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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Application of Flex-QA Arrays in HTS Magnet Testing

Flexible PCB quench antennas have been very useful in providing high-quality high-resolution data in low temperature superconducting magnet tests. Similar multi-sensor arrays have been employed recently to cover a high temperature superconductor magnet tested at FNAL. In the present work, data taking conditions and magnet features to support the analysis framework are discussed. Then observations made during complete magnet powering cycles are described and analysis of quench antenna data are presented. Based on results, improvements to instrumentation and data taking are debated. Views on the future of flexible quench antenna sensors for HTS magnet diagnostics and operational support are shared.

Stoynev, S.↗
DOE OSTI2025

Deploying and Operating CephFS for Scientific Applications at Fermilab

Fermilab has been running a Ceph cluster in production for several years to support high-throughput scientific computing. Our primary use case is CephFS, which serves interactive data analysis workloads, with growing interest in using RGW for scalable object storage of scientific datasets. In this talk, we'll share lessons learned from successfully deploying and maintaining our Ceph cluster with cephadm, including challenges faced, performance tuning, and operational practices. We'll also present custom tools we've developed to streamline monitoring and management and discuss how Ceph fits into our broader storage architecture for large-scale scientific research.

Peisker, Alison [Fermilab]↗
DOE OSTI2020

GCAM-Demeter-LU

This GCAM-Demeter-LU is made available under the Open Data Commons Attribution License:http://opendatacommons.org/licenses/by/1.0/. The dataset includes the projected global gridded land cover (excluding the Antarctic) for the period of 2015-2100 at 0.05-degree resolution and 5-year time step under fifteen SSP-RCP scenarios driven by five GCMs (i.e., gfdl, hadgem, ipsl, miroc, and noresm), using the Global Change Analysis Model (GCAM) and a geospatial downscaling model (Demeter). The data has been stored in self-describing NetCDF format. The dataset also includes the mean and standard deviation of the results driven by the five GCMs. More specifically, the data in each year includes grid-explicit fraction (in percent) of each of the 32 plant functional types that are widely used in current Earth system models. The NetCDF files are named as “GCAM_Demeter_LU_SSP_RCP_Model_Year.nc”, where “SSP” and “RCP” denote the SSP and RCP scenarios, including 'ssp1_rcp26', 'ssp1_rcp45', 'ssp1_rcp60', 'ssp2_rcp26', 'ssp2_rcp45', 'ssp2_rcp60', 'ssp3_rcp45', 'ssp3_rcp60', 'ssp4_rcp26', 'ssp4_rcp45', 'ssp4_rcp60', 'ssp5_rcp26', 'ssp5_rcp45', 'ssp5_rcp60', and 'ssp5_rcp85'. “Year” denotes the year of the land use data, and “GCM” denotes the source driving forcing data from five global climate models (gfdl, hadgem, ipsl, miroc, and noresm), or the mean (“modelmean”) and the standard deviation (“modelstd”) of the results from the five GCMs.See https://github.com/JGCRI/chen_et_al_2020a for details on how to reproduce this data. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Cloud-Based Demonstration of the Eastern Interconnection Situational Awareness Monitoring System (ESAMS)

This report describes a cloud-based implementation and field demonstration of the Eastern Interconnection Situational Awareness and Monitoring System (ESAMS). ESAMS was developed to support the detection and source localization of forced oscillations using synchrophasor measurements from tie-lines connecting areas served by different reliability coordinators (RCs), so that RCs could better coordinate their response to wide-area events. A previous effort had identified deployment barriers associated with hosting shared situational awareness tools at a single RC. To address these barriers, ESAMS was migrated to Amazon Web Services and evaluated in a six-month field demonstration. ISO New England (ISO-NE) and PJM streamed data to the platform using AWS Direct Connect and a site-to-site VPN, respectively. The resulting multi-utility measurement footprint enabled regional source localization across major portions of the U.S. Eastern Interconnection and supported routine identification of oscillation events. During the final three months of the trial, 24 events above 2 MW/MVAR were detected. The largest detected oscillation approached a 25 MW peak-to-peak amplitude, and the longest persisted intermittently for more than 11 hours. The demonstration also assessed operational considerations—including data transfer volumes, end-to-end latency, and cloud computing costs—and found that network and compute requirements were modest relative to typical cloud capabilities while providing performance comparable to prior on-premises deployments. Overall, the results indicate that cloud hosting can provide a practical path to shared interconnection-wide oscillation monitoring. The cloud ESAMS demonstration establishes a foundation for broader utility participation and for building future wide-area analytics that leverage measurements across organizational boundaries.

Follum, James D.↗
DOE OSTI2024

Central Asia Seismic Hazard Assessment (CASHA): A Probabilistic Seismic Hazard Assessment for Kazakhstan, Kyrgyzstan and Tajikistan

Probabilistic seismic hazard assessments (PSHA) underpin the calculation of earthquake loads in most building codes around the world. In Central Asia, the building codes are slowly being updated to incorporate some of the contemporary concepts of seismic hazard representation. There is also a regional desire to coordinate hazard assessments and building code modernization. However, some challenges remain. Expertise in the region related to seismic hazard assessments is still largely compartmentalised, requiring a significant amount of training and capacity building in seismic hazard assessment related topics. In addition, there are vast amounts of seismic data (bulletin and waveforms), both from analogue and digital eras, that the region’s countries stored but until recently did not use or share among themselves or with the broader seismological community around the world. Finally, after the collapse of the Soviet Union in the 1990s, many of the countries’ seismic networks suffered a major setback with the lack of attention and budget to update existing equipment and installation of new instruments. In order to address these issues, the United States Department of Energy through Lawrence Livermore National Laboratory (LLNL) initiated a project in 2016 to engage and train local scientists in Central Asia to install new equipment, to enhance the quality of seismic monitoring and reporting, to improve and harmonise the regional earthquake catalogue, and to conduct national probabilistic seismic hazard assessments using the new and improved datasets. To achieve the seismic hazard assessment related goals, a series of workshops were held in Almaty, Kazakhstan; Bishkek, Kyrgyzstan; and Dushanbe, Tajikistan from 2016 until 2020. During the time that the COVID-19 pandemic restricted travel, workshops continued online (22 online workshops were hosted in two years). Finally, in May 2022, an in-person workshop in Istanbul, Turkey brought together all project participants along with civil engineers engaged with building code activities in their respective countries, providing a platform to discuss the implementation of the hazard models into updates of building codes in each country, as well as to discuss model parameters, sensitivity analyses and model results in terms of hazard maps, uniform hazard spectra and hazard deaggregations. The workshops were a combination of lectures and hands-on exercises, and included international participation as well as local scientists and engineers. The workshops served several purposes, including training, coordination of data collection, interactions between local earth scientists and engineers, and brainstorming and knowledge exchange among local and international experts. This report outlines the new earthquake catalogue compilation effort and the PSHA project undertaken in Kyrgyzstan, Tajikistan, and Kazakhstan as part of this initiative. The southern part of this region is tectonically active with moderate to high levels of both shallow crustal seismic activity and occurrence of deeper earthquakes under the Hindu Kush and Pamir mountain ranges. Deeper earthquakes also occur near southwestern Kazakhstan, under the eastern Greater Caucasus and Caspian Sea. Large portions of central and northern Kazakhstan, on the other hand, are in stable continental regions with low levels of seismic activity. This study systematically compiles and improves all available data on local seismicity, active faults, and ground motion attenuation characteristics of the region; and builds a framework to enable a contemporary PSHA to be carried out with the engagement of local scientists. While the project was regional, the seismic hazard assessments are primarily driven by the countries’ own national preferences and understanding of data collection, interpretation, and validation of results.

58 GEOSCIENCES↗
DOE OSTI2024

Inverter Model Validation and Calibration Using Phasor Measurement Unit Data

As the penetration of inverter-based renewable energy resources increases in the power grid, especially at the distribution and microgrid levels, the need to accurately represent them in planning studies increases as well. However, due to the lack of well-established standard procedures, and vendor reluctance towards the detailed sharing of proprietary models, automated dynamic model validation and parameter calibration tools for inverter based resources (IBRs) remain scarce. This work presents a model validation and parameter calibration platform for representing IBRs with generic phasor-domain models. Phasor measurements of power system events are used for continuous validation using the data playback method, and model parameters are re-calibrated if a significant mismatch between measurements and model response is observed. Unique features of the proposed platform include- (a) an iterative Bayesian optimization approach towards parameter calibration to address a possible mismatch between the structures of generic models implemented in simulation softwares and actual commercial inverters, (b) error metrics designed to account for a possible mismatch between the time resolution of simulation and measurements, and (c) analysis of the measurement-simulation mismatch to provide guidance to engineering personnel regarding model shortcomings. The performance of the platform has been illustrated using both simulated data and field measurements to validate/calibrate inverter models in GridLAB-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A Simple Standard for Sharing Ontological Mappings (SSSOM)

Abstract Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Materials Data on BaEr2F8 by Materials Project

Er2BaF8 crystallizes in the monoclinic C2/m space group. The structure is three-dimensional. Ba2+ is bonded to twelve F1- atoms to form face-sharing BaF12 cuboctahedra. There are a spread of Ba–F bond distances ranging from 2.77–2.96 Å. Er3+ is bonded in a 8-coordinate geometry to eight F1- atoms. There are a spread of Er–F bond distances ranging from 2.24–2.32 Å. There are three inequivalent F1- sites. In the first F1- site, F1- is bonded in a 2-coordinate geometry to one Ba2+ and two equivalent Er3+ atoms. In the second F1- site, F1- is bonded in a distorted trigonal non-coplanar geometry to one Ba2+ and two equivalent Er3+ atoms. In the third F1- site, F1- is bonded in a 2-coordinate geometry to two equivalent Ba2+ and two equivalent Er3+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Zn13Rh by Materials Project

RhZn13 crystallizes in the monoclinic C2/m space group. The structure is three-dimensional. Rh is bonded to twelve Zn atoms to form corner-sharing RhZn12 cuboctahedra. There are a spread of Rh–Zn bond distances ranging from 2.58–2.69 Å. There are five inequivalent Zn sites. In the first Zn site, Zn is bonded in a distorted linear geometry to two equivalent Rh and two equivalent Zn atoms. Both Zn–Zn bond lengths are 2.79 Å. In the second Zn site, Zn is bonded in a 1-coordinate geometry to one Rh and four Zn atoms. There are a spread of Zn–Zn bond distances ranging from 2.60–2.84 Å. In the third Zn site, Zn is bonded in a 1-coordinate geometry to one Rh and four Zn atoms. There are a spread of Zn–Zn bond distances ranging from 2.65–2.85 Å. In the fourth Zn site, Zn is bonded in a 1-coordinate geometry to one Rh and ten Zn atoms. The Zn–Zn bond length is 2.59 Å. In the fifth Zn site, Zn is bonded in a 10-coordinate geometry to ten Zn atoms. The Zn–Zn bond length is 2.72 Å.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on IrF4 by Materials Project

IrF4 crystallizes in the orthorhombic Fdd2 space group. The structure is three-dimensional. Ir4+ is bonded to six F1- atoms to form corner-sharing IrF6 octahedra. The corner-sharing octahedral tilt angles are 48°. There are a spread of Ir–F bond distances ranging from 1.89–2.05 Å. There are two inequivalent F1- sites. In the first F1- site, F1- is bonded in a single-bond geometry to one Ir4+ atom. In the second F1- site, F1- is bonded in a distorted bent 120 degrees geometry to two equivalent Ir4+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on PdF4 by Materials Project

PdF4 crystallizes in the orthorhombic Fdd2 space group. The structure is three-dimensional. Pd4+ is bonded to six F1- atoms to form corner-sharing PdF6 octahedra. The corner-sharing octahedral tilt angles are 50°. There are a spread of Pd–F bond distances ranging from 1.88–2.06 Å. There are two inequivalent F1- sites. In the first F1- site, F1- is bonded in a single-bond geometry to one Pd4+ atom. In the second F1- site, F1- is bonded in a bent 120 degrees geometry to two equivalent Pd4+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on MgSe2O5 by Materials Project

MgSe2O5 crystallizes in the orthorhombic Pbcn space group. The structure is three-dimensional. Mg2+ is bonded to six O2- atoms to form edge-sharing MgO6 octahedra. There are two shorter (2.12 Å) and four longer (2.13 Å) Mg–O bond lengths. Se4+ is bonded in a distorted trigonal non-coplanar geometry to three O2- atoms. There are a spread of Se–O bond distances ranging from 1.69–1.87 Å. There are three inequivalent O2- sites. In the first O2- site, O2- is bonded in a bent 120 degrees geometry to two equivalent Se4+ atoms. In the second O2- site, O2- is bonded in a bent 120 degrees geometry to one Mg2+ and one Se4+ atom. In the third O2- site, O2- is bonded in a distorted trigonal planar geometry to two equivalent Mg2+ and one Se4+ atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on MgNb2O6 by Materials Project

MgNb2O6 crystallizes in the orthorhombic Pbcn space group. The structure is three-dimensional. Mg2+ is bonded to six O2- atoms to form edge-sharing MgO6 octahedra. There are a spread of Mg–O bond distances ranging from 2.09–2.15 Å. Nb5+ is bonded in a 6-coordinate geometry to six O2- atoms. There are a spread of Nb–O bond distances ranging from 1.83–2.34 Å. There are three inequivalent O2- sites. In the first O2- site, O2- is bonded in a 3-coordinate geometry to three equivalent Nb5+ atoms. In the second O2- site, O2- is bonded in a distorted trigonal planar geometry to two equivalent Mg2+ and one Nb5+ atom. In the third O2- site, O2- is bonded in a trigonal planar geometry to one Mg2+ and two equivalent Nb5+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on ZnSe2O5 by Materials Project

ZnSe2O5 crystallizes in the orthorhombic Pbcn space group. The structure is three-dimensional. Zn2+ is bonded to six O2- atoms to form edge-sharing ZnO6 octahedra. There are a spread of Zn–O bond distances ranging from 2.13–2.16 Å. Se4+ is bonded in a distorted trigonal non-coplanar geometry to three O2- atoms. There are a spread of Se–O bond distances ranging from 1.70–1.87 Å. There are three inequivalent O2- sites. In the first O2- site, O2- is bonded in a bent 120 degrees geometry to two equivalent Se4+ atoms. In the second O2- site, O2- is bonded in a bent 120 degrees geometry to one Zn2+ and one Se4+ atom. In the third O2- site, O2- is bonded in a distorted trigonal planar geometry to two equivalent Zn2+ and one Se4+ atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on V2Zn2O7 by Materials Project

Zn2V2O7 crystallizes in the monoclinic C2/m space group. The structure is three-dimensional. V5+ is bonded to four O2- atoms to form corner-sharing VO4 tetrahedra. There is two shorter (1.72 Å) and two longer (1.78 Å) V–O bond length. Zn2+ is bonded in a 6-coordinate geometry to six O2- atoms. There are a spread of Zn–O bond distances ranging from 2.00–2.55 Å. There are three inequivalent O2- sites. In the first O2- site, O2- is bonded in a distorted trigonal planar geometry to one V5+ and two equivalent Zn2+ atoms. In the second O2- site, O2- is bonded in a 2-coordinate geometry to one V5+ and two equivalent Zn2+ atoms. In the third O2- site, O2- is bonded in a linear geometry to two equivalent V5+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on CoSe2O5 by Materials Project

CoSe2O5 crystallizes in the orthorhombic Pbcn space group. The structure is three-dimensional. Co2+ is bonded to six O2- atoms to form edge-sharing CoO6 octahedra. There are a spread of Co–O bond distances ranging from 2.11–2.15 Å. Se4+ is bonded in a distorted trigonal non-coplanar geometry to three O2- atoms. There are a spread of Se–O bond distances ranging from 1.70–1.87 Å. There are three inequivalent O2- sites. In the first O2- site, O2- is bonded in a 3-coordinate geometry to two equivalent Co2+ and one Se4+ atom. In the second O2- site, O2- is bonded in a bent 120 degrees geometry to two equivalent Se4+ atoms. In the third O2- site, O2- is bonded in a distorted bent 120 degrees geometry to one Co2+ and one Se4+ atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on MnSe2O5 by Materials Project

MnSe2O5 crystallizes in the monoclinic C2/c space group. The structure is three-dimensional. Mn2+ is bonded to six O2- atoms to form edge-sharing MnO6 octahedra. There are a spread of Mn–O bond distances ranging from 2.18–2.25 Å. Se4+ is bonded in a trigonal non-coplanar geometry to three O2- atoms. There are a spread of Se–O bond distances ranging from 1.69–1.86 Å. There are three inequivalent O2- sites. In the first O2- site, O2- is bonded in a distorted bent 150 degrees geometry to two equivalent Se4+ atoms. In the second O2- site, O2- is bonded in a distorted bent 120 degrees geometry to one Mn2+ and one Se4+ atom. In the third O2- site, O2- is bonded in a distorted trigonal planar geometry to two equivalent Mn2+ and one Se4+ atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on ZrPbS3 by Materials Project

ZrPbS3 crystallizes in the orthorhombic Pnma space group. The structure is three-dimensional. Zr4+ is bonded to six S2- atoms to form edge-sharing ZrS6 octahedra. There are a spread of Zr–S bond distances ranging from 2.54–2.62 Å. Pb2+ is bonded in a 8-coordinate geometry to eight S2- atoms. There are a spread of Pb–S bond distances ranging from 2.75–3.70 Å. There are three inequivalent S2- sites. In the first S2- site, S2- is bonded in a 4-coordinate geometry to three equivalent Zr4+ and one Pb2+ atom. In the second S2- site, S2- is bonded in a 2-coordinate geometry to two equivalent Zr4+ and three equivalent Pb2+ atoms. In the third S2- site, S2- is bonded in a 1-coordinate geometry to one Zr4+ and four equivalent Pb2+ atoms.

36 MATERIALS SCIENCE↗