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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Scalable Metadata Management for a Large Multi-Source Seismic Data Repository

In this work, we implemented the key metadata management components of a scalable seismic data ingestion framework to address limitations in our existing system, and to position it for anticipated growth in volume and complexity. We began the effort with an assessment of open source data flow tools from the Hadoop ecosystem. We then began the construction of a layered architecture that is specifically designed to address many of the scalability and data quality issues we experience with our current pipeline. This included implementing basic functionality in each of the layers, such as establishing a data lake, designing a unified metadata schema, tracking provenance, and calculating data quality metrics. Our original intent was to test and validate the new ingestion framework with data from a large-scale field deployment in a temporary network. This delivered somewhat unsatisfying results, since the new system immediately identified fatal flaws in the data relatively early in the pipeline. Although this is a correct result it did not allow us to sufficiently exercise the whole framework. We then widened our scope to process all available metadata from over a dozen online seismic data sources to further test the implementation and validate the design. This experiment also uncovered a higher than expected frequency of certain types of metadata issues that challenged us to further tune our data management strategy to handle them. Our result from this project is a greatly improved understanding of real world data issues, a validated design, and prototype implementations of major components of an eventual production framework. This successfully forms the basis of future development for the Geophysical Monitoring Program data pipeline, which is a critical asset supporting multiple programs. It also positions us very well to deliver valuable metadata management expertise to our sponsors, and has already resulted in an NNSA Office of Defense Nuclear Nonproliferation commitment to a multi-year project for follow-on work.

58 GEOSCIENCES↗
DOE OSTI2018

SNL Lesson Learned and Guidance for Data Repositories and Analytic Frameworks

This document represents the results of deliverable D05.02 (Identify relevant efforts at SNL and other institutions) under the activity area Relevant Efforts Review. The goal of the Relevant Efforts Review activity is to identify relevant data integration efforts at SNL and possibly other institutions and compile lessons learned that are relevant to the development of a framework for data integration efforts in support of analysts and decision makers. The intent of this activity is to provide, by examples, context of how the requirements-gathering process has already been implemented in other instances and to guide the development of such a process for OCIA's needs. Information for this report was gathered through SNL staff interviews and the team members' knowledge and project experiences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Evaluation of the Computing Systems for Yucca Mountain Repository TSPA-LA Model Operational Readiness

Sandia National Laboratories (SNL) was tasked to conduct an evaluation of the legacy computing systems of the now-closed Yucca Mountain Project (YMP) to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, in the event that the License Application (LA) review by the U.S. Nuclear Regulatory Commission (NRC) is re-started and involves additional requests for information (RAIs). Six problem areas or components of the computing system were identified and subsequently resolved or improved to ensure the operational readiness of the TSPA-LA model capability on the server cluster. As part of this readiness review, the legacy TSPA computational cluster that was relocated from the SNL YMP Lead Lab Project Office in Las Vegas, Nevada to the SNL offices in Albuquerque, New Mexico was replaced with new hardware. Three floating licenses of Goldsim Version 9.60.300 were installed on the new cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software was tested and installed to support the TSPA- type analysis on the server cluster. TSPA-LA modeling cases were tested and verified for the model reproducibility on the current server cluster. All test runs were executed on multiple processors on the server cluster utilizing the Goldsim distributed processing capability, and all runs were completed successfully. The model reproducibility verification was evaluated by two approaches: numerical value comparison and graphical comparison, and the analysis demonstrated an excellent reproducibility of the TSPA-LA model runs on the server cluster. The current server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Weapons Active Repository for Radiographs and Film (WARF) [Slides]

NSRC’s lineages dates to the Technical Library formed by J. Robert Oppenheimer in 1943 as part of the Manhattan Project. Houses 75+ years of nuclear weapons research, designs, procedures, reports, etc. This is the largest collection of nuclear weapons information anywhere in the nation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Consolidated Hydropower Data Repository: Value and Opportunities

Hydropower is one of several types of generating assets that provides energy, capacity, and services to electric power systems. It does so under rubrics and objectives—market driven and regulated, internal and external to asset and fleet owners—that address reliability, cost, price, and, increasingly, flexibility of output. The aggregation of data from multiple hydropower units can provide insights into asset operations and maintenance practices and needs and assist in meeting hydropower objectives. This paper examines the concept and potential benefits of aggregating hydropower asset data—primarily supervisory control and data acquisition (SCADA) information—with examples of insights developed from data aggregated by the Hydropower Research Institute (HRI). Data aggregation as discussed herein, and as implemented by the HRI, extends beyond multiple units in a powerhouse and beyond multiple hydropower facilities in an electric utility fleet or river system. Examples of research and analytics from such aggregated datasets range from unit load dependency analyses to modeling sensor measurements to detect and diagnose anomalies in assets. These examples showed the benefits of utilizing the entire dataset for insights into how the sensor layout of a single unit or set of units compares to the hydropower industry overall. Such insights include whether additional sensors are needed to complete analyses or to make decisions. In addition, utilizing multiple sensors of the same kind within a unit can provide an indication of possible current or upcoming problems with equipment. Although other analyses are possible, their use requires the development of complex models and, potentially, access to types of data that are currently not included with the example dataset used in this study. However, the examples studied herein confirmed the value of data aggregation in the fleet and unit contexts, and the value extends beyond multiple units in a powerhouse and beyond multiple hydropower facilities in an electric utility fleet or river system. The assessments also provided insights into potential extensions to the data aggregation concept that could further add to their value to the hydropower community, and these are included in this document as a set of recommendations.

13 HYDRO ENERGY↗