 for empty numerical cells, and (6) the addition of the file-level metadata (flmd.csv) and data dictionary (dd.csv) were added to comply with the File-Level Metadata Reporting Format. Update on 2022-09-09: Updates were made to reporting format specific files (file-level metadata and data dictionary) to correct swapped file names, add additional details on metadata descriptions on both files, add a header_row column to enable parsing, and add version number and date to file names (v2_20220909_flmd.csv and v2_20220909_dd.csv). Update on 2023-08-08: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-01-05. The file level metadata and data dictionary files were updated to reflect the additional data added. Update on 2024-03-11: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-11-21. Further, revisions to the data files were made to remove incorrect data points (from 1970 and 2001). The reporting format specific files were updated to reflect the additional data added. Revised versions of the PDF and docx files for determination of MDLs for DIC and NPOC were added to replace previous versions. Update on 2025-05-15: Updates were made to both the data files and reporting format specific files. New available DIC and NPOC data was added, up until the end of WY2024 (September 30, 2024). International Generic Sample Numbers (IGSNs), when registered, were added to the data files. The reporting format specific files were updated to reflect the additional data added. Update on 2026-09-01: Updates were made to both the data files and reporting format specific files. New available DIC and NPOC data was added, up until the end of WY2025 (September 30, 2025). Updated versions, as of 2026-08-10, of the PDF and docx files for determination of MDLs for DIC and NPOC data were added to this dataset.

54 ENVIRONMENTAL SCIENCES↗

Hestia SW-IFL Onroad Fossil Fuel Carbon Dioxide (FFCO2) product: Road segment-level annual FFCO2 emissions across Arizona (2017-2022), version 1.1

The SW-IFL onroad fossil fuel carbon dioxide (FFCO2) emissions data product represents CO2 emissions from the combustion of fossil fuels by motor vehicles (e.g., passenger cars, trucks, buses, motorcycles) traveling on designated roadways. The emissions are represented geographically on each road segment within the state of Arizona spanning the 2017 to 2022 time period. This data product was developed as part of the Southwest Urban Corridor Integrated Field Laboratory (SW-IFL) project, which aims to provide new knowledge and tools that address urban environmental issues by integrating high-resolution observations, modeling, and civic engagement. The emissions data are provided in CSV (input data, ONR_FFCO2_AZ_county.csv) and GeoPackage form (output polyline objects - about 786,000 road segments, XXXX_AZ_v1.1.gpkg) designated by road class (interstates, arterials, collectors, local). The metadata file (Metadata_SW-IFL_Onroad_annualFFCO2_v1.1.docx) provides details about attributes and data formats. The GeoPackage emissions data are provided separately for local roads and nonlocal roads (interstates, arterials, collectors). The method file (Methods_SW-IFL_Onroad_annualFFCO2_v1.1.docx) describes the data processing flow and data sources. Update on 2024-04-17: Updates were made to both the input emission data file (.csv) and output segment-level emission file (.gpkg). There was an update in county-level emission input data (ONR_FFCO2_AZ_county.csv) and the entire road segments were reprocessed to reflect this update.Update on 2024-04-29: Update was made to one output segment-level emission file (Nonlocal_AZ_v1.0.gpkg). There was an error in the AADT values and the data were reprocessed to reflect this update.Update on 2024-10-22: Temporal coverage was extended to include 2022. VMT values were recalculated using new AADT data and the entire road segments were reprocessed to reflect these updates.

54 ENVIRONMENTAL SCIENCES↗

Cross sections for direct and dissociative ionization of NH3 and CS2 by electron impact

A crossed electron beam-molecular beam collision geometry is used to measure cross sections for the production of positive ions by electron impact on NH3 and CS2. Ionization cross-section data for NH3 and the values of various cross sections are presented, as well as ionization efficiency curves for CS2. Considerable differences are found between the various results on NH3. The present values are close to the data of Djuric et al. (1981). The semiempirical calculations of Hare and Meath (1987) differ considerably in the absolute values of cross sections. Discrepancies were observed in comparisons of cross sections of other fragment ions resulting from the ionization and dissociate ionization of NH3.

Rao, M. V. V. S.↗

Improving the Quality of Geothermal Data Through Data Standards and Pipelines Within the Geothermal Data Repository: Preprint

For machine learning outputs to be applicable to real world problems, high quality data are needed to ensure high quality results. With the more recent emphasis on machine learning in geothermal, there is an increasing need for greater focus on the quality of the data available for use in these projects. For example, Geothermal Operational Optimization Using Machine Learning (GOOML) utilized large quantities of geothermal power plant operational data to inform power plant operational configurations to maximize power generation. High quality datasets result from dependable sensors or devices collecting data, high frequency of measurements, sufficient data points, adequate metadata, reliable storage of data, and sufficient data curation. Another component that contributes to high quality data is reusability, which can be enhanced through data standardization. Data Standardization creates consistency in formatting and contents of like datasets, lessening preprocessing requirements and ensuring adequate information provided by a given dataset. The Geothermal Data Repository (GDR) aims to help improve data quality through automated data standardization for high-value datasets through the implementation of data pipelines alongside reliable and accessible long-term storage for datasets. As such, the GDR has decided to shift away from recommending the use of Excel-based content models and towards the implementation of automated data pipelines. This takes the burden of data standardization off the user and project team and will increase the availability of standardized geothermal data available through the GDR. A set of recommendations, or a data standard for each data type will exist with each data pipeline in order to advise data collection for maximum usability for future research. This paper serves to describe the GDR's proposed transition towards data standardization through automated data pipelines, to discuss the need for and value of such a shift, and to call for suggestions from the community regarding the most useful data standards and pipelines.

data↗

Continuously-Variable Vernier Scale

Easily fabricated device increases precision in reading graphical data. Continuously-variable vernier scale (CV VS) designed to provide greater accuracy to scientists and technologists in reading numerical values from graphical data. Placed on graph and used to interpolate coordinate value of point on curve or plotted point on figure within division on each coordinate axis. Requires neither measurement of line segments where projection of point intersects division nor calculation to quantify projected value. Very flexible device constructed with any kind of scale. Very easy to use, requiring no special equipment of any kind, and saves considerable amount of time if numerous points to be evaluated.

Miller, Irvin M.↗

Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.

97 MATHEMATICS AND COMPUTING↗

Spectroscopic Evidence of Keto-enol Tautomerism in Deliquesced Malonic Acid Particles

Scanning Transmission X-ray Microscopy combined with Near Edge X-ray Absorption Fine Structure Spectroscopy (STXM/NEXAFS), and optical microscopy coupled with Fourier Transform Infrared Spectroscopy (micro-FTIR) have been applied to observe hygroscopic growth and chemical changes in malonic acid particles deposited on substrates. Extent of the hygroscopic growth of particles has been quantified in terms of the corresponding water-to-solute ratios (WSR) based on STXM/NEXAFS and micro-FTIR data sets. WSR values derived separately from two applied methods displayed a remarkable agreement with previous data reported in the literature. Comparison of NEXAFS and FTIR spectra acquired at different relative humidity (RH) shows efficient keto-enol tautomerization of malonic acid, with the enol form dominated at higher RH. The keto-enol equilibrium constants were calculated using relevant peak intensities in the carbon and oxygen K-edge NEXAFS spectra as a function of RH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Year-long buoy-based observations of the air–sea transition zone off the US west coast

Abstract. Two buoys equipped with Doppler lidars owned by the US Department of Energy (DOE) were deployed off the coast of California in autumn of 2020 by Pacific Northwest National Laboratory. The buoys collected data for an entire annual cycle at two offshore locations proposed for offshore wind development by the Bureau of Ocean Energy Management. One of the buoys was deployed approximately 50 km off the coast near Morro Bay in central California in 1100 m of water. The second buoy was deployed approximately 40 km off Humboldt County in northern California in 625 m of water. The buoys provided the first-ever continuous measurements of the air–sea transition zone off the coast of California. The atmospheric and oceanographic characteristics of the area and estimates of annual energy production at both the Morro Bay and Humboldt wind energy areas show that both locations have a high wind energy yield and are prime locations for future floating offshore wind turbines. This article provides a description and comprehensive analysis of the data collected by the buoys, and a final post-processed dataset is uploaded to a data archive maintained by the DOE. Additional analysis was conducted to show the value of the data collected by the DOE buoys. All post-processed data from this study are available on the Wind Data Hub website: https://a2e.energy.gov/data# (last access: 14 September 2023). Near-surface, wave, current, and cloud datasets for Humboldt and Morro Bay are provided at https://doi.org/10.21947/1783807 (Krishnamurthy and Sheridan, 2023b) and https://doi.org/10.21947/1959715 (Krishnamurthy and Sheridan, 2023a), respectively. Lidar datasets for Humboldt and Morro Bay are provided at https://doi.org/10.21947/1783809 (Krishnamurthy and Sheridan, 2023d) and https://doi.org/10.21947/1959721 (Krishnamurthy and Sheridan, 2023c), respectively.

54 ENVIRONMENTAL SCIENCES↗

Relaxation and turbulence effects on sonic boom signatures

The rudimentary theory of sonic booms predicts that the pressure signatures received at the ground begin with an abrupt shock, such that the overpressure is nearly abrupt. This discontinuity actually has some structure, and a finite time is required for the waveform to reach its peak value. This portion of the waveform is here termed the rise phase, and it is with this portion that this presentation is primarily concerned. Any time characterizing the duration of the rise phase is loosely called the 'rise time.' Various definitions are used in the literature for this rise time. In the present discussion the rise time can be taken as the time for the waveform to rise from 10 percent of its peak value to 90 percent of its peak value. The available data on sonic booms that appears in the open literature suggests that typical values of shock over-pressure lie in the range of 30 Pa to 200 Pa, typical values of shock duration lie in the range of 150 ms to 250 ms, and typical values of the rise time lie in the range of 1 ms to 5 ms. The understanding of the rise phase of sonic booms is important because the perceived loudness of a shock depends primarily on the structure of the rise phase. A longer rise time typically implies a less loud shock. A primary question is just what physical mechanisms are most important for the determination of the detailed structure of the rise phase.

Pierce, Allan D.↗

Variable Time Base Integrator Circuit for Buffet Signal Measurements

A measurement circuit to obtain buffet data from wind tunnel models wherein a signal proportional to the average RMS value of buffet data is produced for subsequent recording. Feedback means are employed to suppress the D.C. portion of signals developed by the strain gages during dynamic testing. Automatic recording of gain settings of amplifiers employed in the circuit is also provided.

Batts, Colossie N.↗

Search for octupolar order in NpO 2 by neutron powder diffraction

The magnetic structure of neptunium dioxide (NpO 2 ) remains a mystery despite decades of research. We revisited the search for magnetic ordering in NpO 2 by performing a powder neutron diffraction experiment at low temperatures and relatively large values of Q. Diffraction data were collected for 300 MK, 15 K, and 35 K to understand the phase transition near 25 K. However, no significant changes in the neutron diffraction pattern were identified. Using the octupolar magnetic form factor j 6 , the maximum theoretical expected value of the magnetic moment (3.27 μ B ), the calculated magnetic Bragg peak intensities would not be observable in neutron powder diffraction data. This value is much larger than the previously estimated magnetic moment of ~0.1 μ B . In conclusion, supported by experimental results, these calculations suggest that unpolarized neutron powder diffraction is unsuitable for measuring octupolar ordering in NpO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Free Energies of Proton-Coupled Electron Transfer Reagents and Their Applications

Here, we present an update and revision to our 2010 review on the topic of proton- coupled electron transfer (PCET) reagent thermochemistry. Over the past decade, the data and thermochemical formalisms presented in that review have been of value to multiple fields. Concurrently, there have been advances in the thermochemical cycles and experimental methods used to measure these values. This Review (i) summarizes those advancements, (ii) corrects systematic errors in our prior review that shifted many of the absolute values in the tabulated data, (iii) provides updated tables of thermochemical values, and (iv) discusses new conclusions and opportunities from the assembled data and associated techniques. We advocate for updated thermochemical cycles that provide greater clarity and reduce experimental barriers to the calculation and measurement of Gibbs free energies for the conversion of X to XHn in PCET reactions. In particular, we demonstrate the utility and generality of reporting potentials of hydrogenation, E°(V vs H 2 ), in almost any solvent and how these values are connected to more widely reported bond dissociation free energies (BDFEs). The tabulated data demonstrate that E°(V vs H 2 ) and BDFEs are generally insensitive to the nature of the solvent and, in some cases, even to the phase (gas versus solution). This Review also presents introductions to several emerging fields in PCET thermochemistry to give readers windows into the diversity of research being performed. Some of the next frontiers in this rapidly growing field are coordination-induced bond weakening, PCET in novel solvent environments, and reactions at material interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗