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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Stormtime Particle Energization with AMIE Potentials

Simulations were conducted to investigate the influence of rapid electric field fluctuations on electron energization in the inner magnetosphere based on the assimilative mapping of ionospheric electrodynamics (AMIE) technique. Simulations for four different magnetic storms were run, namely those that occurred on May 15,1997, May 4, 1998, September 25, 1998, and October 19, 1998. Here, we have examined the formation of high energy electrons in the inner magnetosphere during these storm events with our recently-developed relativistic radiation belt transport code. The point of this numerical experiment is to show that a simulation of a real event must have the high time resolution electric field input files in order to produce the seed population for the radiation belts, which are often observed to increase in the days following a magnetic storm. Specifically, a cadence of the global electric field pattern of 5 minutes or less produces inner magnetospheric fluxes that are larger (by up to 5 orders of magnitude) than fluxes produced with a longer cadence. Differences were particularly large relative to simulation results with a 3-hour time cadence, analogous to a Kp-driven electric field model.

Khazanov, George V.↗
DOE OSTI2023

Soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie.

Uploaded raw datasets from electrical resistivity tomography (ERT), ground penetrating radar (GPR), electromagnetic induction (EMI) and insitu sensors were acquired across land-lake interfaces along Lake Erie. These datasets were useful to delineate the soil architecture and subsurface stratigraphic heterogeneities. We combined multiple geophysical methods with lithostratigraphic logs from borehole cores and data from soil and borehole sensors to investigate spatial heterogeneities across land-lake interfaces. The apparent electrical conductivity (Eca) maps matched closely with the soil maps from public database and also detected additional soil units that were missing in the traditional soil maps. This implies that electromagnetic induction (EMI) could be relied upon for non invasive characterization of soils in sampling restricted sites where only non-invasive measurements are feasible. Results from electrical resistivity tomography (ERT) and Ground penetrating radar (GPR) are consistent with the surficial geology of the study area, and revealed that the vertical variabilities at the sites are mainly driven by stratigraphy.The ERT data (.stg) were acquired from three different sites portage river (PTR), crane creek (CRC) and old woman creek (OWC). The ".stg" files can be opened with ERT inversion software such as EarthImager, ResIpy or Res2DInv. The GPR data (.GPZ) were also acquired from the three sites, and the ".GPZ" data files can be opened with EKKO_project 5 software from Sensors & Software Inc., or with any other standard GPR software. The EM data (.csv) were acquired from the three sites while the soil sensor data (.csv) here were acquired only from crane creek site. The ".csv) files can be opened with MS Excel or any other spread sheet software.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

BOREAS Level-3a Landsat TM Imagery: Scaled At-sensor Radiance in BSQ Format

For BOREAS, the level-3a Landsat TM data, along with the other remotely sensed images, were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy, detailed land cover, and biophysical parameter maps such as FPAR and LAI. Although very similar in content to the level-3s Landsat TM products, the level-3a images were created to provide users with a more usable BSQ format and to provide information that permitted direct determination of per-pixel latitude and longitude coordinates. Geographically, the level-3a images cover the BOREAS NSA and SSA. Temporally, the images cover the period of 22-Jun-1984 to 30-Jul-1996. The images are available in binary, image-format files. With permission from CCRS and RSI, several of the full-resolution images are included on the BOREAS CD-ROM series. Due to copyright issues, the images not included on the CD-ROM may not be publicly available. See Sections 15 and 16 for information about how to acquire the data. Information about the images not on the CD-ROMs is provided in an inventory listing on the CD-ROMs.

Nickerson, Jaime↗
DOE OSTI2019

Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive

This dataset contains results from two GIPL runs for RCP4.5 and RCP8.5 across the Seward Peninsula. The model was run on 500 m by 500 m resolution for the period 1901-2100. Meteo variables include forcing air temperature and precipitation as well as modeled maxim and average snow height. This dataset also includes ground temperature at 10 different depths for every grid cell, active layer depth and talik thickness. Auxillary variables include ecotype map and projected latitude and longitude. Ground temperature borehole data that is used for model calibration and validation of GIPL2 for Seward Peninsula 500 m resolution model runs for 1901-2100 time period. Dataset also includes calibrated model parameters for future use. The main purpose of this dataset is the reproducibility of research. Data were produced for regional permafrost distribution assessment for present and future, in addition, model parameters can be used for future model runs on adjacent territories. This dataset contains *.pdf, *.txt, *.csv, and *.nc. files. 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↗
NASA NTRS2000

BOREAS RSS-14 Level -3 Gridded Radiometer and Satellite Surface Radiation Images

The BOREAS RSS-14 team collected and processed GOES-7 and -8 images of the BOREAS region as part of its effort to characterize the incoming, reflected, and emitted radiation at regional scales. This data set contains surface radiation parameters, such as net radiation and net solar radiation, that have been interpolated from GOES-7 images and AMS data onto the standard BOREAS mapping grid at a resolution of 5 km N-S and E-W. While some parameters are taken directly from the AMS data set, others have been corrected according to calibrations carried out during IFC-2 in 1994. The corrected values as well as the uncorrected values are included. For example, two values of net radiation are provided: an uncorrected value (Rn), and a value that has been corrected according to the calibrations (Rn-COR). The data are provided in binary image format data files. Some of the data files on the BOREAS CD-ROMs have been compressed using the Gzip program. See section 8.2 for details. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2004

Stormtime Particle Energization with High Temporal Resolution AMIE Potentials

Simulations were conducted to investigate the influence of rapid electric field fluctuations on electron energization in the inner magnetosphere based on the assimilative mapping of ionospheric electrodynamics (AMIE) technique. Simulations for four different magnetic storms were run, namely those that occurred on 15 May 1997, 4 May 1998, 25 September 1998, and 19 October 1998. Here we have examined the formation of high- energy (100-500 keV) electrons in the inner magnetosphere during these storm events with our recently developed relativistic radiation belt transport code. The point of this numerical experiment is to show that a simulation of a real event must have the high time resolution electric field input files in order to produce the seed population for the radiation belts, which are often observed to increase in the days following a magnetic storm. Specifically, a cadence of the global electric field pattern of 5 min or less produces inner magnetospheric fluxes that are larger (by up to several orders of magnitude) than fluxes produced with a longer cadence. Differences were particularly large relative to simulation results with a 3-hour time cadence, analogous to a Kpdriven electric field model.

Khazanov, George V.↗
NASA NTRS2004

Stormtime Particle Energization with High Temporal Resolution AMIE Potentials

Simulations were conducted to investigate the influence of rapid electric field fluctuations on electron energization in the inner magnetosphere based on the assimilative mapping of ionospheric electrodynamics (AMIE) technique. Simulations for four different magnetic storms were run, namely those that occurred on May 15, 1997, May 4, 1998, September 25, 1998, and October 19, 1998. Here, we have examined the formation of high energy (10-1000 keV) electrons in the inner magnetosphere during these storm events with our recently-developed relativistic radiation belt transport code. The point of this numerical experiment is to show that a simulation of a real event must have the high time resolution electric field input files in order to produce the seed population for the radiation belts, which are often observed to increase in the days following a magnetic storm. Specifically, a cadence of the global electric field pattern of 5 minutes or less produces inner magnetospheric fluxes that are larger (by up to several orders of magnitude) than fluxes produced with a longer cadence. Differences were particularly large relative to simulation results with a 3-hour time cadence, analogous to a Kp-driven electric field model.

Khazanov, George V.↗
NASA NTRS2016

Multidisciplinary Model Transformation Through Simplified Intermediate Representations

There has long been a challenge of making engineering tools from multiple disciplines interoperate. This problem extends to system modeling practices. This challenge has been confronted with a wide variety of techniques. These techniques include attempting to interface tools together into combined suites, attempting to find underlying commonalities in mathematics, supporting connections through semantic encoding, various graph mappings and transformations, and code wrappers. All of these approaches have strengths and weaknesses. These are measured in multiple areas: relative freedom of action of individual domain engineers in developing their own tools, speed of execution, ease of creation, traceability, fidelity of information transfer, and degree of alignment between the concepts of different domains. This paper presents an approach to this interoperation problem currently being used in the World-Wide Web. The approach is to develop easy-to-parse formats that allow flexibility to both the file author and file interpreter. Many of the formats that are currently deployed sacrifice runtime performance for the ability of third parties to easily understand what to do with the data. XML became popular earlier as a de-facto standard format for many web applications, but is now being replaced by JSON to enhance human readability and provide a simpler data model. This is the basis for work in this paper. Our approach, which provides the key to interoperation, is a simplified “shrapnel” intermediate collection of objects and relationships that is the result of a breakdown of the system model into minimal pieces. It is then reassembled on the destination side, forming a two-step transformation. Previous efforts with single-step transformations have proven too difficult to create efficiently. In contrast, the use of this approach leads to an almost automatic procedure for transformation development. The Europa project is a large engineering project that must coordinate the efforts of many different teams with different specialties. The traditional form of exchanging engineering information has been documentation. The vision of model-based systems engineering is to make this information exchange much more digital. This paper presents the application of our simplified format to connecting two different engineering tools to the system model, with a focus on a dynamic mission simulation encoded in Modelica.

Cole, Bjorn↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗
NASA NTRS2000

BOREAS Level-3s Landsat TM Imagery Scaled At-sensor Radiance in LGSOWG Format

For BOReal Ecosystem-Atmosphere Study (BOREAS),the level-3s Landsat Thematic Mapper (TM) data, along with the other remotely sensed images,were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy,detailed land cover, and biophysical parameter maps such as Fraction of Photosynthetically Active Radiation (FPAR) and Leaf area Index (LAI). CCRS collected and supplied the level-3s images to BOREAS for use in the remote sensing research activities. Geographically,the bulk of the level-3s images cover the BOREAS Northern Study Area (NSA) and Southern Study Area (SSA) with a few images covering the area between the NSA and SSA. Temporally,the images cover the period of 22-Jun-1984 to 30-Jul-1996. The images are available in binary,image-format files.

Nickeson, Jaime↗
DOE OSTI2017

Mapping of orthogonal 2D flux coordinates for two nearby magnetic X-points to logically rectangular domains

The behavior of plasmas in configurations with magnetic null points is of potential interest for a number of systems. Such nulls, sometimes referred to as X-points, a name strictly valid only for wellseparated nulls where magnetic separatrices cross at a right angle, may occur in only one component of the magnetic field, such as the poloidal field in a tokamak. Numerical simulations are often used to study and predict turbulence and transport in such systems. For cases with strong magnetic field such that the ion and electron gyro-frequencies are much larger that particle collision frequencies, there is a strong anisotropy in the plasma transport along the magnetic field compared to across the field. Because of the strong anisotropy, it is often advantageous for simulations to use a coordinate system based on magnetic flux surfaces together with a coordinate orthogonal to the flux surfaces. This report presents the topological considerations needed to construct the mapping on an orthogonal flux-surface mesh onto a logically rectangular domain often used in simulation codes of the divertor region of tokamaks having two nearby X-points, thus extending the mapping now common single-null or well-separated double nullpoint cases with one null located at the top and bottom of the device. This extension is especially relevant to study the capability of snowflake divertors in tokamaks for reducing the peak heat flux of exhaust plasma on the target plates [1-3]. The analysis presented here follows the analytic description of the poloidal magnetic field, B pol , near two closely-spaced X-points given by Ryutov [1-3]. This analysis is applicable to experimental devices where the two X-points are generated by distributed poloidal field coils and the plasma core current. This analytic description is used to identify topological features of an orthogonal mesh. A key parameter that specifies the various topology changes is the poloidal angle between the primary X-point and the second X-point, and the changes are associated with a set of critical angles. Understanding these changes leads to the final step in the mesh construction by identifying the locations of various regions or patches in configuration space and in a corresponding logically rectangular index space. UEDGE [4] and other 2-D fluid plasma simulation codes [5-7] describe the edge plasma of toroidally symmetric tokamak configurations with one or more X-points in a divertor region. The 2-D spatial mesh is usually based on a magnetic configuration produced by an MHD equilibrium code such as EFIT and written out as one or more “eqdsk” files. As illustrated in Fig. 1, the domain of the simulated plasma consists of several flux tubes bounded by poloidal magnetic flux surfaces. The number and spacing of the flux surfaces defines the “radial” resolution of the mesh. The “radial” direction is locally orthogonal to flux surfaces; the “poloidal” direction is locally parallel to flux surfaces. The “poloidal” resolution of the mesh is defined by the number of cells in the poloidal direction between adjacent flux surfaces. For boundary plasma transport codes used for tokamak configurations such as UEDGE it is convenient, though not necessary, to assume that all flux tubes have the same number of poloidal cells so the mesh is logically rectangular in index space, but does possess internal boundaries linking different sub-rectangles in the computational domain. The following sections of this report describe indexing schemes that map tokamak magnetic configurations with one or more x-points in the divertor region(s) onto a rectangular index space. Simulation results from the UEDGE code illustrate the schemes for a few configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Patient-Specific Quality Assurance for the Delivery of {sup 60}Co Intensity Modulated Radiation Therapy Subject to a 0.35-T Lateral Magnetic Field

Purpose: This work describes a patient-specific dosimetry quality assurance (QA) program for intensity modulated radiation therapy (IMRT) using ViewRay, the first commercial magnetic resonance imaging-guided RT device. Methods and Materials: The program consisted of: (1) a 1-dimensional multipoint ionization chamber measurement using a customized 15-cm{sup 3} cube-shaped phantom; (2) 2-dimensional (2D) radiographic film measurement using a 30- × 30- × 20-cm{sup 3} phantom with multiple inserted ionization chambers; (3) quasi-3D diode array (ArcCHECK) measurement with a centrally inserted ionization chamber; (4) 2D fluence verification using machine delivery log files; and (5) 3D Monte Carlo (MC) dose reconstruction with machine delivery files and phantom CT. Results: Ionization chamber measurements agreed well with treatment planning system (TPS)-computed doses in all phantom geometries where the mean ± SD difference was 0.0% ± 1.3% (n=102; range, −3.0%-2.9%). Film measurements also showed excellent agreement with the TPS-computed 2D dose distributions where the mean passing rate using 3% relative/3 mm gamma criteria was 94.6% ± 3.4% (n=30; range, 87.4%-100%). For ArcCHECK measurements, the mean ± SD passing rate using 3% relative/3 mm gamma criteria was 98.9% ± 1.1% (n=34; range, 95.8%-100%). 2D fluence maps with a resolution of 1 × 1 mm{sup 2} showed 100% passing rates for all plan deliveries (n=34). The MC reconstructed doses to the phantom agreed well with planned 3D doses where the mean passing rate using 3% absolute/3 mm gamma criteria was 99.0% ± 1.0% (n=18; range, 97.0%-100%), demonstrating the feasibility of evaluating the QA results in the patient geometry. Conclusions: We developed a dosimetry program for ViewRay's patient-specific IMRT QA. The methodology will be useful for other ViewRay users. The QA results presented here can assist the RT community to establish appropriate tolerance and action limits for ViewRay's IMRT QA.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Patterns and controls on island-wide aboveground biomass accumulation in second-growth forests of Puerto Rico

This dataset includes two products from Martinuzzi et al. (2022): "biomass.tif" is a 26-m resolution forest biomass (AGB) map for Puerto Rico derived from NASA G-LiHT lidar data and forest inventory data (FIA plots), in raster format. "input_multivariate_v2.shp" is a point shapefile with information on forest age, substrate, past land use, topographic wetness, slope, and precipitation, for each forest pixel. These two datasets can be used to evaluate spatial patterns of AGB in second-growth forests across transects of lidar data in humid forests of Puerto Rico, and to analyze relationship(s) between AGB and environmental variables. Additional information on these products can be found on the supporting file called "Readme.txt" included within the data archive, as well as in the original manuscript by Martinuzzi et al (2022).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Procedure Parsing: A Method for Parsing Handwritten Documents into Computer-Based Procedures

The nuclear industry is heavily procedure driven, where almost everything has a step-by-step instruction that is expected to be followed in detail. Historically, these procedures were printed on paper copies. Recently, the industry transitioned towards electronic copies (i.e., PDFs on tablets). One major drive for this transition is the introduction of human error and loss of situation awareness when using paper copies. However, electronic copies of documents inherently have the same error traps as their paper cousins. Therefore, there is an increased interest in a way to utilize the information in the step-by-step guidance, but to present it in a dynamic manner that guides the user and adapts to any encountered conditions. Researchers at Idaho National Laboratory propose a flexible, automated method based on document parsing and augmented by natural language processing (NLP) techniques, to address these shortcomings and capitalize on these recent advancements in machine learning. The proposed method provides a cost-effective solution for computer-assisted procedure parsing of hand-written control room procedures, originally authored in Word or PDF formats, into instructions that can be displayed as computer-based procedures (CBP) in a modern graphical user interface. The researchers devised, implemented and demonstrated the Operating Procedure Extender for Novel Systems (OPENS) method in 2020. The key to OPENS is to map the original procedure text into a context-free grammar, tying content to equipment, locations, and other steps, actions, etc. This formal grammar is then used to isolate and define keywords and actions verbs, such as “measure” or “evaluate” and tie them to specific equipment referenced within that step or located in other steps, substeps, actions, subactions and tables throughout the procedure. OPENS generates an abstract syntax tree from the document which it uses to store a copy of this information in the open-standard, machine-readable and human-readable file formats XML and JSON. The XML is useful to preserve the relational aspects of the procedure for referencing tables and branching information so the user can be directed to the next appropriate active step based on the values entered for that step and previous steps. The JSON is useful for storing and exchanging data objects used to track responses to previous steps and state changes in simulated environments. In future iterations, these formats can also be used for storing more detailed information about input during plant operation or simulation. The techniques the researcher developed could further be improved by integration of recent advancements in machine learning. NLP methods could standardize documents, correct for grammatical error, and provide automated semantic validation. The researcher expects that self-supervised techniques applied to collections of natural language instructions could strengthen the model with broader context. All these methods together give us a practical way to automatically extract protocols from documents and user interactions, empowering researchers, procedure writers and nuclear operators while moving the industry forward.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2009

Architectural Analysis of Complex Evolving Systems of Systems

The goal of this collaborative project between FC-MD, APL, and GSFC and supported by NASA IV&V Software Assurance Research Program (SARP), was to develop a tool, Dynamic SAVE, or Dyn-SAVE for short, for analyzing architectures of systems of systems. The project team was comprised of the principal investigator (PI) from FC-MD and four other FC-MD scientists (part time) and several FC-MD students (full time), as well as, two APL software architects (part time), and one NASA POC (part time). The PI and FC-MD scientists together with APL architects were responsible for requirements analysis, and for applying and evaluating the Dyn-SAVE tool and method. The PI and a group of FC-MD scientists were responsible for improving the method and conducting outreach activities, while another group of FC-MD scientists were responsible for development and improvement of the tool. Oversight and reporting was conducted by the PI and NASA POC. The project team produced many results including several prototypes of the Dyn-SAVE tool and method, several case studies documenting how the tool and method was applied to APL s software systems, and several published papers in highly respected conferences and journals. Dyn-SAVE as developed and enhanced throughout this research period, is a software tool intended for software developers and architects, software integration testers, and persons who need to analyze software systems from the point of view of how it communicates with other systems. Using the tool, the user specifies the planned communication behavior of the system modeled as a sequence diagram. The user then captures and imports the actual communication behavior of the system, which is then converted and visualized as a sequence diagram by Dyn-SAVE. After mapping the planned to the actual and specifying parameter and timing constraints, Dyn-SAVE detects and highlights deviations between the planned and the actual behavior. Requirements based on the need to analyze two inter-system communication protocols that are representative of protocols used in the Aerospace industry have been specified. The protocols are related: APL s Common Ground System (CGS) as used in the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) and the Radiation Belt Space Probes (RBSP) missions. The analyzed communications were implementations of the Telemetry protocol and the CCSDS File Delivery Protocol (CFDP) protocol. Based on these requirements, three prototypes of Dyn-SAVE were developed and applied to these protocols. The application of Dyn-SAVE to these protocols resulted in the detection of several issues. Dyn-SAVE was also applied to several Testbeds that have previously been used for experimentation earlier on this project, as well as, to other protocols and logs for testing its broader applicability. For example, Dyn-SAVE was used to analyze 1) the communication pattern between a web browser and a web server, 2) the system log of a computer in order to detect offnominal computer shut-down behavior, and 3) the actual test cases of NASA Goddard s Core Flight System (CFS) and automatically generated test cases in order to determine the overlap between the two sets of test cases. In all cases, Dyn-SAVE assisted in providing insightful conclusions about each of the cases identified above.

Lindvall, Mikael↗
NASA NTRS2019

Space Communications and Navigation Validation: Extracting Data for the Strategic Center for Networking, Integration, and Communications Scheduling Algorithms

Efficiency in communication system architecture performance between Space Communications and Navigation (SCaN) assets and missions is crucial, as space communication is varied, complex, and often not utilized to its full potential. The SCaN Strategic Center for Networking, Integration, and Communications (SCENIC) new scheduling algorithms, which are designed to simulate the allocation of resources between SCaN assets and missions, have the potential to simulate an increase of this efficiency; however, they require real-world data to be validated against. The purpose of this project was to extract said validation data, which details the frequency and duration of utilized contact windows between missions and assets in the Near Earth Network (NEN), Space Network (SN), and Deep Space Network (DSN). Stored as images in daily operations summaries (DOSs), the tabular data existed in a variety of file formats such as.pdf, .docx, and .doc. Since the tables were stored as images, ABBYY® FineReader® (ABBYY Software Ltd.) optical character recognition (OCR) was implemented, which is a proprietary software that reads images from text. The comma separated value (CSV) output was utilized as input to a series of MATLAB® (The MathWorks, Inc.) methods for reformatting, at which point it was ready to be machine-read. Finally, the results were converted to a Microsoft Excel format for human readability. Along with being used for validation purposes, the data will also be used to map equipment degradation as a function of time to analyze the reliability of network assets.

Kontur, Noah P.↗
DOE OSTI2024

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗
DOE OSTI2024

Data from "A Bayesian Record Linkage Approach to Applications in Tree Demography Using Overlapping LiDAR Scans"

Processed LiDAR data and environmental covariates from 2015 and 2019 LiDAR scans in the Vicinity of Snodgrass Mountain (Western Colorado, USA), in a geographic subset used in primary analysis for the research paper.This package contains LiDAR-derived canopy height maps for 2015 and 2019, crown polygons derived from the height maps using a segmentation algorithm, and environmental covariates supporting the model of forest growth. Source datasets include August 2015 and August 2019 discrete-return LiDAR point clouds collected by Quantum Geospatial for terrain mapping purposes on behalf of the Colorado Hazard Mapping Program and the Colorado Water Conservation Board. Both datasets adhere to the USGS QL2 quality standard. The point cloud data were processed using the R package lidR to generate a canopy height model representing maximum vegetation height above the ground surface, using a pit-free algorithm.This dataset was compiled to assess how spatial patterns of tree growth in montane and subalpine forests are influenced by water and energy availability. Understanding these growth patterns can provide insight into forest dynamics in the Southern Rocky Mountains under changing climatic conditions.This dataset contains .tif, .csv, and .txt files. This dataset additionally 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.

54 ENVIRONMENTAL SCIENCES↗