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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 757 records · Page 42

bifacialVF - Bifacial PV View Factor model 2022 [SWR 17-58]

bifacialvf is a self-contained view factor (or configuration factor) model which replicates a 5-row PV system of infinite extent perpendicular to the module rows. Single-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row. Bilinear interpolation code add-on to bifacialvf (description below) to pre-generate IV arrays and bifacial coefficients, and to examine the energy production with back side irradiance mismatch for either a portrait or landscape module. Included are IV curves and bifacial info for a Yingli (standard) module. Based on the publication: "A Practical Irradiance Model for Bifacial PV Modules" B. Marion, S. MacAlpine, C. Deline, A. Asgharzadeh, F. Toor, D. Riley, J. Stein, C. Hansen 2017 IEEE Photovoltaic Specialists Conference, Washington DC, 2017 URL: https://www.nrel.gov/docs/fy17osti/67847.pdf

Deline, Chris↗

Geophysical borehole logging data of wells ER-GLS1, ER-GUM1, ER-PLM7, and ER-PLM8 at the East River Watershed, Colorado

The purpose of this data set is to provide a means of characterizing the bedrock variability both within a single borehole location and across the East River Watershed. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States, and all boreholes are located within Mancos shale bedrock. The data set contains geophysical borehole logging data acquired in October 2018 in boreholes ER-GUM1 (East River- Gothic Upper Montane Borehole #1) and ER-GLS1 (East River- Gothic Lower Subalpine Borehole #1), and acquired in October 2019 in boreholes ER-PLM7 (East River- Pumphouse Lower Montane Borehole #7) and ER-PLM8 (East River- Pumphouse Lower Montane Borehole #8). It contains depth, natural gamma ray emission, spectral gamma ray emission(Th, K, U), magnetic susceptibility, fluid temperature and electrical conductivity, electromagnetic (EM) induction derived rock electrical resistivity, heat pulse and spinner flow measurements to estimate groundwater flow, and Nuclear Magnetic Resonance (NMR) derived water content and hydraulic conductivity. Data for each borehole are provided as comma delimited text files. For each borehole accurate location information is provided (based on RTK GPS (Real Time Kinematic Global Positioning System) surveying). Borehole logging data were acquired using Mount Sopris borehole tools, and Vista Clara Javelin for NMR data.

54 ENVIRONMENTAL SCIENCES↗

Data from: "Soil moisture mediates alpine life form and community productivity responses to warming"

This dataset contains values that were used to support conclusions drawn in the publication “Soil moisture mediates alpine life form and community productivity responses to warming”, originally published in 2016 by Winkler et al. All data were collected in the alpine site of the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, in the Front Range of the Colorado Rocky Mountains, USA. The file types in this archive include comma-separated-values (.csv) files, and two types of geospatial files: .kml and shapefiles (.shp). The csv files can be opened by R, Microsoft Excel, or any simple text editor software. The geospatial files can be opened by Google Earth/Google Maps, and the ESRI shapefiles can be opened by geographic information systems softwares that can read shapefiles, including ESRI’s ArcGIS Desktop suite, and QGIS.Climate warming is expected to alter primary production and community composition in alpine systems around the globe. Whether production will increase in response to warming in the absence of additional precipitation remains underexplored. We experimentally warmed an alpine plant community on Niwot Ridge, Colorado to test whether warming increases or decreases productivity of multiple plant life form groups and the entire plant community. We also provided supplemental water to a subset of plots to alleviate potential drying effects of warming. We predicted alpine community above-ground productivity would increase in response to warming only when combined with supplemental water to limit soil drying. We also predicted plant life form groups would vary in their responses and would like buffer changes in community productivity.

54 ENVIRONMENTAL SCIENCES↗

WHONDRS Summer 2019 Sampling Campaign: Global River Corridor Sediment FTICR-MS, Dissolved Organic Carbon, Aerobic Respiration, Elemental Composition, Grain Size, Total Nitrogen and Organic Carbon Content, Bacterial Abundance, and Stable Isotopes (v10)

The WHONDRS Summer 2019 Sampling (S19S) Campaign collected samples in 97 globally distributed river corridor systems between July and September 2019. Surficial streambed sediments were collected at three locations within each site (upstream, midstream, and downstream). Surface water was collected at the downstream site. This dataset includes a portion of the data types produced from the sediment samples and does not include any results from the surface water. Surface water data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1603775. The S19S campaign was designed with the science community to ask questions associated with links among core/transient metabolomes, microbial metabolism, biogeochemical function, and physical properties of watershed and river corridor systems. This data package was originally published in December 2020. It was updated in April 2021 (v2; modified files), May 2022 (v3; new and modified files), November 2022 (v4; new and modified files), January 2023 (v5 and v6; new and modified files), February 2023 (v7; new and modified files), August 2023 (v8; new and modified files), July 2025 (v9; new and modified files), and June 2026 (v10; new and modified files). Version 10 includes major restructuring of the files and their formats. See the change history in the readme for details. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset contains (1) readme, (2) data dictionary, (3) file level metadata, (4) sampling protocol, (5) a data checks report, (6) field metadata, (7) international generic sample number (IGSN) mapping file, (8) joint genome institute (JGI) mapping file, (9) a folder of site photos, and (10) a folder of sample data. The sample data folder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and FTICR methods; (2) respiration rates and normalized respiration rates calculated from laboratory sediment incubations, (3) X-ray fluorescence (XRF) elemental composition, (4) grain size distribution from the < 2 millimeter fraction of sediment, (5) total organic carbon and total nitrogen content, (6) bacterial abundance flow cytometry data, (7) sediment stable isotopes (C and N), (8) laboratory methods, (9) water and sediment mass and volume used in incubations, (10) a folder with code, inputs, and plots for the respiration rates, (11) a folder containing XRF data, (12) a folder containing unaligned, peak-picked high resolution characterization of dissolved organic matter from sediment via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory), (12) and a folder containing processed FTICR-MS data. All files are .msa, .txt, .spx, .xml, .csv, .pdf, .txt, .jpg, or .jpeg.

13C↗

Using NJOY to Create MCNP ACE Files and Visualize Nuclear Data

We provide lecture materials that describe the input requirements to create various MCNP ACE files (Fast, Thermal, Dosimetry, Photo-nuclear and Photo-atomic) with the NJOY Nuclear Data Processing code system. Input instructions to visualize nuclear data with NJOY are also provided.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Detailed Wind Turbine Blade Cost Model

This technical report describes a detailed blade cost model for wind turbine blades in the range of 30 to 100 meters in length. The model estimates the bill of materials, the number of labor hours and the cycle time, and the costs related to direct labor, overhead, buildings, tooling, equipment, maintenance, and capital. The model applies to multimegawatt wind turbine blades manufactured via vacuum-assisted resin transfer molding, which is the most commonly adopted manufacturing method for modern wind turbine blades. The model is implemented both in a large Excel file and in Python. The latter is freely available in the repository of the Wind-Plant Integrated System Design and Engineering Model (WISDEM[R]) github.com/WISDEM. WISDEM is a multidisciplinary analysis and optimization design framework developed at the National Renewable Energy Laboratory. This blade cost model represents a valuable tool to run design optimization studies for wind turbines. In this report, the model is first presented with its approach and assumptions and then computes the costs of three blades, namely the 33-meter-long Wind Partnership for Advanced Component Technologies (WindPACT) study blade, the 63-meter-long International Energy Agency (IEA) Wind Task 37 land-based reference wind turbine blade, and the 100-meter-long SNL-100-03 blade developed at Sandia National Laboratories.

17 WIND ENERGY↗

Sandbox for Mac Malware v 1.0

This software is an analyzer for automated sandbox analysis of malware on the OS X operating system. It runs inside an OS X virtual machine to collect data about what happens when a given file is opened or run. As of August 2014, there was no sandbox software for Mac OS X malware, as it requires different methods from those used on the Windows OS (which most sandboxes are written for). This software adds OS X analysis capabilities to an existing open-source sandbox, Cuckoo Sandbox (http://cuckoosandbox.org/), which previously only worked for Windows. The analyzer itself can take many different types of files as input: the traditional Mach-O and FAT executables, .app files, zip files, Python scripts, Java archives, and web pages, as well as PDFs and other documents. While the file is running, the analyzer also simulates rudimentary human interaction with clicks and mouse movements in order to bypass the tests some malware use to see if they are being analyzed. The analyzer outputs several different kinds of data: function call traces, network captures, screenshots, and all created and modified files. This work also includes a static analysis Cuckoo module for Mach-O binary files. It extracts file structures, code library imports and exports, and signatures. This data can be used along with the analyzer results to create signatures for malware.

Walkup, Elizabeth↗

Correlated Synthetic Time Series Generation using Fourier and ARMA

As the contribution of renewable energy grows in electricity markets, the complexity nuclear’s place within the energy mix increases, and likewise the need for robust simulation techniques. While decades of wind, solar, and demand pro- files can sometimes be obtained, this is too few samples to provide a statistically meaningful analysis of a system with baseload, peaker, and renewable generation. Synthetic time series generation presents itself as a suitable methodology to meet this need. One approach for synthetic series generation is training a model using Fourier series decomposition for seasonal patterns and Auto-Regressive Moving Average models (ARMA) to describe time-correlated statistical noise about the seasonal patterns. When combined, the Fourier plus ARMA (FARMA) model has been shown to provide an infinite set of independent, identically-distributed sample time series with the same statistical properties as the original data [1]. When considering an energy mix with renewable electricity production, several time series of energy, grid, and weather measurements are needed for each synthetic year modeled to statistically comprehend the efficiency of any given energy mix. These cannot be considered independent series in a given synthetic year. To capture and reproduce the correlations that might exist in the measured histories, the ARMA can further be extended as a Vector ARMA (VARMA). In the VARMA algorithm, covariance in statistical noise is captured both within a history as part of the autoregressive moving average, and with respect to the other variables in the time series. In this work the implementation of the Fourier VARMA in the RAVEN uncertainty quantification and risk analysis software framework [2] is presented, along with examples of correlated synthetic history generation.

97 MATHEMATICS AND COMPUTING↗

Organic layer thickness and carbon concentration in burned and unburned sites, Seward Peninsula, AK, 2022

Measurements associated with organic layer samples collected from naturally burned (1971, 2002, 2015, 2019) and unburned sites at the Kougarok Fire Complex, Seward Peninsula, AK, 2022. Here, a discontinuous permafrost underlies an arctic tundra ecosystem. Measurements include elemental carbon and nitrogen concentrations and stocks, organic layer thickness, and thaw depth. There are five files in *.csv format with one data file and four data description files including data dictionary, methods, terminology, and file-level metadata. 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↗

Verification Testing of OLI Systems Mixed Solvent Electrolyte Model for the Na-K-Mg-Ca-H-Cl-SO 4 -OH-HCO 3 -CO 3 -CO 2 -H 2 ) System to High Ionic Strength at 25°C

This technical report summarizes model verification results and summary statistics for 41 evaporite mineral solubility cases evaluated by Savannah River National Laboratory using OLI Systems’ aqueous electrolyte thermodynamic modeling software. The 41 verification cases containing a total of 60 solubility curves comprise mineral solubility data from low to high ionic strength at 25°C for the eight-component system Na-K-Mg-Ca-H-Cl-SO 4 -OH-HCO 3 -CO 3 -CO 2 -H 2 O as reported by Harvie et al. (1984). Thermodynamic calculations were executed using OLI Systems’ Stream Analyzer computation module within the OLI Studio software platform (Ver. 11.0, Rev. 11.0.1.9). The Mixed Solvent Electrolyte (MSE) thermodynamic framework was chosen for this investigation because of its superiority in modeling high ionic-strength inorganic salt solutions and actinide redox chemistry and solubility, both of which are relevant to the geological repository conditions at the Waste Isolation Pilot Plant in Carlsbad, New Mexico. Mineral solubility data in various inorganic salt solutions were digitized and extracted from figures generated by Harvie et al. (1984). For each of the 60 solubility curves, a case-specific chemistry model and input file were generated in OLI Studio using OLI Stream Analyzer and the MSE (H 3 O + ion) public databank provided by OLI Systems. Model simulation results were exported to Microsoft Excel to calculate summary statistics and to generate graphs comparing the OLI model predictions to the solubility data. Summary statistics include residuals (model – data) and concordance (accuracy × precision, where precision is indicated by the Pearson correlation coefficient and accuracy accounts for bias and scale differential). Private databanks were not developed, and activity coefficient model regressions were not performed to improve OLI model fits to the data. Of the 41 model verification plots, 83% have a mean of the percent residuals less than or equal to 25%. Similarly, 75% display a concordance greater than or equal to 0.75. Only seven of the 41 verification plots fail to show good agreement between the model and data. Of these seven, three are relevant to the WIPP repository because they involve the Mg-OH-Cl-SO 4 -CO 3 aqueous system. The remaining four address salt solubilities at the pH extremes (strong acid and strong base). It should be noted that in two of the three Mg-OH-Cl-SO 4 -CO 3 system cases, the regressed Harvie et al. (1984) solubility curve also deviated from the data. Lack of agreement between the OLI model-predicted solubility curves and the data is attributable to one or more of the following: specific solid species are not included in the OLI MSE databank; there is significant variation among the different solubility datasets chosen by Harvie et al. (1984); the OLI MSE model’s thermodynamic parameters were determined using different solubility datasets; and the activity coefficient parameters for certain relevant ion-ion and ion-molecule pairs have not been optimized via data regression. Two recommendations for future work are to (1) evaluate solubility data for the Mg-OH-Cl-SO 4 -CO 3 system at high ionic strength and, if necessary, develop a private OLI MSE database that includes missing species and, where necessary, regressed standard state properties and interaction parameters; (2) perform similar verification testing of the OLI model for actinide solubility data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Model files for estimating snow dynamics and stable water isotopes across the East River, CO.

A coupled hydrologic and snowpack stable water isotope model is used to assesses controls on isotopic inputs across the East River, Colorado, a large, mountainous basin. The hydrologic model uses the semi-empirical, spatially distributed and publicly available U.S. Geological Survey numerical code Precipitation-Modelling Runoff System (PRMS). Water and energy are tracked daily through the atmosphere, canopy and subsurface at a 100-m grid resolution. The isotope mass balance model follows previous work by Ala-aho et al. (2017) to track stable isotopes entering the soil system as snowmelt or rain. Water stores and fluxes needed for the isotope model use hydrologic model output for each timestep and model modeled grid location. This data package provides all files related to the hydrologic model (executable, input and output files), the isotopic model calibration and the historic isotopic model (water years 2015-2020). The isotope model source code and executable are provided. The file "readme.txt" includes information on the file structure, steps to run the model, and description of included folders.

54 ENVIRONMENTAL SCIENCES↗

ORNL_AISD_NiPt

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for three different sizes of the crystal structure: 256 atoms, 864 atoms, and 2,048 atoms, each of which contains 1900 configurations. For each size of the crystal structure, the data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in three compressed zipped folders: atoms256.zip, atoms864.zip, atoms2048.zip Each zipped folder contains the data that describes crystals of size 256 atoms, 864 atoms, and 2,048 atoms respectively. Each one of the three zipped folders contains the data structured in the following way: -Ni_ground_state.cfg --> atomic configuration for the pure nickel -Pt_ground_state.cfg --> atomic configuration for the pure platinum -Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder. Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms256.zip is 65,046. The total number of atomic configurations contained in atoms864.zip is 63,936. The total number of atomic configurations contained in atoms2048.zip is 61,997. The total number of atomic configurations spanned by the entire dataset is 190,979. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büccchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D

36 MATERIALS SCIENCE↗

SU-F-T-469: A Clinically Observed Discrepancy Between Image-Based and Log- Based MLC Position

Purpose: To present a clinical case which challenges the base assumption of log-file based QA, by showing that the actual position of a MLC leaf can suddenly deviate from its programmed and logged position by >1 mm as observed with real-time imaging. Methods: An EPID-based exit-fluence dosimetry system designed to prevent gross delivery errors was used in cine mode to capture portal images during treatment. Visual monitoring identified an anomalous MLC leaf pair gap not otherwise detected by the automatic position verification. The position of the erred leaf was measured on EPID images and log files were analyzed for the treatment in question, the prior day’s treatment, and for daily MLC test patterns acquired on those treatment days. Additional standard test patterns were used to quantify the leaf position. Results: Whereas the log file reported no difference between planned and recorded positions, image-based measurements showed the leaf to be 1.3±0.1 mm medial from the planned position. This offset was confirmed with the test pattern irradiations. Conclusion: It has been clinically observed that log-file derived leaf positions can differ from their actual positions by >1 mm, and therefore cannot be considered to be the actual leaf positions. This cautions the use of log-based methods for MLC or patient quality assurance without independent confirmation of log integrity. Frequent verification of MLC positions through independent means is a necessary precondition to trusting log file records. Intra-treatment EPID imaging provides a method to capture departures from MLC planned positions. Work was supported in part by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

Foam Fracturing Fluid Half-life Experimental Data

Foam thermal stability was studies at Temple University in collaboration with Oak Ridge National Lab (ORNL). The goal of this project is to explore thermally stable foams as hydrofracking fluid media for potential applications in enhanced geothermal system (EGS). Data generated from this project will allow researchers to explore foam as potential fracturing fluid. More than 800 data points on the half-life of foams are recorded in Excel files in the included archive resource (Half-life of Foams with Different Surfactants and Stabilizing Agents). The Excel file within each surfactant folder contains half-life data of the respective surfactant with different stabilizing agents, pressure, and temperature. The respective folders also contains Word files describing the details of the data included in the respective Excel sheet.

15 GEOTHERMAL ENERGY↗

Energy Exascale Earth System Model v2.0.2

Second patch release of v2.0.0 Changes since v2.0.1 [Important change] Add and update SSP370 and SSP585 cases, add tests, fix use-case files, Change ocean and sea-ice IC for ARRM60to10. [EAM] allow thetaxx as a CAM_TARGET, enable northamericax4v1pg2_WC14to60E2r3 for AMIP, fix ndrop initialization, allow up to 15 history files. [EAMxx] allow use of readnl [EAM-MMF] allow transient SST case for C++ MMF, remove specific task/thread count for ESMT test, modify the variance transport diagnostic, reorg tests, [HOMME] Allow optional sponge layer. [ELM] add 2 land-atm compsets, update FATES to API 17.0.0, allow FATES sp mode, allow ELM harvest to drive FATES harvest, fix memleaks, reduce test build times, modified parameters for miscanthus and switchgrass based on calibration [MPAS-Ocean] turn on ocean BGC in BGC cases, fix interface locations for 60L PHC grid, add mode spec to conservation check streams, allow oRRS18to6v3 grid to run with JRA, update ocean and sea ice ICs for ARRM60to10 (needed for v2), GPU port of thickness tendency, add CMPASO-JRA1p4, [MPAS framework] Add new reproducible global sum module for MPAS components, Add mostRecentAccessTime attribute to streams [MPAS-landice] Update MALI version and Greenland mesh [MPAS-seaice] add single-cell test case, fix BGC restart, Adds omp critical directives for ice warnings seen on cori. [CIME] Fix component namelist creation bugs when NINST>1, add OpenACC, OpenMP and CXX GPU tests, fix nonBFB tests, stop using config_compilers, reduce ELM test build times with shared executable, update OpenMPI on Chrysalis. fix baseline handling, provenance handling with update to cime6.0.33, also use component-specific config_pes files and add the ones from master [Machine updates] cori modules after maint, Chrysalis to OpenMPI-4.1.3 [run_e3sm] replace default case name and group. [Externals] update SCORPIO to 1.3.2

ECP↗

In Situ Soil Moisture and Thaw Depth Measurements Coincident with Airborne SAR Data Collections, Seward Peninsula, Alaska, 2022

The in-situ soil moisture and thaw depth measurements provided in this dataset were collected coincident with airborne overflights of L-band synthetic aperture radar (SAR) instruments at the Teller, Kougarok, and Council study sites on the Seward Peninsula, Alaska. Overflights occurred on August 19, 2022. Soil moisture data at Teller and Kougarok was collected on August 19, and at Council on August 20. Thaw depth, soil pits, and any additional measurements were recorded on August 20 and 21. Field measurements and flights were conducted during the summer of 2022 as a collaboration between the National Aeronautics and Space Administration (NASA) Arctic-Boreal Vulnerability Experiment (ABoVE) Project’s Airborne SAR Campaign and the Next-Generation Ecosystem Experiments (NGEE) Arctic Project. This dataset includes a data file (*.csv), a data dictionary (*_dd.csv) and a file-level metadata (*_flmd.csv). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), 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).

EARTH SCIENCE > LAND SURFACE > FROZEN GROUND↗

Data and Scripts Associated with "Modeling Ecohydrological Responses of Vegetation to Urban Microclimates Using the E3SM Land Model"

This dataset supports the study of vegetation ecohydrological responses to urban microclimates using the land component of the Energy Exascale Earth System Model (ELM) at four urban sites in Knoxville, Tennessee, USA. It includes the model inputs, simulation outputs, and associated scripts for running ELM simulations and analyzing the resulting data. The Model_Inputs folder includes static surface data, satellite-derived phenology (i.e., leaf area index), and atmospheric forcing data used to drive ELM simulations. Detailed descriptions of these datasets are provided in Section 2.3.2 of the associated manuscript. The Model_Outputs folder contains simulation results for the baseline, treatment, and ensemble experiments. Outputs from the baseline and treatment simulations are provided as raw ELM NetCDF files. Because the raw outputs from the 4,000-member ensemble are prohibitively large, the ensemble results are provided as summarized CSV files, which also serve as the source data for Figure 5 of the associated manuscript. The Scripts folder contains three components: E3SM, the core codebase of the Energy Exascale Earth System Model (E3SM); elm-olmt, the Offline Land Model Testbed (OLMT) used to perform the simulations; and knoxville_elm, which contains the analysis scripts used to process model outputs and generate the figures and results presented in the associated manuscript. Additional information is provided in Scripts_readme.txt within the Scripts directory.

Lu, Xiaoman [ORNL] (ORCID:0000000306698780)↗

A GPU-based Approach for Path Planning Optimization via Travel Length Reduction

Typically, before constructing an object with an additive manufacturing system, the 3D object must be sent through a process called slicing. Slicing converts a 3D object commonly in the form of an STL file into a set of layers by horizontally intersecting a plane with the object at various heights. At each height, called a layer, multiple 2D polygons can be generated. Each polygon represents a boundary for solid geometry and is called an island. Each island is then comprised of multiple path types in an attempt to optimally fill the polygon. To move between each island and each islands’ paths, travels are inserted. Travels are simply motion by the system to move from one area of construction to another. Travels do not contribute to the construction of the object, and so, are considered wasted motion. In large-scale additive manufacturing, objects can be quite large and the distance between islands can be large as well. As a result, these travels can waste a significant amount of time. Ideally, travels would be as short as possible, however, computing global minimal travel paths is computationally expensive. To combat this problem, researchers at Oak Ridge National Lab developed a GPU-based approach to travel insertion based on a unique factoradic representation. This representation was then utilized by the GPU to solve the Traveling Salesman Problem (TSP). This algorithm was able to compute global minimal travel paths quickly resulting in faster object construction. A general investigation was also carried out to determine when a GPU vs CPU implementation would be beneficial.

Borish, Michael↗