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At least 397 records · Page 22

Infinite possibilities: Computational structures technology

Computational Fluid Dynamics (or CFD) methods are very familiar to the research community. Even the general public has had some exposure to CFD images, primarily through the news media. However, very little attention has been paid to CST--Computational Structures Technology. Yet, no important design can be completed without it. During the first half of this century, researchers only dreamed of designing and building structures on a computer. Today their dreams have become practical realities as computational methods are used in all phases of design, fabrication and testing of engineering systems. Increasingly complex structures can now be built in even shorter periods of time. Over the past four decades, computer technology has been developing, and early finite element methods have grown from small in-house programs to numerous commercial software programs. When coupled with advanced computing systems, they help engineers make dramatic leaps in designing and testing concepts. The goals of CST include: predicting how a structure will behave under actual operating conditions; designing and complementing other experiments conducted on a structure; investigating microstructural damage or chaotic, unpredictable behavior; helping material developers in improving material systems; and being a useful tool in design systems optimization and sensitivity techniques. Applying CST to a structure problem requires five steps: (1) observe the specific problem; (2) develop a computational model for numerical simulation; (3) develop and assemble software and hardware for running the codes; (4) post-process and interpret the results; and (5) use the model to analyze and design the actual structure. Researchers in both industry and academia continue to make significant contributions to advance this technology with improvements in software, collaborative computing environments and supercomputing systems. As these environments and systems evolve, computational structures technology will evolve. By using CST in the design and operation of future structures systems, engineers will have a better understanding of how a system responds and lasts, more cost-effective methods of designing and testing models, and improved productivity. For informational and educational purposes, a videotape is being produced using both static and dynamic images from research institutions, software and hardware companies, private individuals, and historical photographs and drawings. The extensive number of CST resources indicates its widespread use. Applications run the gamut from simpler university-simulated problems to those requiring solutions on supercomputers. In some cases, an image or an animation will be mapped onto the actual structure to show the relevance of the computer model to the structure. Transferring the digital files to videotape presents a number of problems related to maintaining the quality of the original image, while still producing a broadcast quality videotape. Since researchers normally do not create a computer image using traditional composition theories or video production requirements, often the image loses some of its original digital quality and impact when transferred to videotape. Although many CST images are currently available, those that are edited into the final project must meet two important criteria: they must complement the narration, and they must be broadcast quality when recorded on videotape.

Beam, Sherilee F.↗

ADEOS Total Ozone Mapping Spectrometer (TOMS) Data Products User's Guide

Two data products from the Total Ozone Mapping Spectrometer (ADEOS/TOMS) have been archived at the Distributed Active Archive Center, in the form of Hierarchical Data Format files. The ADEOS/ TOMS began taking measurements on September 11, 1996, and ended on June 29, 1997. The instrument measured backscattered Earth radiance and incoming solar irradiance; their ratio was used in ozone retrievals. Changes in the reflectivity of the solar diffuser used for the irradiance measurement were monitored using a carousel of three diffusers, each exposed to the degrading effects of solar irradiation at different rates. The algorithm to retrieve total column ozone compares measured Earth radiances at sets of three wavelengths with radiances calculated for different total ozone values, solar zenith angles, and optical paths. The initial error in the absolute scale for TOMS total ozone is 3 percent, the one standard deviation random error is 2 percent, and the drift is less than 0.5 percent over the 9-month data record. The Level 2 product contains the measured radiances, the derived total ozone amount, and reflectivity information for each scan position. The Level 3 product contains daily total ozone and reflectivity in a 1-degree latitude by 1.25 degrees longitude grid. The Level 3 files containing estimates of UVB at the Earth surface and tropospheric aerosol information will also be available. Detailed descriptions of both HDF data files and the CDROM product are provided.

Krueger, A.↗

Earth Probe Total Ozone Mapping Spectrometer (TOMS) Data Product User's Guide

Two data products from the Earth Probe Total Ozone Mapping Spectrometer (EP/TOMS) have been archived at the Distributed Active Archive Center, in the form of Hierarchical Data Format files. The EP/ TOMS began taking measurements on July 15, 1996. The instrument measures backscattered Earth radiance and incoming solar irradiance; their ratio is used in ozone retrievals. Changes in the reflectivity of the solar diffuser used for the irradiance measurement are monitored using a carousel of three diffusers, each exposed to the degrading effects of solar irradiation at different rates. The algorithm to retrieve total column ozone compares measured Earth radiances at sets of three wavelengths with radiances calculated for different total ozone values. The initial error in the absolute scale for TOMS total ozone is 3 percent, the one standard deviation random error is 2 percent, and the drift is less than 0.5 percent over the first year of data. The Level-2 product contains the measured radiances, the derived total ozone amount, and reflectivity information for each scan position. The Level-3 product contains daily total ozone and reflectivity in a 1-degree latitude by 1.25 degrees longitude grid. Level-3 files containing estimates of LTVB at the Earth surface and tropospheric aerosol information are also available, Detailed descriptions of both HDF data-files and the CD-ROM product are provided.

McPeters, R.↗

Real Data and Rapid Results: Ocean Color Data Analysis with Giovanni (GES DISC Interactive Online Visualization and ANalysis Infrastructure)

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step addressing the challenge of using archived Earth Observing System (EOS) data for regional or global studies by developing an infrastructure with a World Wide Web interface which allows online, interactive, data analysis: the GES DISC Interactive Online Visualization and ANalysis Infrastructure, or "Giovanni." Giovanni provides a data analysis environment that is largely independent of underlying data file format. The Ocean Color Time-Series Project has created an initial implementation of Giovanni using monthly Standard Mapped Image (SMI) data products from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission. Giovanni users select geophysical parameters, and the geographical region and time period of interest. The system rapidly generates a graphical or ASCII numerical data output. Currently available output options are: Area plot (averaged or accumulated over any available data period for any rectangular area); Time plot (time series averaged over any rectangular area); Hovmeller plots (image view of any longitude-time and latitude-time cross sections); ASCII output for all plot types; and area plot animations. Future plans include correlation plots, output formats compatible with Geographical Information Systems (GIs), and higher temporal resolution data. The Ocean Color Time-Series Project will produce sensor-independent ocean color data beginning with the Coastal Zone Color Scanner (CZCS) mission and extending through SeaWiFS and Moderate Resolution Imaging Spectroradiometer (MODIS) data sets, and will enable incorporation of Visible/lnfrared Imaging Radiometer Suite (VIIRS) data, which will be added to Giovanni. The first phase of Giovanni will also include tutorials demonstrating the use of Giovanni and collaborative assistance in the development of research projects using the SeaWiFS and Ocean Color Time-Series Project data in the online Laboratory for Ocean Color Users (LOCUS). The synergy of Giovanni with high-quality ocean color data provides users with the ability to investigate a variety of important oceanic phenomena, such as coastal primary productivity related to pelagic fisheries, seasonal patterns and interannual variability, interdependence of atmospheric dust aerosols and harmful algal blooms, and the potential effects of climate change on oceanic productivity.

Acker, J. G.↗

Development and Implementation of Efficiency-Improving Analysis Methods for the SAGE III on ISS Thermal Model Originating

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument is the fifth in a series of instruments developed for monitoring aerosols and gaseous constituents in the stratosphere and troposphere. SAGE III will be delivered to the International Space Station (ISS) via the SpaceX Dragon vehicle in 2015. A detailed thermal model of the SAGE III payload has been developed in Thermal Desktop (TD). Several novel methods have been implemented to facilitate efficient payload-level thermal analysis, including the use of a design of experiments (DOE) methodology to determine the worst-case orbits for SAGE III while on ISS, use of TD assemblies to move payloads from the Dragon trunk to the Enhanced Operational Transfer Platform (EOTP) to its final home on the Expedite the Processing of Experiments to Space Station (ExPRESS) Logistics Carrier (ELC)-4, incorporation of older models in varying unit sets, ability to change units easily (including hardcoded logic blocks), case-based logic to facilitate activating heaters and active elements for varying scenarios within a single model, incorporation of several coordinate frames to easily map to structural models with differing geometries and locations, and streamlined results processing using an Excel-based text file plotter developed in-house at LaRC. This document presents an overview of the SAGE III thermal model and describes the development and implementation of these efficiency-improving analysis methods.

Liles, Kaitlin↗

Spatial Link Coverage Projections for the Glenn Research Center Communication Analysis Suite (GCAS)

Space communications are a fundamental part of every NASA mission, and reliable space communications are essential. Precise planning, simulation, and analysis of communications abilities are needed to know exactly what data rates, visibility times, and signal strength can be expected during the real missions. The goal of this work was to take a 3D icosphere, where each face was a point to be evaluated, and display the link performance onto a 2D projection of celestial bodies for links to a node location that could be spatially located at any of the icosahedral faces. 2D projections were produced for a wide range of spatial link grid sizes and compressed into low-size MAT files for ease of access and rapid implementation. The final icosahedral projections can be displayed onto various celestial body maps, using ultra-high-resolution maps for stitching. The results have proven satisfactory and are planned to support various simulation efforts.

communication link analysis↗

GADRAS Batch Inject Tool User Guide

Gamma Detector Response and Analysis Software (GADRAS) is used by the radiation detection and emergency response community to perform modeling and spectral analysis for gamma detector systems. Built into GADRAS is the ability to define a detector, geometry, background characteristics and source composition to generate synthetic spectra for drills and exercises (injects). Consequence Management is currently in development of a sample result data simulator tool in which a deposition model is probed for source conditions at moments in time and locations in space. These values are used to generate realistic sample results for use in drills and exercises. In addition to sample results, there is a need to simulate the actual spectra that would be observed in the field by downlooking HPGe instruments given a deposition activity. This way, the FRMAC Gamma Spectroscopist can practice their process of generating quantified results from spectra on realistic data as well. Recognizing the decades of work done in GADRAS to accurately generate synthetic spectra, this team decided to build a link between the new simulator and GADRAS to generate these spectra quickly and easily. The simulator tool will generate a file that specifies the name of the spectra, its location, date/time of measurement, duration of measurement, height off the ground, and the deposition activity and age for every radionuclide in the simulation. Then, a new tool within the Inject Tab of GADRAS was developed to read in this file given a detector selection and generate In-Situ spectra for each row in the file in any file format the user chooses. This way, simulation cell staff can take these files and then upload them to the appropriate data system (RAMS or RadResponder) for use during drills and exercises. An advanced feature of this tool allows for generating any spectra given an appropriate model and mapping of source to model layer in the batch inject tool. This way, spectra from field sample counts, mobile laboratories, or even fixed laboratories can be generated in bulk given an estimate of the radioactivity concentration or total radioactivity in an import file. This expands the capabilities of this tool a great deal and will make it a more useful tool for CM and others to help estimate detector response for nearly any situation. This user guide will explain the steps needed to perform a batch inject file generation.

61 RADIATION PROTECTION AND DOSIMETRY↗

Using active learning to improve quasar identification for the DESI spectra processing pipeline

The Dark Energy Spectroscopic Instrument (DESI) survey uses an automatic spectral classification pipeline to classify spectra. QuasarNET is a convolutional neural network used as part of this pipeline originally trained using data from the Baryon Oscillation Spectroscopic Survey (BOSS). In this paper we implement an active learning algorithm to optimally select spectra to use for training a new version of the QuasarNET weights file using only DESI data, with the goal of improving classification accuracy. This active learning algorithm includes a novel outlier rejection step using a Self-Organizing Map to ensure we label spectra representative of the larger quasar sample observed in DESI. We perform two iterations of the active learning pipeline, assembling a final dataset of 5600 labeled spectra, a small subset of the approximately 1.3 million quasar targets in DESI's Data Release 1. When splitting the spectra into training and validation subsets we achieve similar performance to the previously trained weights file in completeness and purity calculated on the validation dataset but do so with less than one tenth of the amount of training data. The new weights also more consistently classify objects in the same way when used on unlabeled data compared to the old weights file. In the process of improving QuasarNET's classification accuracy we discovered a systemic error in QuasarNET's redshift estimation and used our findings to improve our understanding of QuasarNET's redshifts.

Machine learning↗

TEAMER: Performance mapping of Re Vision's Persistance PTO

Contains datasets from experimental measurements that were used to validate Re Vision's Persistence PTO's efficiency and performance. These measurements were obtained using a dynamometer test bench setup. The data includes open-circuit voltage and loss measurements to validate machine characteristics, efficiency mapping tests to determine the generator's performance mapping, and efficiency mapping tests to determine the converter's efficiency over the feasible operating range. This data was collected between June 2023 and September 2023. The data was collected at the National Renewable Energy Laboratory's Flatirons Campus, Colorado, United States. The data was collected using NREL's 5-kW dynamometer test bench, equipped with a torque sensor and various voltage and current sensors fed to a dedicated data acquisition system. Units for the data are included in the data file headers for each data series. A text editor or spreadsheet software such as Excel is required to view the *.csv data. The data are also provided in *.mat files. To view data plots, a Matlab script with *.mat files are provided.

16 TIDAL AND WAVE POWER↗

Basin and Range Investigation for Developing Geothermal Energy: Exploration Data

This data package includes exploration material from the Basin & Range Investigation for Developing Geothermal Energy [in Hidden Systems] project (BRIDGE), which is part of a broader initiative to advance the exploration of hidden geothermal resources in the Basin & Range Province of the western U.S. Data modalities include a helicopter-borne time-domain electromagnetic survey, magnetotellurics, 2-meter temperature measurements, ground-based gravity and legacy aeromagnetic surveys, geochemistry, geologic mapping, LiDAR analysis, 3D models, associated geospatial data, and a bibliography of existing data and references utilized in prospect characterization and conceptual modeling. Key files are in CSV, Geosoft, and Geotools formats. Please refer to READMEs for dataset-specific information. Where applicable, acquisition data and inversion models for a particular prospect or area of interest are organized separately. This BRIDGE data package is the product of a collaboration led by Sandia National Laboratories with partners from Geologica Geothermal Group, Inc., the U.S. Navy Geothermal Program Office, and consultants Steven Sewell (Australis Geoscience Ltd) and William Cumming (Cumming Geoscience). The project's areas of interest (AOIs) are based off priority areas of interest in the southwestern portion of the Nevada Play Fairway map, distribution across tectonic provinces, accessibility, and the project team's extensive experience in the region. AOIs cover about a dozen basins that include unexplored prospects, partially explored prospects, and some developed analogue resources that provide validation cases. Many unexplored and partially explored prospects are on U.S. Department of Defense (DoD) land, though adjacent lands are included as well.

15 GEOTHERMAL ENERGY↗

SU-F-T-233: Evaluation of Treatment Delivery Parameters Using High Resolution ELEKTA Log Files

Purpose: As modern linacs have become more technologically advanced with the implementation of IGRT and IMRT with HDMLCs, a requirement for more elaborate tracking techniques to monitor components’ integrity is paramount. ElektaLog files are generated every 40 milliseconds, which can be analyzed to track subtle changes and provide another aspect of quality assurance. This allows for constant monitoring of fraction consistency in addition to machine reliability. With this in mind, it was the aim of the study to evaluate if ElektaLog files can be utilized for linac consistency QA. Methods: ElektaLogs were reviewed for 16 IMRT patient plans with >16 fractions. Logs were analyzed by creating fluence maps from recorded values of MLC locations, jaw locations, and dose per unit time. Fluence maps were then utilized to calculate a 2D gamma index with a 2%–2mm criteria for each fraction. ElektaLogs were also used to analyze positional errors for MLC leaves and jaws, which were used to compute an overall error for the MLC banks, Y-jaws, and X-jaws by taking the root-meansquare value of the individual recorded errors during treatment. Additionally, beam on time was calculated using the number of ElektaLog file entries within the file. Results: The average 2D gamma for all 16 patient plans was found to be 98.0±2.0%. Recorded gamma index values showed an acceptable correlation between fractions. Average RMS values for MLC leaves and the jaws resulted in a leaf variation of roughly 0.3±0.08 mm and jaw variation of about 0.15±0.04 mm, both of which fall within clinical tolerances. Conclusion: The use of ElektaLog files for day-to-day evaluation of linac integrity and patient QA can be utilized to allow for reliable analysis of system accuracy and performance.

60 APPLIED LIFE SCIENCES↗

Molecular simulation data for 'Data-guided Multi-Map variables for ensemble refinement of molecular movies'

These trajectories, scripts, and analysis performed on Summit underly the work published as 'Data-guided Multi-Map variables for ensemble refinement of molecular movies'. The trajectories include equilibrium and non-equilibrium sampling of ADK, CODH, and FLPP3, the scripts used to build the systems, and the scripts used to analyze the output. The directory structure is explained further in an internal README file.

59 BASIC BIOLOGICAL SCIENCES↗

BOREAS Forest Cover Data Layers of the NSA in Raster Format

This data set was processed by BORIS staff from the original vector data of species, crown closure, cutting class, and site classification/subtype into raster files. The original polygon data were received from Linnet Graphics, the distributor of data for MNR. In the case of the species layer, the percentages of species composition were removed. This reduced the amount of information contained in the species layer of the gridded product, but it was necessary in order to make the gridded product easier to use. The original maps were produced from 1:15,840-scale aerial photography collected in 1988 over an area of the BOREAS NSA MSA. The data are stored in binary, image format files and they are available from Oak Ridge National Laboratory. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗

Distributed computing strategies for processing of FT-ICR MS imaging datasets for continuous mode data visualization

High-resolution Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging enables the spatial mapping and identification of biomolecules from complex surfaces. The need for long time-domain transients, and thus large raw file sizes, results in a large amount of raw data (“big data”) that must be processed efficiently and rapidly. This can be compounded by largearea imaging and/or high spatial resolution imaging. For FT-ICR, data processing and data reduction must not compromise the high mass resolution afforded by the mass spectrometer. The continuous mode “Mosaic Datacube” approach allows high mass resolution visualization (0.001 Da) of mass spectrometry imaging data, but requires additional processing as compared to featurebased processing. We describe the use of distributed computing for processing of FT-ICR MS imaging datasets with generation of continuous mode Mosaic Datacubes for high mass resolution visualization. An eight-fold improvement in processing time is demonstrated using a Dutch nationally available cloud service.

Environmental Molecular Sciences Laboratory↗

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability: Supporting Data and Code

This repository contains R code and associated datasets for reproducing the analysis described in the manuscript titled “Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability” (DOI: 10.1029/2024JG008604). The provided scripts facilitate a comprehensive analysis of snow depth variability influenced by microtopography and vegetation distribution in a subarctic watershed. Included datasets are high-resolution spatial maps of snow depth, terrain elevation, vegetation height, and distance from shrubs taller than 1 meter, all formatted as text files (.txt). These data are fully describe in doi:10.15485/2316038. Users can adapt the provided R scripts to accommodate different data formats or larger spatial domains, noting that some output files may require modification due to their size.The code includes implementations for boosted regression tree analysis adapted from methods outlined in Elith et al. (2008). Users interested in understanding or modeling landscape-scale snow distribution patterns, particularly in Arctic or subarctic ecosystems, will find this package useful. 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↗

Production Operations Management System

The Production Operations Management System (POMS) is a set of software tools which allows production teams and analysis groups across multiple Fermilab experiments to launch, modify and monitor large scale campaigns of related Monte Carlo or data processing jobs. POMS provides a web service interface that enables automated jobs submission on distributed resources according to customers’ requests and subsequent monitoring and recovery of failed submissions, debugging and record keeping. POMS interfaces with existing HEP data access, processing, movement and monitoring tools at Fermilab, including Jobsub, dCache, SAM, and FIFEmon, and in combination with them handles the creation and tracking of unique filenames for multistage campaigns. A flexible, interactive GUI interface exists as part of the system to visualize campaign stages, parallelization tracks and data flow. An important feature of POMS is a one-to-one connection between the GUI campaign visualizer and a text based representation of the complete campaign configuration. An extensible library of template campaign configurations is available. The templates are user modifiable and map cleanly to and from the GUI description of the campaign. Future releases of POMS will interface with Rucio for file movement.

97 MATHEMATICS AND COMPUTING↗

Format for Interchange and Display of 3D Terrain Data

Visible Scalable Terrain (ViSTa) is a software format for production, interchange, and display of three-dimensional (3D) terrain data acquired by stereoscopic cameras of robotic vision systems. ViSTa is designed to support scalability of data, accuracy of displayed terrain images, and optimal utilization of computational resources. In a ViSTa file, an area of terrain is represented, at one or more levels of detail, by coordinates of isolated points and/or vertices of triangles derived from a texture map that, in turn, is derived from original terrain images. Unlike prior terrain-image software formats, ViSTa includes provisions to ensure accuracy of texture coordinates. Whereas many such formats are based on 2.5-dimensional terrain models and impose additional regularity constraints on data, ViSTa is based on a 3D model without regularity constraints. Whereas many prior formats require external data for specifying image-data coordinate systems, ViSTa provides for the inclusion of coordinate-system data within data files. ViSTa admits highspeed loading and display within a Java program. ViSTa is designed to minimize file sizes and maximize compressibility and to support straightforward reduction of resolution to reduce file size for Internet-based distribution.

Backes, Paul↗

Calibration Software for Use with Jurassicprok

The Jurassicprok Interferometric Calibration Software (also called "Calibration Processor" or simply "CP") estimates the calibration parameters of an airborne synthetic-aperture-radar (SAR) system, the raw measurement data of which are processed by the Jurassicprok software described in the preceding article. Calibration parameters estimated by CP include time delays, baseline offsets, phase screens, and radiometric offsets. CP examines raw radar-pulse data, single-look complex image data, and digital elevation map data. For each type of data, CP compares the actual values with values expected on the basis of ground-truth data. CP then converts the differences between the actual and expected values into updates for the calibration parameters in an interferometric calibration file (ICF) and a radiometric calibration file (RCF) for the particular SAR system. The updated ICF and RCF are used as inputs to both Jurassicprok and to the companion Motion Measurement Processor software (described in the following article) for use in generating calibrated digital elevation maps.

Chapin, Elaine↗