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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-G-BRA-12: Development of An Intra-Fractional Motion Tracking and Dose Reconstruction System for Adaptive Stereotactic Body Radiation Therapy in High-Risk Prostate Cancer

Purpose: A clinical trial on stereotactic body radiation therapy (SBRT) for high-risk prostate cancer is undergoing at our institution. In addition to escalating dose to the prostate, we have increased dose to intra-prostatic lesions. Intra-fractional prostate motion deteriorates well planned radiation dose, especially for the small intra-prostatic lesions. To solve this problem, we have developed a motion tracking and 4D dose-reconstruction system to facilitate adaptive re-planning. Methods: Patients in the clinical trial were treated with VMAT using four arcs and 10 FFF beam. KV triggered x-ray projections were taken every 3 sec during delivery to acquire 2D projections of 3D anatomy at the direction orthogonal to the therapeutic beam. Each patient had three implanted prostate markers. Our developed system first determined 2D projection locations of these markers and then 3D prostate translation and rotation via 2D/3D registration of the markers. Using delivery log files, our GPU-based Monte Carlo tool (goMC) reconstructed dose corresponding to each triggered image. The calculated 4D dose distributions were further aggregated to yield the delivered dose. Results: We first tested each module in our system. MC dose engine were commissioned to our treatment planning system with dose difference of <0.5%. For motion tracking, 1789 kV projections from 7 patients were acquired. The 2D marker location error was <1 mm. For 3D motion tracking, root mean square (RMS) errors along LR, AP, and CC directions were 0.26mm, 0.36mm, and 0.01mm respectively in simulation studies and 1.99mm, 1.37mm, and 0.22mm in phantom studies. We also tested the entire system workflow. Our system was able to reconstruct delivered dose. Conclusion: We have developed a functional intra-fractional motion tracking and 4D dose re-construction system to support our clinical trial on adaptive high-risk prostate cancer SBRT. Comprehensive evaluations have shown the capability and accuracy of our system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

L0 Data from the 2018 NGEE Arctic LiDAR and Imagery Unoccupied Aerial System Campaign at the Teller 47 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from EES-14 (Earth System Observations group) at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 47 along the Teller road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data, and DJI Phantom 4 Advanced was used to collect optical red/green/blue (RGB) imagery at regular intervals along 11 flight paths. This data package contains unprocessed data products (processing level 0) including flight paths, raw photos, and raw lidar data files (*.kml, *.jpg, and *.lpd formats). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included (see Supplemental Files, *.rinex, and *.rtcm3 files). 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field

Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. Additionally, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. Finally, the capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

SU-E-P-36: Evaluation of MLC Positioning Errors in Dynamic IMRT Treatments by Analyzing Dynalog Files

Purpose: To assess the accuracy of MLC positioning in Varian linear accelerator, in dynamic IMRT technique, from the analysis of dynalog files generated by the MLC controller. Methods: In Clinac accelerators (pre-TrueBeam technology), control system has an approximately 50ms delay (one control cycle time). Then, the system compares the measured position to the planned position corresponding to the next control cycle. As it has been confirmed by Varian technical support, this effect causes that measured positions appear in dynalogs one cycle out of phase with respect to the planned positions. Around 9000 dynalogs have been analyzed, coming from the three linear accelerators of our center (one Trilogy and two Clinac 21EX) equipped with a Millennium 120 MLC. In order to compare our results to recent publications, leaf positioning errors (RMS and 95th percentile) are calculated with and without delay effect. Dynalogs have been analyzed using a in-house Matlab software. Results: The RMS errors were 0.341, 0.339 and 0.348mm for each Linac; being the average error 0.343 mm. The 95th percentiles of the error were 0.617, 0.607 and 0.625; with an average of 0.617mm. A recent multi-institution study carried out by Kerns et al. found a mean leaf RMS error of 0.32mm and a 95th percentile error value of 0.64mm.Without delay effect, mean leaf RMS errors obtained were 0.040, 0.042 and 0.038mm for each treatment machine; being the average 0.040mm. The 95th percentile error values obtained were 0.057, 0.058 and 0.054 mm, with an average of 0.056mm. Conclusion: Results obtained for the mean leaf RMS error and the mean 95th percentile were consistent with the multi-institution study. Calculated error statistics with delay effect are significantly larger due to the speed proportional and systematic leaf offset. Consequently it is proposed to correct this effect in dynalogs analysis to determine the MLC performance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-476: Performance of the AS1200 EPID for Periodic Photon Quality Assurance

Purpose: To assess the dosimetric performance of a new amorphous silicon flat-panel electronic portal imaging device (EPID) suitable for high-intensity, flattening-filter-free delivery mode. Methods: An EPID-based QA suite was created with automation to periodically monitor photon central-axis output and two-dimensional beam profile constancy as a function of gantry angle and dose-rate. A Varian TrueBeamTM linear accelerator installed with Developer Mode was used to customize and deliver XML script routines for the QA suite using the dosimetry mode image acquisition for an aS1200 EPID. Automatic post-processing software was developed to analyze the resulting DICOM images. Results: The EPID was used to monitor photon beam output constancy (central-axis), flatness, and symmetry over a period of 10 months for four photon beam energies (6x, 15x, 6xFFF, and 10xFFF). EPID results were consistent to those measured with a standard daily QA check device. At the four cardinal gantry angles, the standard deviation of the EPID central-axis output was <0.5%. Likewise, EPID measurements were independent for the wide range of dose rates (including up to 2400 mu/min for 10xFFF) studied with a standard deviation of <0.8% relative to the nominal dose rate for each energy. Also, profile constancy and field size measurements showed good agreement with the reference acquisition of 0° gantry angle and nominal dose rate. XML script files were also tested for MU linearity and picket-fence delivery. Using Developer Mode, the test suite was delivered in <60 minutes for all 4 photon energies with 4 dose rates per energy and 5 picket-fence acquisitions. Conclusion: Dosimetry image acquisition using a new EPID was found to be accurate for standard and high-intensity photon beams over a broad range of dose rates over 10 months. Developer Mode provided an efficient platform to customize the EPID acquisitions by using custom script files which significantly reduced the time. This work was funded in part by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Laika BOSS (Binary Object Scanning System)

Laika BOSS (Binary Object Scanning System), often written as "Laikaboss", is an object scanner and intrusion detection system that strives to be scalable, flexible, and verbose. Its goal is to take arbitrary file input and extract all relevant subfiles and metadata for use in helping analysts determine the function and maliciousness of a file at a glance. This is an extension to the original code developed by Lockheed Martin.

Walkup, Gregory↗
DOE OSTI2024

Community Geothermal: Energy, Cost, and Carbon Modeling for District Design - Ann Arbor, MI

This data includes results on an analysis of existing and projected energy, cost, and carbon for the City of Ann Arbor - District Geothermal Design and Deployment to Equitably Decarbonize Low Income Neighborhoods in Ann Arbor project. The scope of the project includes designing and implementing a geothermal district heating and cooling system that reduces thermal heating and cooling load by 75% and greenhouse gas emissions by 40% in the project area (262 households, 6 commercial buildings). The existing neighborhood was modeled using Design Builder, an EnergyPlus software, to understand the current energy load. The energy model was then flipped to reflect the designed district geothermal heating and cooling system to project the effect on energy, carbon, and cost. This dataset includes the analysis files utilized and created for this study. There are 3 categories of data: 1) existing/benchmarking, 2) energy modeling, and 3) post processed calculations. This follows the methodology and process of the project team, which is fully explained in file 00_Technical Economic Environmental Assessment. All uses of data are referenced throughout this assessment to their respective files included below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Epidemiologic Study of One Million U.S. Radiation Workers and Veterans

The single most important question in radiation epidemiology is determining the level of health risks associated with radiation exposures that occur gradually over time. The study of one million early U.S. radiation workers and veterans has been designed to provide information on risk following chronic exposures by focusing on occupational groups with differing radiation exposure patterns, including intakes of radionuclides. The cost-efficient study builds on the investments made and foundations laid by investigators and government agencies over the past 30-40 years, which have established early worker cohorts that can now provide answers to questions on the lifetime human health risks associated with low-level radiation exposures. Within the overall goal of the epidemiologic study of one million U.S. radiation workers and veterans, this project had a total of nine specific aims which included studies of six populations for multiple endpoints including cancer overall mortality, leukemia and non-cancer mortality. The six populations included: Mound, Ohio, workers exposed to polonium, tritium and plutonium; nuclear power plant workers within the Landauer dosimetry and Nuclear Regulatory Commission data files; industrial radiographers; Mallinckrodt uranium workers; uranium workers who linked with the US Renal Data System; and nuclear weapons test participants. Over 400,000 workers and atomic veterans are included in these populations, with vital status being determined and analyses of all causes of death undertaken. A critical, integral component of the studies has been comprehensive evaluations of dosimetry involving, in many cases, complex dose reconstructions, and assessments of uncertainties. The work has also involved development of state-of-the art statistical approaches and modeling. All nine aims were accomplished successfully, resulting in publication of two NCRP documents, 13 literature papers, numerous Boice Reports in Health Physics News and many presentations of the work at scientific meetings. Furthermore, recommendations have been developed for an approach to integrate epidemiologic observations with radiation biology for risk assessment and biological models of radiation effect. The results of this project, as well as ongoing epidemiology studies of US radiation workers and veterans, are providing much-needed insights into complex issues regarding cancer and non-cancer health risks from low dose irradiation, how to apply a "dose and dose rate effectiveness factor" to scale the risks from the A-bomb survivor data to current occupational and environmental circumstances, and how to evaluate risk following intakes of radioactive substances. In addition to application to radiation workers, the results of the studies can provide guidance as society debates the role of nuclear energy and deals with nuclear waste, threats of terrorist attacks with nuclear/radiological devices, the remarkable increase in medical exposures to CT scans and nuclear imaging, and to NASA as radiation protection for astronauts on long-duration mission beyond low-Earth orbit is planned.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

The Vineyard Wind Power Purchase Agreement: Insights for Estimating Costs of U.S. Offshore Wind Projects

This report analyzes the power purchase agreements (PPAs) between Massachusetts electric distribution utilities (EDC) and Vineyard Wind LLC filed on July 31, 2018, and derives insights for estimating cost of U.S. offshore wind systems and broader cost modeling activities. The documented price for delivery of offshore wind generation and renewable energy certificates under the Vineyard Wind/electric distribution utilities PPA is 74 $/megawatt-hour (MWh) (2022$) for facility 1 (400 MW) and 65 $/MWh (2023$) for facility 2 (400 MW). However, this PPA price does not comprise the complete set of expected revenue sources and tax benefits available to the Vineyard Wind LLC project. A comprehensive accounting of expected revenue sources inclusive of those that are exogenous to the reported PPA is conducted in this study to estimate the project's levelized revenue of energy (LROE). This allows for a more equivalent comparison of the PPA pricing with bottom-up modeled (unsubsidized) levelized cost of energy (LCOE) estimates. LROE from the Vineyard LLC/EDC PPA is estimated to be 98$/MWh (2018$). This LROE estimate for the first commercial-scale offshore wind project in the United States appears to be within the range of LROE estimated for offshore wind projects recently tendered in Northern Europe with a start of commercial operation by the early 2020s. This suggests that a cost and risk premium for the initial set of U.S. offshore wind projects may be less pronounced than anticipated by many industry observers and analysts.

17 WIND ENERGY↗
DOE OSTI2021

Data and Insights for the KRUSTY Nuclear-Powered Tests

This document, and the associated files, describe all of the data from the KRUSTY warm criticals and the KRUSTY nuclear system test. The warm criticals were a group of tests where fission power heated the core and the feedback response was studied. There were 3 experiments, the 15-cent run (which was a true “free run”), followed by 30-cent and 60-cent runs, where reactivity was added to heat the core to higher temperatures. The nuclear system test (often referred to as the full-run or the final-run), engaged the power conversion system and evaluated system performance. These experiments are described in a pair of NUCLEAR TECHNOLOGY papers, which includes plots of the data that this document-set includes. Note that a lot of information in this document is based on my interpretation and could be wrong, but I’ve included it to potentially save some people a lot of time and headaches by trying to figure out which instrumentation to believe, but beware treating anything I say as fact. I’ve also included several post-irradiation photos, to show some thermocouple locations and indicate possible changes in emissivity and/or geometry (although no changes in geometry were indicated).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

SPRUCE Deep Peat Heat (DPH) Metagenomes for Peat Samples Collected June 2015

This data set provides links to the results of metagenomic analyses of 38 peat core samples collected on 16 June 2015 from SPRUCE experiment treatment plots after approximately one year of belowground heating. These metagenomes are archived in the U.S. Department of Energy Joint Genome Institute (DOE JGI) Integrated Microbial Genomes (IMG) system and are available at the accession numbers provided below and in the accompanying inventory file. This work was done in collaboration with the DOE Joint Genome Institute (JGI) study that is targeting understanding the microbial metagenomes of “fungal, bacterial, and archaeal communities mediating C cycling and trace gas flux in peatland ecosystems subject to climate change” (Proposal ID: 1445). The SPRUCE experiment site is an ombrotrophic bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

2D reactive transport model of shale chemical weathering and biogeochemical fluxes along a mountainous hillslope, East River Watershed, Colorado: Input files and simulation results

This data package contains input files and simulation results for a two-dimensional (2D) reactive transport model used to quantitatively analyze the coupled hydrological and biogeochemical processes governing shale weathering and associated biogeochemical fluxes under realistic environmental conditions in the high-elevation East River Watershed. These data support the conclusions presented in Stolze et al. (Water Resources Research, under review), "Model-based interpretation of solute exports and carbon partitioning during shale weathering in a mountainous hillslope". The model simulates atmospheric-subsurface gas exchange, subsurface water flow, and shale weathering processes under dynamic, year-scale conditions along a shale-underlain hillslope located in the East River watershed. The simulations were performed using the PFLOTRAN flow and reactive transport code and executed on the Perlmutter supercomputer to leverage its large-scale parallel computing capabilities. The data package contains two zipped folders, "model_input_files" and "simulation_results", and one readme.txt file. "model_input_files" contains the necessary input files to run the calibrated base-base model presented in Stolze et al. (Water Resources Research, under review). "simulation_results" contains a single hdf5 file ("Output_2D_hillslope_model.h5") which includes the results of simulation performed using the base-case model. This file can be opened with HDFView 3.1.4, Python, or MATLAB. "readme.txt" contains relevant information about the base-case model and provides guidelines on how to run the associated input files provided in the folder "model_input_files". Furthermore, readme.txt provides information regarding the model results provided in "Output_2D_hillslope_model.h5" such as matrix dimensionality and output units. Field datasets used to evaluate model performance were collected at three monitoring wells located along a hillslope transect (PLM1, PLM2, and PLM3). Dissolved ion concentration data were collected from November 2016 to October 2021 for Ca, Mg, DIC, Na, K, SO4 (Dong et al., 2025 - dic_npoc_data_2014_2024.zip - DOI:10.15485/1660459; Williams et al., 2025 - anion_data_2014_2024.zip - DOI:10.15485/1668054; Dong et al., 2025 - cation_data_2014_2024.zip - DOI:10.15485/1668055). Note that we used the files named er_PLM1_xx_yy, er_PLM2_xx_yy, and er_PLM3_xx_yy where xx stands for the name of the aqueous species and yy stands for the depth where the measurements were performed. Soil water content ([0 - 1] m) and water table depth were collected from November 2016 to October 2021 (Wan et al., 2024 - Dynamic_water_table__depthsFig2b.csv and Soil_water_content_Fig4e.csv - DOI:10.15485/2322567). Gaseous CO2 concentration were collected from October 2020 to December 2021(Wan et al., 2024 - Soil_CO2_concentrations_Fig4h.csv - DOI:10.15485/2322567) Gaseous CO2 flux from the subsurface to the atmosphere were collected in the vicinity of PLM2 from October 2019 to May 2022 (Wu et al., 2025). Soil microbial biomass concentration was measured from August 2016 to June 2017 (Sorensen et al., 2019 - 2017_East_River_Pumphouse_Microbial_Biomass__1_.csv - DOI:10.15485/1577267) All field data are published as CSV files compatible with Microsoft Excel, MATLAB, and Python, or as text files. The coordinates of the monitoring wells and the CO2(g) flux sensor in the coordinate system WGS84 are: -PLM1: [38.9197710 ; -106.9492750] -PLM2: [38.9201580 ; -106.9487170] -PLM3: [38.9207843 ; -106.9483668] -PLM4: 38.9210060 ; -106.9479528] -CO2(g) flux sensor: [38.9199180 ; -106.9489906] ------------------------------------------------------------------------------------------- This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy User Facility using NERSC award BER-ERCAP 23980, BER-ERCAP 28550, and BER-ERCAP 33789.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Non-growing Season Plant Nutrient Uptake Controls Arctic Tundra Vegetation Composition: Modeling Archive

This Modeling Archive is in support of a NGEE-Arctic publication: Riley et al. (2021) “Non-growing season plant nutrient uptake controls Arctic tundra vegetation composition under future climate” (Riley et al., 2021). The dataset contains “ecosys” model outputs reported in Riley et al. (2021) that examines the role of non-growing season (NGS) nutrient dynamics on 21st century vegetation composition. The study highlighted the importance of these nutrient dynamics on the emergent plant functional type distributions, focusing on their role in shrub expansion. The study showed that ignoring NGS nutrient dynamics led to a dramatic under-prediction of shrub expansion by year 2100, motivating the need to include these processes in Earth System Models. Included are modeled net primary production (NPP) and nitrogen (N) uptake for two scenarios: (1) baseline and (2) no NGS N uptake. The output is provided (1) at 25 km resolution across the North American tundra; (2) for years 2012 through 2100; and (3) PFT-specific. Dataset contains 20 NetCDF files in a zip file and one pdf.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↗
DOE OSTI2024

UAS remote sensing (Autel EVO II platform): Red-green-blue (RGB) imagery and derived products (Level 0-2 data), Seward Peninsula, Alaska, 2023

Airborne remote sensing data collected using a optical red-green-blue (RGB) sensor installed on an Autel EVO II unoccupied aerial system (UAS). This package includes data from 4 flights flown over the NGEE-Arctic Council Mile Marker (MM) 71 and Teller MM27 sites on the Seward Peninsula, Alaska USA, in July 2023. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors, and Level 1-2 processed products including digital surface models (DSM), photo orthomosaics, canopy height models (CHM) and digital terrain models (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as image (*.jpg, *.tif), point cloud (*.laz), tabular (*.csv) and *.pdf formats. Raw images are compressed as tar.gz. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the data and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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↗
DOE OSTI2024

UAS remote sensing (Autel EVO II platform): Red-green-blue (RGB) imagery and derived products (Level 0-2 data), Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using a optical red-green-blue (RGB) sensor installed on an Autel EVO II unoccupied aerial system (UAS). This package includes data from 15 flights flown over the NGEE-Arctic Council Mile Marker (MM) 71, Kougarok MM64, and Teller MM27 sites on the Seward Peninsula, Alaska USA, in July 2022. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors, and Level 1-2 processed products including digital surface models (DSM), photo orthomosaics, canopy height models (CHM) and digital terrain models (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as image (*.jpg, *.tif), point cloud (*.laz), tabular (*.csv) and *.pdf formats. Raw images are compressed as tar.gz. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the data and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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↗
DOE OSTI2024

Machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado and New Mexico

Temporally continuous snow depth estimates are vital for understanding changing snow patterns in the Arctic and impacts on permafrost. We trained random forest machine learning models to predict snow depth from temperature data recorded at or just below the ground surface. Training data was collected at the Teller 27 Watershed and Kougarok 64 Hillslope during the 2021 - 2022 water year on the Seward Peninsula, Alaska using distributed temperature profiling (DTP) systems. We then applied this model to other sites where ground surface or shallow soil temperature data was available for at least one water year (see Related Datasets). Many of these temperature measurements were collocated with snow depth observations. Ground surface temperature (i.e. snow-ground interface temperature) is easy to measure using small, cheap and easy-to-deploy temperature sensors such as iButtons and TinyTags, and such measurements have previously been used to calculate a variety of snow metrics (e.g. snow onset date). However, this is the first study to estimate snow depth directly from ground surface temperature data. The present dataset contains one *.csv file which includes machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado, and New Mexico and one *.kml file including the locations of sites with snow depth predictions. No training data predictions are included in the *.csv file. 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↗
DOE OSTI2023

Mission-driven design methodology for optical systems

Disclosed are devices, systems and methods for a mission-driven design framework for optical systems. An exemplary method for improving the design of an optical system includes receive a first plurality of parameters indicative of performance requirements of the optical system, receive a second plurality of parameters representative of characteristics of one or more components in the optical system, generate a mathematical representation that combines the first plurality of parameters and the second plurality of parameters, perform a sensitivity analysis to obtain a ranking of parameters from the first plurality of parameters and the second plurality of parameters, select, based on the ranking of the parameters, at least one parameter that produces a largest change in the mathematical representation, and produce a constraint file comprising the at least one parameter for ingestion by a design tool to enable the design of the optical system.

Higbee, Shawn D.↗
DOE OSTI2025

LiDAR Point Cloud Data from the 2018 NGEE Arctic UAS Campaign at the Teller 47 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory’s (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from the EES-14 group at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 47 along the Teller Road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDAR System was used to collect LiDAR data. The LiDAR data has undergone basic post-processing using Routescene LidarViewer Pro software to create point cloud data (.laz files). This data package contains point clouds (.laz), processing metadata files (json.lvp), and post-processed kinematic files (.csv). Ancillary aircraft data, flight mission parameters, weather conditions, and lidar data and imagery can be found in NGA281 (https://doi.org/10.5440/1671794).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).

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