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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Globus service enhancements for exascale applications and facilities

Many extreme-scale applications require the movement of large quantities of data to, from, and among leadership computing facilities, as well as other scientific facilities and the home institutions of facility users. These applications, particularly when leadership computing facilities are involved, can touch upon edge cases (e.g., terabyte files) that had not been a focus of previous Globus optimization work, which had emphasized rather the movement of many smaller (megabyte to gigabyte) files. We report here on how automated client-driven chunking can be used to accelerate both the movement of large files and the integrity checking operations that have proven to be essential for large data transfers. In conclusion, we present detailed performance studies that provide insights into the benefits of these modifications in a range of file transfer scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Experimental Setup of Apodization Techniques for Beam Diagnostics Performed at ELBE

The ELBE (Electron Linac for beams with high Brilliance and low Emittance) facility in Dresden, Germany is a multipurpose user facility, which is also used for accelerator R&D purposes. The beam line was set up for transverse beam profile measurements, where the imaging system includes a series of three apodizers and five circular apertures. During beam operations both of these were changed remotely through automated LabView routines. The bunch structure and charge were varied to collect a series of images that were acquired automatically, and then stored for later analysis. Over 12,000 images were captured and then analyzed using software written at Jefferson Lab that runs ImageJ as it's main image processing library.

Freeman, B.↗
DOE OSTI2020

TESLA's High Gradient March: Thirty years anniversary of TESLA Technology Collaboration (TTC)

In 2020, the TTC (TESLA Technology Collaboration) celebrates 30 years of collaborative efforts on SRF technologies. The first international TESLA workshop on a TeV Energy Superconducting Linear Accelerator was held at Cornell University on July 23-26, 1990. The purpose of the meeting was to work on a parameter list for a superconducting high energy physics collider in the Teravolt energy region and to explore ideas on how to increase the gradients and lower the costs for the accelerator structures. It was clear from the beginning that the needed technological progress would require a large international collaboration. This meeting was indeed the origin of a long preparation effort toward a future ILC (International Linear Collider), which eventually led to the realization of the TTF (TESLA Test Facility, since 2005 operated as the DESY user facility FLASH) and the European XFEL also at DESY, and created the conditions supporting the proposals for several large SRF-based research facilities like SNS, LCLS-II, ESS, PIP-II and SHINE, as well as a growing number of smaller facilities around the world. Highlights of this 30-year international collaboration are presented and celebrated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Cherenkov Light-based Beam Profiling for Ultrarelativistic Electron Beams

We describe a beam profile monitor design based on Cherenkov light emitted from a charged particle beam in an air gap. The main components of the profile monitor are silicon wafers used to reflect Cherenkov light onto a camera lens system. The design allows for measuring large beam sizes, with large photon yield per beam charge and excellent signal linearity with beam charge. Furthermore, the profile monitor signal is independent of the particle energy for ultrarelativistic particles. Different design and parameter considerations are discussed. A Cherenkov light-based profile monitor has been installed at the FACET User Facility at SLAC. Finally, we report on the measured performance of this profile monitor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Principles of Neutron Scattering from Condensed Matter. By Andrew T. Boothroyd. Oxford University Press, 2020. Pp. 512. Price GBP 55.00. ISBN 9780198862314.

Neutron scattering user facilities are increasingly used by ‘non-expert’ users, opening neutron scattering to new science fields and greatly increasing the scientific impact of these facilities. This book aims to bring the needed introduction to the expanding area of neutron scattering techniques to this wider audience of scientists using neutron scattering as part of their experimental portfolio. In my opinion, it completely succeeds in that goal and provides the right balance of introduction and in-depth discussion. I also like the layout of the book, with some figures and notes in the margin making it easy to read and navigate. As a ‘long-time’ neutron scatterer, I am excited to add this book to my book shelf.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Water Vapor Isotopic Measurements during CAPE-K Field Campaign Report

CAPE-K_ISO deployed a Picarro L-2130 water vapor isotope analyzer to the Kennaook/Cape Grim Baseline Air Pollution Station in northwest Tasmania as a guest instrument within the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s Cloud and Precipitation Experiment at Kennaook (CAPE-K). The project was led by Joseph Galewsky at the University of New Mexico and supported the second ARM Mobile Facility (AMF2) deployment by adding continuous measurements of water vapor mixing ratio, delta-18O, delta-D, and deuterium excess in marine boundary-layer air.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Unified User-Friendly Instrument Control and Data Acquisition System for the ORNL SANS Instrument Suite

In an effort to upgrade and provide a unified and improved instrument control and data acquisition system for the Oak Ridge National Laboratory (ORNL) small-angle neutron scattering (SANS) instrument suite—biological small-angle neutron scattering instrument (Bio-SANS), the extended q-range small-angle neutron scattering diffractometer (EQ-SANS), the general-purpose small-angle neutron scattering diffractometer (GP-SANS)—beamline scientists and developers teamed up and worked closely together to design and develop a new system. We began with an in-depth analysis of user needs and requirements, covering all perspectives of control and data acquisition based on previous usage data and user feedback. Our design and implementation were guided by the principles from the latest user experience and design research and based on effective practices from our previous projects. In this article, we share details of our design process as well as prominent features of the new instrument control and data acquisition system. The new system provides a sophisticated Q-Range Planner to help scientists and users plan and execute instrument configurations easily and efficiently. The system also provides different user operation interfaces, such as wizard-type tool Panel Scan, a Scripting Tool based on Python Language, and Table Scan, all of which are tailored to different user needs. The new system further captures all the metadata to enable post-experiment data reduction and possibly automatic reduction and provides users with enhanced live displays and additional feedback at the run time. We hope our results will serve as a good example for developing a user-friendly instrument control and data acquisition system at large user facilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Community Requirements Meta-Analysis: Characterizing Needs and Opportunities for HPDF

This High Performance Data Facility (HPDF) Project is creating a new scientific user facility to provide advanced infrastructure for data-intensive science, supporting the DOE’s Office of Science (SC) community. HPDF’s mission is to enable and accelerate scientific discovery by delivering state-of-the-art data management infrastructure, capabilities, and tools. This meta-analysis examines the needs of the breadth of the SC community, captured in publicly available community reports or mission documents. The meta-analysis identifies and provides initial characterization of fifteen core requirements for the HPDF Project team to consider during the conceptual design phase. The fifteen requirements illustrate how scientific work among SC communities requires modern, seamless user experiences across the ASCR Ecosystem to advance the use of large volumes of heterogeneous data. The scientific community requires support for the missing middle of compute between local and HPC to interactively and collaboratively use growing datasets. Data producers and end users will benefit from enhanced data catalogs and portals that improve data access through advanced search of well curated data. The fifteen requirements are examined here organized across five themes for discussion. Examples in each theme illustrate the array of scientific needs that convey the important role that the fully realized and operational High Performance Data Facility will be able to play as an integral part of the evolving ASCR Ecosystem. Our amalgamated data tables from ESnet reports demonstrate ranges to the volumes of data HPDF must be concerned with, but limitations are inherent to this meta-analysis (see Key Challenges & Limitations). Feedback and validation of these requirements along with additional details and emergent community requirements will be gathered through user research and design activities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High Performance Computing Facility Operational Assessment 2022: Oak Ridge Leadership Computing Facility

The Oak Ridge Leadership Computing Facility (OLCF) was established to accelerate scientific discovery by providing world-leading computational performance and advanced data infrastructure. As a US Department of Energy (DOE) Office of Science user facility, the OLCF has managed the successful deployment and operation of a succession of leadership-class resources dedicated to open science. In addition to these resources, the OLCF staff continually strive to develop innovative processes and technologies, improve security, and empower users through allocation management and comprehensive user support and training. These efforts support the advancement of science by the OLCF users and benefit high-performance computing (HPC) facilities around the world. In calendar year (CY) 2022, the OLCF supported 1,681 users and 570 projects and exceeded all targets for user satisfaction. The facility received an average satisfaction score of 4.6 out of 5 on the annual user survey, and 96% of respondents reported a high satisfaction rate with the OLCF overall. Of the 3,212 user tickets submitted in CY 2022, OLCF staff resolved 97% within 3 business days. The facility also introduced several new services for users this year, including weekly virtual office hours with subject matter experts from ORNL and vendor partners; new views in MyOLCF that allow users to analyze allocation and compute usage for a project; the ability to build and run containers on Summit; and improved data visualization support and training resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

LaserNetUS: A Proposal to Advance North America’s First High Intensity Laser Research Network Final Report

LaserNetUS Collaborative Network established in 2018 is a network of high-power laser facilities supported by the Department of Energy (DOE) Office of Fusion Energy Sciences (FES) and operating effectively as a user facility. Its mission is to advance and promote intense laser science and applications by providing scientists and students with broad access to unique facilities and enabling technologies, advancing the frontiers of laser-science research, and fostering collaboration among researchers and networks from around the world. Users who submit proposals through an annual call are selected by an external and independent proposal review panel (PRP) not involving personnel from any of the facilities.

36 MATERIALS SCIENCE↗
DOE OSTI2018

FY 2018 Annual Status Report for the Nuclear Fuels and Materials Library

The Nuclear Fuels and Materials Library (NFML), which is owned by U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) and curated by the Nuclear Science User Facilities (NSUF), is a collection of specialized information and nuclear fuel and material samples from past and ongoing irradiation test campaigns. The NFML also includes real-world components retrieved from decommissioned power reactors and donations from other sources. The NFML can be accessed through a web portal at the NSUF web page NSUF.INL.gov or directly at https://nsuf-infrastructure.inl.gov/. The NFML was conceived shortly after the NSUF was established in 2007. The concept was to offer Advanced Test Reactor (ATR) irradiated materials and NSUF project samples that were stored in Idaho National Laboratory (INL) hot cells to researchers for use in NSUF-awarded research projects. The NFML catalogue began as a series of electronic spreadsheets gathered from principal investigators (PI) and INL programs. In the summer of 2016, the spreadsheets were migrated into an online database within the NSUF website. The NFML inventory has continued to grow with the addition of NSUF-funded project specimens, Experimental Breeder Reactor No. 2 (EBR-II) legacy samples, and donated material from Oak Ridge National Laboratory (ORNL). The online library technology further evolved with upgrades for users and administrators of the database. NFML outreach in FY 2018 included NSUF representatives at conferences and workshops domestically and internationally. This document provides a status report on the NFML for FY 2018.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

LaserNetUS

For this grant the University of Michigan participated in a consortium funded by the DoE Office of Fusion Energy Sciences to establish a national network of Petawatt-class laser systems to act as domestic user facilities that can enable a broad range of frontier scientific research. This consortium is called LaserNetUS and was directly responsive to recommendations made in a recent National Academy of Sciences Report with regard to US strategy for high intensity laser research, “Opportunities in Intense Ultrafast Lasers: Reaching for the Brightest Light”. As detailed in this report, the research in this area has the potential to transform science in a number of research fields and to open up new areas of fundamental research. High field science was initiated in the US in the 1990’s, and subsequently Europe and Asia have embraced this research field, investing more than a billion dollars in this area over the past several years.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

ARM Mobile Facility Leaving Alaska for U.S. Southeast

The Atmospheric Radiation Measurement (ARM) user facility will soon begin the process of moving its third mobile facility (AMF3) from Alaska to the Southeastern United States. A workshop in August 2018 identified the Southeast as a priority region of interest for further study by ARM. The Southeast is a region with abundant atmospheric convection, yet the land surface, boundary layer, vegetation, and aerosol properties are markedly different from those seen at ARM’s fixed observatory in Oklahoma, allowing opportunities to explore new research questions. To maximize the scientific value of the new site, DOE’s Biological and Environmental Research program selected a site science team that will help guide the move of AMF3. Brookhaven National Laboratory (BNL) in New York will lead the AMF3 relocation effort. Supported by ARM and DOE’s Atmospheric System Research (ASR), the multi-institutional team is responsible for developing a science plan and initial research project for the Southeastern U.S. deployment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Experiment Design with Confidence: CoMET

The Nuclear Science User Facilities (NSUF) has been facilitating nuclear materials research since 2007 by providing access to national laboratory and other partner capabilities at no cost to the researchers. With funding from the Department of Energy – Office of Nuclear Energy, approximately 400 projects have been awarded to support research into radiation effects on fuels and materials. During these ten years, the NSUF has created tools to help researchers write better proposals and perform better research projects. In 2018, several of those tools have been combined to create a single point of access to NSUF information management resources. The Combined Materials Experiment Toolkit or CoMET, combines the Nuclear Energy Infrastructure Database (NEID), the Nuclear Fuels and Materials Library (NFML), and the NSUF proposal system, with a new subject matter expert database and an experiment design tool. The NEID contains information on 500 nuclear R&D facilities around the world, including 85 NSUF partner facilities. The NFML has information on nearly 10,000 material specimens, mostly irradiated materials, which can be used for research in NSUF projects. The new SME database includes contact information for NSUF researchers and scientists. The experiment design tool is an expert system that can guide a researcher through the process of designing an NSUF project by interacting with the other resources. Once a researcher has worked through this process, they will be able to save their experiment plan and input it into the NSUF proposal system. These tools are intended to aid both new and veteran researchers build solid research projects and take full advantage of NSUF resources. They also help the NSUF administer the hundreds of proposals that it receives each year. In the future, NSUF plans to add integrated data storage and retrieval to CoMET.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

US Department of Energy, Office of Science, High-Performance Computing Facility: 2023 Operational Assessment Oak Ridge Leadership Computing Facility

The Oak Ridge Leadership Computing Facility (OLCF) was established to accelerate scientific discovery by providing world-leading computational performance and advanced data infrastructure. As a US Department of Energy (DOE) Office of Science user facility, the OLCF has managed the successful deployment and operation of a succession of leadership-class resources dedicated to open science. In addition to these resources, the OLCF staff continually strive to develop innovative processes and technologies, improve security, and empower users through effective allocation management and comprehensive user support and training. These efforts support the advancement of science by the OLCF users and benefit high-performance computing (HPC) facilities around the world. In calendar year (CY) 2023, the OLCF supported 1,676 users and 598 projects and exceeded all targets for user satisfaction. The facility received an average satisfaction score of 4.52 out of 5 on the annual user survey, and 94% of respondents reported a high satisfaction rate with the OLCF overall. Of the 3,619 user tickets submitted in CY 2023, OLCF staff resolved 97% within 3 business days. The facility opened Frontier to full scientific operations this year. Two projects conducted on Frontier received the Association for Computing Machinery (ACM) Gordon Bell Prize and the Gordon Bell Special Prize for Climate Modeling, and a third earned a nomination as a Gordon Bell Prize finalist. The facility’s previous flagship machine, Summit, gained new life and was extended through 2024 in part to help provide resources to the Integrated Research Infrastructure (IRI) projects and the National Artificial Intelligence Research Resource (NAIRR) pilot program. The facility instantiated an Advanced Computing Ecosystem testbed in part to support IRI workflows. OLCF made interactivity easier and more accessible to users than ever through tools like Jupyter notebooks and workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Tensorized Feature Spaces for Feature Explosion

In this paper 1 1 This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-000R22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan) This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-000R22725., we present a novel framework that uses tensor factorization to generate richer feature spaces for pixel classification in hyperspectral images. In particular, we assess the performance of different tensor rank decomposition methods as compared to the traditional kernel-based approaches for the hyperspectral image classification problem. We propose Orion, which takes as input a hyperspectral image tensor and a rank and outputs an enhanced feature space from the factor matrices of the decomposed tensor. Our method is a feature explosion technique that inherently maps low dimensional input space in $\mathbb{R}^{K}$ to high dimensional space in $\mathbb{R}^{R}$ , where $R\gg K$ , say in the order of 1000x, like a kernel. We show how the proposed method exploits the multi-linear structure of hyperspectral three dimensional tensor. We demonstrate the effectiveness of our method with experiments on three publicly available hyperspectral datasets with labeled pixels and compare their classification performance against traditional linear and non-linear supervised learning methods such as SVM with Linear, Polynomial, RBF kernels, and the Multi-Layer Perceptron model. Finally, we explore the relationship between the rank of the tensor decomposition and the classification accuracy using several hyperspectral datasets with ground truth.

Pasricha, Ravdeep Singh↗
DOE OSTI2021

Model America - data and models of every U.S. building

The 5-year goal of the 'Model America' concept was to generate a model of every building in the United States. This data repository delivers on that goal. Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,714,640 buildings detected in the United States and this dataset contains 122,930,327 (97.8%) buildings which resulted in a successful simulation. Future, annual updates have been proposed that may include additional buildings, data improvements, or other algorithmic enhancements. This dataset of 122.9 million buildings includes: Models (state_county.zip) - OpenStudio (v3.1.0) and EnergyPlus (v9.4) building energy models. Please note that the download requires the free Globus Connect Personal (https://www.globus.org/globus-connect-personal); Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus(v9.4) 2,784-page Input/Output Reference Guide (https://energyplus.net/sites/all/modules/custom/nrel_custom/pdfs/pdfs_v9.4.0/InputOutputReference.pdf) for everything that can be retrieved or simulated from these models. These models were derived from the following metadata, which is not included in this dataset: 1. ID - unique building ID 2. County - county name 3. State - state name 4. CZ - ASHRAE Climate Zone designation 5. Clim_Zone - text label of climate zone 6. est_year - estimated year of construction 7. est_commercial - estimated building type (0=residential, 1=commercial) 8. Centroid - building center location in latitude/longitude (from Footprint2D) 9. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 10. Height - building height (meters) 11. Area2D - footprint area (ft2) 12. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 13. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 14. NumFloors - number of floors (above-grade) 15. Area - estimate of total conditioned floor area (ft2) 16. Standard - building vintage. These models are made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy's (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. Please cite as: New, Joshua R., Adams, Mark, Bass, Brett, Berres, Anne, and Clinton, Nicholas (2021). 'Model America - data and models of every U.S. building. [Data set].' Constellation, doi.ccs.ornl.gov/ui/doi/339, April 14, 2021

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

CINT 2026 Strategic Plan

The Center for Integrated Nanotechnologies (CINT) plays a leadership role in the area of nanoscience through its function as a Department of Energy (DOE), Office of Science Nanoscale Science Research Center national user facility. By creating a collaborative community of diverse users and expert scientific staff, CINT fosters high-impact nanoscience discoveries, leads next-generation technique development, and advances the frontiers of knowledge beyond that which is achievable by individual researchers or any single institution.

77 NANOSCIENCE AND NANOTECHNOLOGY↗