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At least 1,171 records · Page 65

Wall adjustment strategy software for use with the NASA Langley 0.3-meter transonic cryogenic tunnel adaptive wall test section

The Wall Adjustment Strategy (WAS) software provides successful on-line control of the 2-D flexible walled test section of the Langley 0.3-m Transonic Cryogenic Tunnel. This software package allows the level of operator intervention to be regulated as necessary for research and production type 2-D testing using and Adaptive Wall Test Section (AWTS). The software is designed to accept modification for future requirements, such as 3-D testing, with a minimum of complexity. The WAS software described is an attempt to provide a user friendly package which could be used to control any flexible walled AWTS. Control system constraints influence the details of data transfer, not the data type. Then this entire software package could be used in different control systems, if suitable interface software is available. A complete overview of the software highlights the data flow paths, the modular architecture of the software and the various operating and analysis modes available. A detailed description of the software modules includes listings of the code. A user's manual is provided to explain task generation, operating environment, user options and what to expect at execution.

Wolf, Stephen W. D.↗

Learning to Predict and Improve Build Successes in Package Ecosystems

Software has become increasingly complex, with a typical application depending on tens or hundreds of packages. Finding compatible versions and build configurations of these packages is challenging. This paper presents a method to learn the likelihood of software build success, and techniques for leveraging this information to guide dependency solvers to better software configurations. We leverage the heavily parameterized package recipes from the Spack package manager to produce a training data set of builds, and we use Graph Neural Networks to learn whether a given package configuration will build successfully or not. We apply our tool to the U.S. Exascale Computing Project’s software stack. We demonstrate its effectiveness in predicting whether a given package will build successfully. We show that our technique can be used to improve the solutions generated by dependency solvers, reducing the need for developers to find working builds by trial and error.

97 MATHEMATICS AND COMPUTING↗

Q-Fibre Quarterly Performance Progress Report

The project titled Quantitative Strain Monitoring for Well and Seal Integrity through Wellbore Fiber Optic Cable s, or Q-Fibre in short, is a multi-national collaborative project under the Clean Energy Transitional Partnership (CETP) program. The lead organization of the project is the Norwegian Geotechnical Institute (NGI), and the LLNL team joins as a beneficiary member. The LLNL team receives the funding from the U.S. Department of Energy with the amount of $\$$1 million across three years, and the budget is primarily allocated to Work Package 3 (WP3) of the project, which focuses on Numerical Modeling of Fiber Optic Cable Data . Figure 1 presents all work packages involved in the project and corresponding lead organization for each work package. The LLNL team leads WP3.

42 ENGINEERING↗

Data bus system development program

Two data bus systems were designed fabricated, Data Bus System I and Data Bus System II. The technical features of the delivered hardware include the following: (1) 5 MHz selfclocking data bus; (2) bidirectional communications utilizing Manchester Code at data rates in excess of 20,000 words per second; (3) utilization of MSI COS/MOS technology (4) probability of accepting an erroneous data bit less than 1 in 10 to the 25th power (5) low power consumption (50 to 1 reduction in quiescent current over P/MOS) (6) compatibility with projected high density packaging. Three distinct types of data bus remote terminals were developed: the subsystem interface unit, the combination of an electronic interface unit and a standard interface unit-serial, and an SIU/Preprocessor.

Harrison, J. S. J.↗

CHESS 2025: Leaf Area Index (LAI) for meadow, shrub, tree, and understory vegetation

This dataset contains Leaf Area Index (LAI) measurements made as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Data were collected in the Upper Gunnison Basin, Colorado, across three study domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). Field observations of LAI were collected within 72 hours of airborne data collection by the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. LAI measurements were collected using the LICOR LAI-2200C Plant Canopy Analyzer following protocols outlined in the instrument manual (LI-COR 2019). Sampling targeted four distinct vegetation types: meadows, shrubs, trees, and aspen forest understory. We have archived data separately by site type because different field methods were used for each. At meadow sites, measurements were made at the four corners of 1m x 1m plots, with the instrument moving inward toward the center of the plot. At shrub sites, we measured the canopies of individual shrubs. At tree sites, we made measurements within a 10m x 10m subplot centered around a focal tree, with 30 observations taken on a regular grid. At aspen understory sites, we measured overstory trees following the tree protocol and understory herbaceous vegetation following the meadow protocol. All measurements included above-canopy (A) and below-canopy (B) readings, with specific protocols for scattering correction measurements in direct-sun conditions. Data were processed using the R package `rlai` (Worsham 2025). This package includes functions to calculate LAI, gap fraction, apparent clumping factor (Ω), scattering correction, and other canopy metrics. Package contents: Full file descriptions appear in ‘flmd.csv’. Files named according to the convention ‘lai_*_summary_data_cleaned.csv’ contain summary values of LAI, apparent clumping factor (Ωapp), and scattering correction factors for each site. These are the analysis-ready products that most data users will work with. Files named ‘lai_*_metadata_cleaned.csv’ contain additional site-level observations made during field collection. We have also archived intermediate and supplementary data for users who wish to check our processing approach or apply alternative methods. ‘raw_lai_2200C.zip’ contains the raw files as read from the LI-COR instrument, with no processing applied, in TXT format. The zip archive contains subdirectories by site type, which are further subdivided by sampling area. Filenames correspond to the sampling site number. ‘intermediate_results.zip’ contains detailed output from the processing routines, in JSON format. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘scattering_correction_logs.zip’ contains logfiles from the implementation of Kobayashi et al.'s (2013) scattering correction algorithm. The logfiles report values of several parameters at each iteration of the algorithm, as the model converges toward a stable solution. They are intended for users who want to verify scattering correction performance. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘spot_checks.csv’ reports LAI and other values for a small number of files processed with LI-COR FV2200 software (LI-COR 2013) using the same control parameters as in our R-based approach. Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). All zip files can be expanded with common archive utilities. TXT, CSV, and JSON files can be ingested into R or Python computing environments or read in common text editor utilities. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. * Todorov and Worsham are co–first authors.

2018 NEON and 2025 CHESS Campaigns↗

American Meteorological Society (AMS) - The Modern Era Retrospective-Analysis for Research and Applications (MERRA) Data and Accessibility

The AM Short Course on The Modern Era Retrospective-analysis for Research and Applications (MERRA) data and accessibility will be held on January 11, 2009 preceding the 89th Annual Meeting in Phoenix, Arizona. Preliminary programs, registration, hotel, and general information will be posted on the AMS Web site in mid-September 2008. Retrospective-analyses (or reanalyses) have been established as an important tool in weather and climate research over the last decade. As computer power increases, the data assimilation and modeling systems improve and become more advanced, the input data quality increases and so reanalyses become more reliable. In 2008, NASA Global Modeling and Assimilation Office began producing a new reanalysis called the Modem Era Retrospective-analysis for Research and Applications (MERRA). The initial data from the reanalysis has been made available to the community and should be complete through 30 years (1979-present) by Fall of 2009. MERRA has taken advantage of the advancement of computing resources to provide users more data than previously available. The native spatial resolution is nominally 1/2 degrees and the surface two dimensional data are one hourly frequency. In addition to the meteorological analysis data, complete mass, energy and momentum budget data and also stratospheric data are provided. The eventual data holdings will exceed 150Tb. In order to facilitate user accessibility to the data, it will be stored in online hard drives (not tape storage) and available through several portals. Subsetting tools will also be available to allow users to tailor their data requests. The goals of this short course are to provide hands on users of reanalyses instruction on MERRA systems and also interactive experience with the online data and access tools. The course is intended for students and research scientists who will be actively interested in accessing and applying MERRA data in their weather, climate or applications work. The course has three parts. There will be an overview of the MERRA system, the validation of the system and the native data format. Second, Instructors will provide examples of weather and climate data analysis using various software packages (primarily GrADS) as well as the online access tools for subsetting and download, as well as visualization (e.g. Giovanni and Google Earth). This will also include examples on changing the data format to fit user's preferences and also to regrid the data for comparisons to other reanalyses and observational data. Lastly, there will he time set aside for participants to have hands on access to the data and software while interacting with the instructors and other developers. The course convener is Dr. Michael Bosilovich, NASA GSFC Global Modeling and Assimilation Office (GMAO). He will be joined by several GMAO, Goddard Earth Science Data and information Services Center (GES DISC) and Software Integration and Visualization Office (SIVO) staff.

daSilva, Arlindo↗

Trace Metal Uptake and Mercury Methylation by Sediments from a Stream in Tennessee

The formation and transport of methylmercury (MeHg), a neurotoxin, in aquatic environments is a global concern for human health as MeHg can bioaccumulate and biomagnify to high concentrations in aquatic food webs. MeHg is formed by conversion from inorganic mercury through microbial mediated methylation. Sulfate-reducing bacteria have been identified as the primary organisms responsible for MeHg production. Pure-culture studies suggest that low availability of cobalt and copper may inhibit mercury methylation, but whether such limitations occur in the environment is unclear. To explore the possible interaction between trace metal availability and mercury methylation, sediments from the East Fork Poplar Creek in Oak Ridge, Tennessee were sampled and then incubated in the presence and absence of added dissolved cobalt and copper. Three types of data are provided in this package. The first reports the uptake of dissolved cobalt and copper by these stream sediments on short time scales (24 hours) in the form of final dissolved and adsorbed concentrations. The second data component consists of a time series of dissolved concentrations and pH values for stream sediments incubated with artificial stream water containing different addition levels of dissolved cobalt or copper. The dissolved concentrations reported include total iron, manganese, sulfur, phosphorus, nickel, zinc and cobalt, dissolved concentrations of sulfate and orthophosphate, and the amount of cobalt or copper adsorbed by the sediment. The third data component reports data at 0 and 72 hours of incubation time for stream sediments to which cobalt was added. These data include concentrations of methylmercury with isotope labeling to enable determination of methylation and demethylation rates as well as dissolved concentrations of sulfate, phosphate, chloride, iron, cobalt, and organic carbon. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units. Note that "u" is used in place of Greek lower-case mu to indicate the micro prefix on units. A Table of Contents file (Data_package_TableofContents.txt) provides an index for the data contained in the individual files.

54 ENVIRONMENTAL SCIENCES↗

The Weather Analysis Display (WAND) Tool: Developing a Meteorological Data Display Tool for Situational Awareness During Day-Of-Launch of Space Launch Vehicles Using Python

Atmospheric conditions are an important driver in the design and operation of space launch vehicles. The Profile Envision and Splicing Tool (PRESTO) was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NE) to generate vertically complete atmospheric profiles from various data sources at NASA’s Kennedy Space Center (KSC), co-located on the United States Air Force (USAF) Eastern Range (ER), for NASA’s Space Launch System (SLS) day-of-launch (DOL) loads and trajectory analysis. PRESTO was designed solely to generate a vertically complete atmospheric profile (Orcutt et al., 2017). However, NE has also been tasked to provide a quality assessment of meteorological data examined on DOL, which goes beyond PRESTO’s utility. Thus, NE developed the Weather Analysis Display (WAND) to visualize data from all available observation systems in conjunction with climatological databases. WAND can display data from various sources in multiple ways, including Skew-T Log-P plots, time-height cross sections, and time series. WAND was developed in Python 3 taking advantage of common packages, such as NumPy for data handling, SciPy for mathematical functions, Matplotlib for data visualization, and Tkinter for the execution of the Graphical User Interface (GUI).

Orcutt, John M.↗

Opportunities for Utilizing the International Space Station for Studies of F2- Region Plasma Science and High Voltage Solar Array Interactions with the Plasma Environment

The near circular, 51.6deg inclination orbit of the International Space Station (ISS) is maintained within an altitude range of approximately 300 km to 400 km providing an ideal platform for conducting in-situ studies of space weather effects on the mid and low-latitude F-2 region ionosphere. The Floating Potential Measurement Unit (FPMU) is a suite of instruments installed on the ISS in August 2006 which includes a Floating Potential Probe (FPP), a Plasma Impedance Probe (PIP), a Wide-sweep Langmuir Probe (WLP), and a Narrow-sweep Langmuir Probe (NLP). The primary purpose for deploying the FPMU is to characterize ambient plasma temperatures and densities in which the ISS operates and to obtain measurements of the ISS potential relative to the space plasma environment for use in characterizing and mitigating spacecraft charging hazards to the vehicle and crew. In addition to the engineering goals, data from the FPMU instrument package is available for collaborative multi-satellite and ground based instrument studies of the F-region ionosphere during both quiet and disturbed periods. Finally, the FPMU measurements supported by ISS engineering telemetry data provides a unique opportunity to investigate interactions of the ISS high voltage (160 volt) solar array system with the plasma environment. This presentation will provide examples of FPMU measurements along the ISS orbit including night-time equatorial plasma density depletions sampled near the peak electron density in the F2-region ionosphere, charging phenomenon due to interaction of the ISS solar arrays with the plasma environment, and modification of ISS charging due to visiting vehicles demonstrating the capabilities of the FPMU probes for monitoring mid and low latitude plasma processes as well as vehicle interactions with the plasma environment.

Minow, Joseph I.↗

Understanding the structural basis of HIV-1 restriction by the full length double-domain APOBEC3G

APOBEC3G, a member of the double-domain cytidine deaminase (CD) APOBEC, binds RNA to package into virions and restrict HIV-1 through deamination-dependent or deamination-independent inhibition. Mainly due to lack of a full-length double-domain APOBEC structure, it is unknown how CD1/CD2 domains connect and how dimerization/multimerization is linked to RNA binding and virion packaging for HIV-1 restriction. We report rhesus macaque A3G structures that show different inter-domain packing through a short linker and refolding of CD2. The A3G dimer structure has a hydrophobic dimer-interface matching with that of the previously reported CD1 structure. A3G dimerization generates a surface with intensified positive electrostatic potentials (PEP) for RNA binding and dimer stabilization. Unexpectedly, mutating the PEP surface and the hydrophobic interface of A3G does not abolish virion packaging and HIV-1 restriction. The data support a model in which only one RNA-binding mode is critical for virion packaging and restriction of HIV-1 by A3G.

59 BASIC BIOLOGICAL SCIENCES↗

Packaging printed circuit boards: A production application of interactive graphics

The structure and use of an Interactive Graphics Packaging Program (IGPP), conceived to apply computer graphics to the design of packaging electronic circuits onto printed circuit boards (PCB), were described. The intent was to combine the data storage and manipulative power of the computer with the imaginative, intuitive power of a human designer. The hardware includes a CDC 6400 computer and two CDC 777 terminals with CRT screens, light pens, and keyboards. The program is written in FORTRAN 4 extended with the exception of a few functions coded in COMPASS (assembly language). The IGPP performs four major functions for the designer: (1) data input and display, (2) component placement (automatic or manual), (3) conductor path routing (automatic or manual), and (4) data output. The most complex PCB packaged to date measured 16.5 cm by 19 cm and contained 380 components, two layers of ground planes and four layers of conductors mixed with ground planes.

Perrill, W. A.↗

Restoration of APOLLO Data by the NSSDC and PDS Lunar Data Node

The Apollo Lunar Surface Experiment Packages (ALSEPs), suites of instruments deployed by the Apollo 12. 14, 15, 16 and 17 astronauts on the lunar surface, still represent the only in-situ measurements of the Moon's environment taken over long time periods, Much of these data are housed at the National Space Science Data Center (NSSDC) at Goddard Space Flight Center but are in forms that are not readily usable, such as microfilm, hardcopy, and magnetic tapes with older, obsolete formats. The Lunar Data Node (LDN) has been formed under the auspices of the Planetary Data System (PDS) Geosciences Node to put relevant, scientifically important Apollo data into accessible digital form for use by researchers and mission planners. The LDN has prioritized the restoration of these data based on their scientific and engineering value and the level of effort required. We will report on progress made and plans for future data restorations.

Williams, David R.↗

Mappymatch FKA: YAMM (Yet Another Map-Matcher) [SWR 22-38]

A surprisingly non-trivial technical challenge is to associate points in space (e.g., GPS data) with specific segments of a road network or map. The software package ( allows users to match GPS point data to a road network (commonly known as "map matching"). The software is designed such that a user could match a set of GPS points to a variety of different road network representations using a variety of map matching algorithms. There are currently several "built-in" road networks and map matching algorithms but the software has been designed to enable new ones to be added with minimal overhead.

Reinicke, Nicholas↗

Machine learning tools for epigenetics

The software provides machine learning analysis and visualization to detect patterns in epigenetic data, including conventional machine learning and statistical methods, and open-source packages like pyBigWig (https://github.com/deeptools/pyBigWig) for data processing. The software is written in python, it uses some python libraries.

Kim, Anastasiia↗

A Study of Cirrus Clouds and Aerosols in the Upper Troposphere using Models and Satellite Data

This report is the final report for the Cooperative Agreement NCC2-1213. It is a compilation of publications produced under this Cooperative Agreement and conference presentations. The tasks for the Aerosol Physical Chemistry Model for the Upper Troposphere include: Task 1: To compare APCM predictions against the SUCCESS data and other aircraft campaigns and to investigate the role of aerosol composition on cirrus cloud nucleation; Task 2: To study the seasonal evolution and spatial distribution of upper-tropospheric tropical and polar cirrus; Task 3: To investigate CLAES cirrus data with other complementary (TOGA-COARE and CEPEX) data. Tasks for Upper Tropospheric Cirrus Clouds include: Task 1: Assemble 3-hourly (or more frequent) meteorological satellite data fiom geostationary satellites to obtain a global, or nearly global, dataset of infiared brightness temperatures as a function of time for airborne experimental periods; Task 2: Explore methods to improve the cloud top altitude distributions calculated fiom meteorological satellite data. This will focus on linlung the 6.5 micron channel geostationary brightness temperatures and the 10.5 micron brightness temperatures; Task 3: Explore methods to differentiate convective fiom stratiform cloudiness; Task 4: Perform trajectory analyses using an existing trajectory modeling package that links the cloud data with air mass histories; Task 5: Apply techniques from tasks 1 through 4 to provide meteorological support to the CRYSTAL-FACE mission, both in its preparation and deployment phases. The report include four published articles and two slide presentations.

Bergstrom, Robert W.↗

pvOps v.0.1

This python package contains a series of functions to facilitate fusion of text-based and time series production data collected at photovoltaic sites. The package also contains example datasets and tutorials to help demonstrate how the functions can be used. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1554 O

Gunda, Thushara↗

Stennis Space Center Salinity Drifter Project. A Collaborative Project with Hancock High School, Kiln, MS

Presentation topics include: importance of salinity of coastal waters, habitat switching algorithm, habitat switching module, salinity estimates from Landsat for Sabine Calcasieu Basin, percent of time inundated in 2006, salinity data, prototyping the system, system as packaged for field tests, salinity probe and casing, opening for water flow, cellular antenna used to transmit data, preparing to launch, system is launched in the Pearl River at Stennis Space Center, data are transmitted to Twitter by cell phone modem every 15 minutes, Google spreadsheet I used to import the data from the Twitter feed and to compute salinity (from conductivity) and display charts of salinity and temperature, results are uploaded to NASA's Applied Science and Technology Project Office Webpage.

Kalcic, Maria↗