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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

PNNL-Predictive-Phenomics/ProteoMeter

ProteoMeter is a Python package that assists in the statistical analysis of global proteomics, protein post-translation modification (PTM), and limited proteolysis (LiP) data. It contains batch correction, normalization, and statistical testing methods, as well as functions that "roll up" peptide-level data to the single-site level. It has a robust user configuration system, allowing it to flexibly integrate different types of experiment designs. For basic usage, a simple configuration file provides the essential functionality. Advanced users have access to the entire statistical pipeline for fine-tuning analyses. Processed data is easily exported to many common spreadsheet and data-frame formats.

Rozum, Jordan [Pacific Northwest National Lab]↗
DOE OSTI2022

April 2020 Darshan counters from the Summit supercomputer

This dataset is the Darshan counters collected from the Summit supercomputer in a month of April 2020. 1. Description of methods used for collection/generation of data: Job submitted on Summit HPC system when completed successfully and has made I/O calls (captured by Darshan tool) writes a Darshan log file on alpine filesystem. One job can have multiple `jsrun` commands and Darshan will generate separate logs each log corresponding to an `jsrun` command, so a job can have one or more Darshan logs associated with it. 2. Methods for processing the data: To process the data, we first use `darshan-util` tool to parse the Darshan logs. Then we restructure the logs and merge data from multiple Darshan logs if they belong to the same Summit job.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Emergent Nanostructure and Ion Transport in Polyzwitterion/Polyanion Blends

We investigated blends of poly(1-(3-sulfonatopropyl)-2-vinylpyridinium) (P2VPPS) and poly(lithium (trifluoromethane)sulfonimide methacrylate) (poly(MTFSI)Li) at varying molar ratios to gain a mechanistic understanding of ionic conductivity in a miscible polyzwitterion/polyanion system. This dataset contains the raw numerical data corresponding to the figures in the manuscript. The data files include the following information: (1) Experimental Data – includes X-ray and neutron scattering measurements, broadband dielectric spectroscopy (BDS) data, extracted DC conductivity values, differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) results, extracted glass transition temperatures, etc. (2) CGMD Data – includes molecular dynamics (MD) trajectory files and computed structural correlations. All data files are organized/named according to the figure numbers in the manuscript.

36 MATERIALS SCIENCE↗
DOE OSTI2018

SPRUCE Deep Peat Heating (DPH) to Whole Ecosystem Warming (WEW) Metagenomes for Peat Samples Collected June 2016

This data set provides links to the results of metagenomic analyses of 44 peat samples collected on 13 June 2016 from SPRUCE experiment treatment and ambient plots. Experimental plots had received approximately 24 months of belowground warming (deep peat heating (DPH), Hanson et al. 2015) with the last 9 of those months including air warming for implementation of whole ecosystems warming (WEW – Hanson et al. 2016). The SPRUCE experiment site is located in an ombrotrophic bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). WEW Metagenomes: Data from 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 (Table 2) and in the accompanying inventory file. The easiest way to find results on IMG is at this link, https://img.jgi.doe.gov/cgi-bin/m/main.cgi, and then enter “June2016WEW” as a search term in the “Quick Genome Search:” box at the top of the page. This work was done in collaboration between ORNL, USFS and 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

System and method for generating a relationship network

A computer-implemented system and process for generating a relationship network is disclosed. The system provides a set of data items to be related and generates variable length data vectors to represent the relationships between the terms within each data item. The system can be used to generate a relationship network for documents, images, or any other type of file. This relationship network can then be queried to discover the relationships between terms within the set of data items.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Distributed Computing for the Project 8 Experiment

The Project 8 collaboration aims to measure the absolute neutrino mass or improve on the current limit by measuring the tritium beta decay electron spectrum. We present the current distributed computing model for the Project 8 experiment. Project 8 is in its second phase of data taking with a near continuous data rate of 1Gbps. The current computing model uses DIRAC (Distributed Infrastructure with Remote Agent Control) for its workflow and data management. A detailed meta-data assignment using the DIRAC File Catalog is used to automate raw data transfers and subsequent stages of data processing. The DIRAC system is deployed on containers managed using a Kubernetes cluster to provide a scalable infrastructure. A modified DIRAC Site Director provides the ability to submit jobs using Singularity on opportunistic High-Performance Computing (HPC) sites.

Distributed Computing, Kubernetes, DIRAC, Project ↗
DOE OSTI2024

Analysis of NCERC Critical Experiments with ENDF/B Nuclear Data Libraries

Nuclear data (ND) libraries are the backbone of the nuclear industry, as they are the collections of tabulated probabilities that define sub-atomic particle interactions with matter. In the areas of criticality safety and experiments, no evaluated nuclear data files (ENDF) are more important than those containing neutron cross section data. It is upon these files, and accompanying radiation transport codes, that practitioners are enabled to safely design both subcritical and critical systems. Likewise, in a symbiotic fashion, it is the same critical assemblies which are used primarily to validate that the cross sections are correct. The ENDF/B library, the United States’ national library maintained by the National Nuclear Data Center (NNDC) at Brookhaven National Laboratory (BNL), is soon releasing a new version, ENDF/B-VIII.1. Prior to the official release, several beta versions of the library were prepared and tested in simulation suites. The work presented here are results comparing the newest ENDF/B beta release (ENDF/B-VIII.1b3) and ENDF/B-VIII.0 with recent experiments done at the National Criticality Experiments Research Center (NCERC) as well as correlated experiments from the Los Alamos Critical Experiments Facility (LACEF). These NCERC and LACEF experiments were performed in part to provide validation for various cross sections that were identified as insufficient in the ENDF/B-VIII.0. In particular, lead, copper, fluorine, and chlorine, as well as the major actinides, were targeted from the last decade of critical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The Global DAS Month of February 2023

During February 2023, a total of 32 individual distributed acoustic sensing (DAS) systems acted jointly as a global seismic monitoring network. The aim of this Global DAS Month campaign was to coordinate a diverse network of organizations, instruments, and file formats to gain knowledge and move toward the next generation of earthquake monitoring networks. During this campaign, 156 earthquakes of magnitude 5 or larger were reported by the U.S. Geological Survey and contributors shared data for 60 min after each event’s origin time. Participating systems represent a variety of manufacturers, a range of recording parameters, and varying cable emplacement settings (e.g., shallow burial, borehole, subaqueous, and dark fiber). Monitored cable lengths vary between 152 and 120,129 m, with channel spacing between 1 and 49 m. The data has a total size of 6.8 TB, and are available for free download. Finally, organizing and executing the Global DAS Month has produced a unique dataset for further exploration and highlighted areas of further development for the seismological community to address.

58 GEOSCIENCES↗
DOE OSTI2024

Surface elevation, snow depth, vegetation height, and color imagery from multiple UAV surveys from 2018 to 2023 across a watershed near Teller road mile marker 27, Seward Peninsula, Alaska

Multiple photogrammetric surveys using an unoccupied aerial system (UAS) were performed across a watershed along Teller road on the Seward Peninsula (Alaska) to investigate terrain, vegetation and snowpack properties. This work was led by the environmental geophysics team from Lawrence Berkeley National Laboratory as part of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). The multiple photogrammetric surveys used mostly a DJI Matrice 210 UAS with a DJI X5S camera, Ground Control Points (GCPs) surveyed with a Real Time Kinematic (RTK)-GPS, and a structure from motion (SfM) technique for photogrammetric reconstruction. Digital Surface elevation Models (DSMs) were inferred at various times of year, including near peak in plant and leaf density (July 19 2017), close to peak in snow depth (April 1 2019 and April 11 2022), and at low plant and leaf density of tall after the first bare-ground date (June 9 2019). Snow and canopy height were obtained by subtracting DSMs from a Digital Terrain Model (DTM) proxy inferred from the June 9 2019 survey. The derived products include ortho-mosaiced RGB map, DSMs, a DTM proxy, snow depth (April 2019 and 2022) and canopy height (July 2017). Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.csv), image (*.jpg), and GeoTiff (*.tif) formats. This metadata document contains a description of the survey and processing steps and the inferred products.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 OSTI2013

RELAP5-3D Restart and Backup Verification Testing

Existing testing methodology for RELAP5-3D employs a set of test cases collected over two decades to test a variety of code features and run on a Linux or Windows platform. However, this set has numerous deficiencies in terms of code coverage, detail of comparison, running time, and testing fidelity of RELAP5-3D restart and backup capabilities. The test suite covers less than three quarters of the lines of code in the relap directory and just over half those in the environmental library. Even in terms of code features, many are not covered. Moreover, the test set runs many problems long past the point necessary to test the relevant features. It requires standard problems to run to completion. This is unnecessary for features can be tested in a short-running problem. For example, many trips and controls can be tested in the first few time steps, as can a number of fluid flow options. The testing system is also inaccurate. For the past decade, the diffem script has been the primary tool for checking that printouts from two different RELAP5-3D executables agree. This tool compares two output files to verify that all characters are the same except for those relating to date, time and a few other excluded items. The variable values printed on the output file are accurate to no more than eight decimal places. Therefore, calculations with errors in decimal places beyond those printed remain undetected. Finally, fidelity of restart is not tested except in the PVM sub-suite and backup is not specifically tested at all. When a restart is made from any midway point of the base-case transient, the restart must produce the same values. When a backup condition occurs, the code repeats advancements with the same time step. A perfect backup can be tested by forcing RELAP5 to perform a backup by falsely setting a backup condition flag at a user-specified-time. Comparison of the calculations of that run and those produced by the same input w/o the spurious condition should be identical. Backup testing is more difficult the other kinds of testing described above because it requires additional coding to implement. The testing system constructed and described in this document resolves all of these issues. A matrix of test features and short-running cases that exercise them is presented. A small information file that contains sufficient data to verify calculations to the last decimal place and bit is produced. This testing system is used to test base cases (called null testing) as well as restart and backup cases. The programming that implements these new capabilities is presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive

This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
DOE OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Arctagrostis latifolia Biomass and Chemistry, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of measured tissue specific biomass, %C, % N and APE (atom percentage in excess) of 15N of harvested A. latifolia in vegetation warming experiment enclosures and paired control plots located on the BEO, Utqiagvik, Alaska. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. This dataset includes one csv file and one pdf 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 OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Arctagrostis latifolia Canopy Traits, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of measured Arctagrostis latifolia canopy traits harvested from vegetation warming experiment enclosures and paired control plots located on the BEO, Utqiavik, Alaska. Harvest types include both natural abundance and enriched A. latifolia. Canopy traits measured include leaf area index (LAI), specific leaf area (SLA) and maximum height. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiavik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. This dataset includes one csv file and one pdf 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 OSTI2022

Forced Diffusion Chamber Monitoring of Soil CO2 Fluxes from 2019 to Present at NGEE Arctic Teller Site, Mile Marker 27, Alaska

Soil CO2 efflux was monitored at the NGEE Arctic Teller Site, Mile Marker 27, in Alaska. Monitoring was performed beginning in June 2019 using EOSense forced diffusion soil CO2 flux sensors at up to six sites characterized by varying vegetation cover, topographic position, and soil temperature and moisture. Dataset includes measurements of soil CO2 flux and chamber temperature. Time interval between measurements ranges from 5 minutes to 3 hours. Included are EOSense chamber locations as *.kml and *.png files, six *.csv files with measurements, and two *.csv reporting format 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↗
DOE OSTI2016

SU-F-T-156: Monte Carlo Simulation Using TOPAS for Synchrotron Based Proton Discrete Spot Scanning System

Purpose: This study provides an overview of the design and commissioning of the Monte Carlo (MC) model of the spot-scanning proton therapy nozzle and its implementation for the patient plan simulation. Methods: The Hitachi PROBEAT V scanning nozzle was simulated based on vendor specifications using the TOPAS extension of Geant4 code. FLUKA MC simulation was also utilized to provide supporting data for the main simulation. Validation of the MC model was performed using vendor provided data and measurements collected during acceptance/commissioning of the proton therapy machine. Actual patient plans using CT based treatment geometry were simulated and compared to the dose distributions produced by the treatment planning system (Varian Eclipse 13.6), and patient quality assurance measurements. In-house MATLAB scripts are used for converting DICOM data into TOPAS input files. Results: Comparison analysis of integrated depth doses (IDDs), therapeutic ranges (R90), and spot shape/sizes at different distances from the isocenter, indicate good agreement between MC and measurements. R90 agreement is within 0.15 mm across all energy tunes. IDDs and spot shapes/sizes differences are within statistical error of simulation (less than 1.5%). The MC simulated data, validated with physical measurements, were used for the commissioning of the treatment planning system. Patient geometry simulations were conducted based on the Eclipse produced DICOM plans. Conclusion: The treatment nozzle and standard option beam model were implemented in the TOPAS framework to simulate a highly conformal discrete spot-scanning proton beam system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Full spectrum (350-2500 nm) canopy spectral reflectance, Seward Peninsula, Alaska, 2018

Full-range (350-2500 nm) canopy reflectance spectra of various Arctic tundra ecosystem endmembers, including canopy-scale species endmember spectra, plot-scale spectra, and transect spectra as well as non-vegetated surface (NVS) spectra. The datasets were collected at the three core NGEE-Arctic watersheds, Kougarok, Teller, and Council, as well as the supplemental Kougarok Mile 80 site within the larger Seward Peninsula, Alaska region. The data were collected in July 2018 using a full-range Spectra Vista Corporation (SVC) HR-1024i spectroradiometer. Canopy-scale reflectance was collected with an 8-degree field-of-view (FOV) foreoptic lens. All spectral measurements were collected as calibrated surface radiance and converted to surface reflectance using a 99.99% reflective Spectralon white reference standard. For those canopy spectra collected with associated functional trait data, the FOV of the instrument was positioned to include the same leaves harvested for functional trait measurements, including leaf mass per area (LMA) and foliar carbon and nitrogen content (see associated dataset). Species included in the spectra and functional trait dataset include Alnus viridis, Betula nana, Betula glandulosa, Arctous alpina, and Salix pulchra. This data package includes 35 files in a variety of formats including processed canopy spectra (*.csv), processed dGPS locations (*.csv and *.kmz), digital photographs of spectral targets (*.jpg) and raw data from spectroradiometer and dGPS instruments (compressed as tar.gz). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA208_flmd.csv.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 OSTI2025

Rucio at LSST/Rubin

In this presentation, we will explore the Rucio experience with the Rubin Observatory experiment. Our discussion will cover several key areas: Scalability Tests: Insights into the performance and scalability evaluations of Rucio in the context of Rubin's data needs and what we have learned, especially with many small files. Role in Rubin's Data Curation: Rubin's Data Butler: An overview of how Rucio, along with with Rubin's Data Butler using Hermes-K, which involves message passing through Kafka, is integrated in the Rubin's data curation system. Monitoring and Support: Current status of Rucio and PostgreSQL monitoring and Rucio deployment and support within the Rubin environment. Tape RSE Implementation: Deal with the order of magnitude more files going to tape than HEP. Future Needs: An examination of Rubin's evolving requirements for Rucio services and how we plan to address them.

Lee, Dennis [Fermilab]↗