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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 1,549 records · Page 86

Carbon Storage Technical Viability Approach (CS TVA) Database

The Carbon Storage Technical Viability Approach (CS TVA) database was developed to support the implementation of the CS TVA Matrix to a national data availability assessment for technically viable carbon storage. This database leverages the efforts of multiple adjacent and overlapping databases by non-redundantly combining the databases into a single database along with additionally providing tags facilitating the CS TVA. The non-redundant aspect of the database permits an accurate assessment of the concentration of available data, aiding in spatial and categorical data gaps analysis relative to the individual CS TVA Matrix Components. Version 2.0 of the database is an expansion of Version 1.0. Version 2.0 was created to include additional data gathered to fill gaps in the existing data set. Downloading the CS TVA v2.0 database will result in two separate databases, the version 1.0 original .gdb, and a second addendum .gdb with the new data gathered, together these two databases make up v2.0. Please see the ReadMe file below for full details, metadata information, use disclaimer, and attributions.

Coal↗

The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST

We present TXPipe, a modular, automated and reproducible pipeline for ingesting catalog data and performing all the calculations required to obtain quality-assured two-point measurements of lensing and clustering, and their covariances, with the metadata necessary for parameter estimation. The pipeline is developed within the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC), and designed for cosmology analyses using LSST data. In this paper, we present the pipeline for the so-called 3x2pt analysis -- a combination of three two-point functions that measure the auto- and cross-correlation between galaxy density and shapes. We perform the analysis both in real and harmonic space using TXPipe and other LSST-DESC tools. We validate the pipeline using Gaussian simulations and show that it accurately measures data vectors and recovers the input cosmology to the accuracy level required for the first year of LSST data under this simplified scenario. We also apply the pipeline to a realistic mock galaxy sample extracted from the CosmoDC2 simulation suite (Korytov et al. 2019). TXPipe establishes a baseline framework that can be built upon as the LSST survey proceeds. Furthermore, the pipeline is designed to be easily extended to science probes beyond the 3x2pt analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Science Capsule - Capturing the Data Life Cycle

The data generated from scientific workflows often become unusable due to the lack or incompleteness of information required for processing and analyzing the data. Reproducibility of scientific data and workflows facilitates efficient processing and analyses. A key to enabling reproducibility is to capture the end-to-end workflow life cycle, and any contextual metadata and provenance.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Curifactory: A research experiment manager

Curifactory is a command line tool and framework for organizing Python experiment code, configuration parameters, and results. It is an opinionated and lightweight approach to workflow management infrastructure and is primarily intended to support researchers conducting experiments on one machine. This software was developed to support the reproducibility of results for several data science projects in the Nuclear Nonproliferation Division at Oak Ridge National Laboratory. Curifactory is intended to be a general framework and is not specific to machine learning or data science. It can aid in any field in which experiments are primarily computation-based studies and can be implemented in Python (e.g., high-energy physics, astronomy, computational chemistry). Here, the design emphasizes the automated caching of intermediate data analysis artifacts to speed up development involving computationally intensive tasks. It also allows for data provenance and experiment reproduction. Individual experiment runs are tracked through logs and their output reports, and entire copies of a run with all cached data and metadata can be exported for others to run using Curifactory on another machine. Curifactory experiments can either be integrated into a project from the beginning or can be written on top of an existing codebase without needing significant modification. A few important views of the Curifactory library can be seen in Figure 1.

97 MATHEMATICS AND COMPUTING↗

xCDAT: A Python Package for Simple and Robust Analysis of Climate Data

xCDAT (Xarray Climate Data Analysis Tools) is an open-source Python package that extends Xarray (Hoyer & Hamman, 2017) for climate data analysis on structured grids. xCDAT streamlines analysis of climate data by exposing common climate analysis operations through a set of straightforward APIs. Some of xCDAT’s key features include spatial averaging, temporal averaging, and regridding. These features are inspired by the Community Data Analysis Tools (CDAT) library (Dean N. Williams et al., 2009) (D. N. Williams, 2014) (Doutriaux et al., 2019) and leverage powerful packages in the Xarray ecosystem including xESMF (Zhuang et al., 2023), xgcm (Abernathey et al., 2022), and CF xarray (Cherian et al., 2023). To ensure general compatibility across various climate models, xCDAT operates on datasets that are compliant with the Climate and Forecast (CF) metadata conventions (Hassell et al., 2017).

54 ENVIRONMENTAL SCIENCES↗

Making digital objects FAIR in high energy physics: An implementation for Universal FeynRules Output (UFO) models

Research in the data-intensive discipline of high energy physics (HEP) often relies on domain-specific digital contents. Reproducibility of research relies on proper preservation of these digital objects. This paper reflects on the interpretation of principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) in such context and demonstrates its implementation by describing the development of an end-to-end support infrastructure for preserving and accessing Universal FeynRules Output (UFO) models guided by the FAIR principles. UFO models are custom-made python libraries used by the HEP community for Monte Carlo simulation of collider physics events. Our framework provides simple but robust tools to preserve and access the UFO models and corresponding metadata in accordance with the FAIR principles.

Neubauer, Mark S.↗

Codebase release 2.0 for UFOManager

Research in the data-intensive discipline of high energy physics (HEP) often relies on domain-specific digital contents. Reproducibility of research relies on proper preservation of these digital objects. This paper reflects on the interpretation of principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) in such context and demonstrates its implementation by describing the development of an end-to-end support infrastructure for preserving and accessing Universal FeynRules Output (UFO) models guided by the FAIR principles. UFO models are custom-made python libraries used by the HEP community for Monte Carlo simulation of collider physics events. Our framework provides simple but robust tools to preserve and access the UFO models and corresponding metadata in accordance with the FAIR principles.

Neubauer, Mark S.↗

Practical procedures for sensor quality assessment

Sensors are increasingly deployed for process monitoring and control. These produce on-line measurements at a high frequency, in parallel with low-frequency laboratory measurements. Compared to laboratory practices, sensor data quality assessment and control practices are far less structured at most utilities. This leads to inaccurate sensor data with unknown uncertainty factors.This chapter shows how to establish standard operating procedures (SOPs) to support sensor data quality assessment and control and subsequent maintenance actions by producing relevant sensor metadata. Furthermore, SOPs are provided for the most commonly used wastewater quality sensors, inspired by utility and academic best practices. This chapter builds on definitions provided in Chapter 3 and provides additional definitions specifically related to sensors maintenance. Chapter 6 complements the methods in this chapter, which are based on reference measurements, with data-analytical techniques.

Alferes, Janelcy↗

Analytical methods for online data quality assessment

This chapter provides a comprehensive overview of the main steps for algorithmic sensor signal quality assessment, which can enhance the decision-making process for water resource recovery facility (WRRF) operation and optimization. It introduces the concept of redundancy as the basis for data quality assessment. It also explains the typical data processing pipeline, which consists of preliminary analysis, data pre-processing, and specific algorithmic approaches. Each of these processes is presented and discussed in three separate sections. Importantly, this chapter introduces the main approaches for data quality assessment, provides guidelines for selecting the most suitable one and the key performance indicators to evaluate them and explains how to collect metadata through such an algorithmic approach.

Aguado, Daniel↗

PyDecay/GraphPhys: A Unified Language and Storage System for Particle Decay Process Descriptions

To ease the tasks of Monte Carlo (MC) simulation and event reconstruction (i.e. inferring particle-decay events from experimental data) for long-term BaBar data preservation and analysis, the following software components have been designed: a language ('GraphPhys') for specifying decay processes, common to both simulation and data analysis, allowing arbitrary parameters on particles, decays, and entire processes; an automated visualization tool to show graphically what decays have been specified; and a searchable database storage mechanism for decay specifications. Unlike HepML, a proposed XML standard for HEP metadata, the specification language is designed not for data interchange between computer systems, but rather for direct manipulation by human beings as well as computers. The components are interoperable: the information parsed from files in the specification language can easily be rendered as an image by the visualization package, and conversion between decay representations was implemented. Several proof-of-concept command-line tools were built based on this framework. Applications include building easier and more efficient interfaces to existing analysis tools for current projects (e.g. BaBar/BESII), providing a framework for analyses in future experimental settings (e.g. LHC/SuperB), and outreach programs that involve giving students access to BaBar data and analysis tools to give them a hands-on feel for scientific analysis.

99 GENERAL AND MISCELLANEOUS↗

Development of an Ontology-Directed Signal Processing Toolbox

This project was focused on the development of tools for the automatic configuration of signal processing systems. The goal is to develop tools that will be useful in a variety of Government and commercial areas and useable by people who are not signal processing experts. In order to get the most benefit from signal processing techniques, deep technical expertise is often required in order to select appropriate algorithms, combine them into a processing chain, and tune algorithm parameters for best performance on a specific problem. Therefore a significant benefit would result from the assembly of a toolbox of processing algorithms that has been selected for their effectiveness in a group of related problem areas, along with the means to allow people who are not signal processing experts to reliably select, combine, and tune these algorithms to solve specific problems. Defining a vocabulary for problem domain experts that is sufficiently expressive to drive the configuration of signal processing functions will allow the expertise of signal processing experts to be captured in rules for automated configuration. In order to test the feasibility of this approach, we addressed a lightning classification problem, which was proposed by DOE as a surrogate for problems encountered in nuclear nonproliferation data processing. We coded a toolbox of low-level signal processing algorithms for extracting features of RF waveforms, and demonstrated a prototype tool for screening data. We showed examples of using the tool for expediting the generation of ground-truth metadata, for training a signal recognizer, and for searching for signals with particular characteristics. The public benefits of this approach, if successful, will accrue to Government and commercial activities that face the same general problem - the development of sensor systems for complex environments. It will enable problem domain experts (e.g. analysts) to construct signal and image processing chains without the aid of signal processing experts. Thus enabled, problem domain experts will be able to work more quickly and produce better quality work.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Strategic Plan for Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS)

The Nuclear Energy Computational Fluid Dynamics Advanced Modeling and Simulation (NE-CAMS) system is being developed at the Idaho National Laboratory (INL) in collaboration with Bettis Laboratory, Sandia National Laboratory (SNL), Argonne National Laboratory (ANL), Utah State University (USU), and other interested parties with the objective of developing and implementing a comprehensive and readily accessible data and information management system for computational fluid dynamics (CFD) verification and validation (V&V) in support of nuclear energy systems design and safety analysis. The two key objectives of the NE-CAMS effort are to identify, collect, assess, store and maintain high resolution and high quality experimental data and related expert knowledge (metadata) for use in CFD V&V assessments specific to the nuclear energy field and to establish a working relationship with the U.S. Nuclear Regulatory Commission (NRC) to develop a CFD V&V database, including benchmark cases, that addresses and supports the associated NRC regulations and policies on the use of CFD analysis. In particular, the NE-CAMS system will support the Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, which aims to develop and deploy advanced modeling and simulation methods and computational tools for reliable numerical simulation of nuclear reactor systems for design and safety analysis. Primary NE-CAMS Elements There are four primary elements of the NE-CAMS knowledge base designed to support computer modeling and simulation in the nuclear energy arena as listed below. Element 1. The database will contain experimental data that can be used for CFD validation that is relevant to nuclear reactor and plant processes, particularly those important to the nuclear industry and the NRC. Element 2. Qualification standards for data evaluation and classification will be incorporated and applied such that validation data sets will result in well-defined, well-characterized data. Element 3. Standards will be established for the design and operation of experiments for the generation of new validation data sets that are to be submitted to NE-CAMS that addresses the completeness and characterization of the dataset. Element 4. Standards will be developed for performing verification and validation (V&V) to establish confidence levels in CFD analyses of nuclear reactor processes; such processes will be acceptable and recognized by both CFD experts and the NRC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Greenhouse-Gas Information System: Monitoring and Validating Emissions Reporting and Mitigation

This study and report focus on attributes of a greenhouse-gas information system (GHGIS) needed to support MRV&V needs. These needs set the function of such a system apart from scientific/research monitoring of GHGs and carbon-cycle systems, and include (not exclusively): the need for a GHGIS that is operational, as required for decision-support; the need for a system that meets specifications derived from imposed requirements; the need for rigorous calibration, verification, and validation (CV&V) standards, processes, and records for all measurement and modeling/data-inversion data; the need to develop and adopt an uncertainty-quantification (UQ) regimen for all measurement and modeling data; and the requirement that GHGIS products can be subjected to third-party questioning and scientific scrutiny. This report examines and assesses presently available capabilities that could contribute to a future GHGIS. These capabilities include sensors and measurement technologies; data analysis and data uncertainty quantification (UQ) practices and methods; and model-based data-inversion practices, methods, and their associated UQ. The report further examines the need for traceable calibration, verification, and validation processes and attached metadata; differences between present science-/research-oriented needs and those that would be required for an operational GHGIS; the development, operation, and maintenance of a GHGIS missions-operations center (GMOC); and the complex systems engineering and integration that would be required to develop, operate, and evolve a future GHGIS.

54 ENVIRONMENTAL SCIENCES↗

A Greenhouse-Gas Information System: Monitoring and Validating Emissions Reporting and Mitigation

Current GHG-mitigating regimes, whether internationally agreed or self-imposed, rely on the aggregation of self-reported data, with limited checks for consistency and accuracy, for monitoring. As nations commit to more stringent GHG emissions-mitigation actions and as economic rewards or penalties are attached to emission levels, self-reported data will require independent confirmation that they are accurate and reliable, if they are to provide the basis for critical choices and actions that may be required. Supporting emissions-mitigation efforts and agreements, as well as monitoring energy- and fossil-fuel intensive national and global activities would be best achieved by a process of: (1) monitoring of emissions and emission-mitigation actions, based, in part, on, (2) (self-) reporting of pertinent bottom-up inventory data, (3) verification that reported data derive from and are consistent with agreed-upon processes and procedures, and (4) validation that reported emissions and emissions-mitigation action data are correct, based on independent measurements (top-down) derived from a suite of sensors in space, air, land, and, possibly, sea, used to deduce and attribute anthropogenic emissions. These data would be assessed and used to deduce and attribute measured GHG concentrations to anthropogenic emissions, attributed geographically and, to the extent possible, by economic sector. The validation element is needed to provide independent assurance that emissions are in accord with reported values, and should be considered as an important addition to the accepted MRV process, leading to a MRV&V process. This study and report focus on attributes of a greenhouse-gas information system (GHGIS) needed to support MRV&V needs. These needs set the function of such a system apart from scientific/research monitoring of GHGs and carbon-cycle systems, and include (not exclusively): the need for a GHGIS that is operational, as required for decision-support; the need for a system that meets specifications derived from imposed requirements; the need for rigorous calibration, verification, and validation (CV&V) standards, processes, and records for all measurement and modeling/data-inversion data; the need to develop and adopt an uncertainty-quantification (UQ) regimen for all measurement and modeling data; and the requirement that GHGIS products can be subjected to third-party questioning and scientific scrutiny. This report examines and assesses presently available capabilities that could contribute to a future GHGIS. These capabilities include sensors and measurement technologies; data analysis and data uncertainty quantification (UQ) practices and methods; and model-based data-inversion practices, methods, and their associated UQ. The report further examines the need for traceable calibration, verification, and validation processes and attached metadata; differences between present science-/research-oriented needs and those that would be required for an operational GHGIS; the development, operation, and maintenance of a GHGIS missions-operations center (GMOC); and the complex systems engineering and integration that would be required to develop, operate, and evolve a future GHGIS. Present monitoring systems would be heavily relied on in any GHGIS implementation at the outset and would likely continue to provide valuable future contributions to GHGIS. However, present monitoring systems were developed to serve science/research purposes. This study concludes that no component or capability presently available is at the level of technological maturity and readiness required for implementation in an operational GHGIS today. However, purpose-designed and -built components could be developed and implemented in support of a future GHGIS. The study concludes that it is possible to develop and provide a capability-driven prototype GHGIS, as part of a Phase-1 effort, within three years from project-funding start, that would make use of and integrate existing sensing and system capabilities. As part of a Phase-2 effort, a requirements-driven, operational GHGIS could be developed, within ten years from project funding start. That schedule is driven by the development and long lead-times for some system components. The two efforts would be focused on different deliverables but could commence concurrently, to save time, if that was deemed desirable. We note that, developing and supporting an operational GHGIS will require a new approach and management, sustained funding and other support, as well as technical advances and development of purpose-built components that meet the requisite specifications. A functioning GHGIS will provide the basis for reasoned choices on how best to respond to rising GHG levels, especially when proposed U.S. actions are compared with or conditioned on the actions of other nations.

54 ENVIRONMENTAL SCIENCES↗

Digitization Best Practices [Poster]

This project involved performing tests and documenting results to determine best practices for digitizing older print documents. The digitization process is complicated, especially when original documents exhibit non-standard fonts and are faded. Tests focused on solutions to improve high quality scanning, increase OCR accuracy, and efficiently use embedded metadata. Results are summarized. From the test results on the right sides, we know that when we plan to digitize documents, we should balance Quantity and Quality based on our expectation, and then make final decision for the digitization process.

99 GENERAL AND MISCELLANEOUS↗

SPE3 Far-field Quicklook

The purpose of this report is to provide an overview of the seismic data collected during the SPE3 chemical shot. Farfield seismic data includes data collected at distances of more than 100 m from the shot and instruments deployed for the experiments. This report does not address infrasound, remote sensing, or seismic data collected by regional permanent stations. The primary goal is a fast data check before extensive analysis. The SPE3 shot was conducted on July 24, 2012 (DOY 206) at the SPE test site and in the same borehole as SPE1 and SPE2 (table 1). Data processing at LLNL primarily used mini-­seed data volumes downloaded from the UNR server along with associated metadata. This is in contrast to earlier shots, where LLNL data was based on reformatted Reftek data. Sensor deployment was similar to previous shots, with a few changes. Parts of lines 1 (13, 14, 15, 16), 3 (23,26,36), and 5 (1-­12) were recorded by telemetry as well as to disk, which provided immediate access to the data. A small array (6 station) geophone array was deployed southeast of the shot near AF9 to measure particle motions. A new rotational sensor (ATA ARS-­16) was deployed at station L3-­20.

58 GEOSCIENCES↗

Analyzing and visualizing next generation climate data (Final Report)

The project "Analyzing and visualizing next generation climate data" adds block-structured (mosaic) grid support, parallel processing, and 2D/3D curvilinear interpolation to the open-source UV-CDAT climate data analysis tool. Block structured grid support complies to the Gridspec extension submitted to the Climate and Forecast metadata conventions. It contains two parts: aggregation of data spread over multiple mosaic tiles (M-SPEC) and aggregation of temporal data stored in different files (F-SPEC). Together, M-SPEC and F-SPEC allow users to interact with data stored in multiple files as if the data were in a single file. For computational expensive tasks, a flexible, multi-dimensional, multi-type distributed array class allows users to process data in parallel using remote memory access. Both nodal and cell based interpolation is supported; users can choose between different interpolation libraries including ESMF and LibCF depending on the their particular needs.

54 ENVIRONMENTAL SCIENCES↗

EPICS Version 4 - Implementing Complex Data Types

Through phase 1 and phase 2 SBIR grants, s fully functional I/O Controller and communication protocol for version 4 of EPICS is completed. This new software architecture provides a flexible and extendible architecture. Version 4 is implemented fully in Java. The performance metrics look promising. The final portion of phase 2 is to optimize the communication mechanisms. Subsequent work on different aspects of this are required to provide a viable solutions in various areas. Version 3 of EPICS is able to provide a platform for implementing channel based control, because the channel and attributes for time stamping, alarm, display and control were narrow, well defined, and complete. To extend EPICS functionality beyond this, it is necessary to define attributes needed for archive data, array, image data, and directory services. The proper handling of several array types enables the development of middle layer servers such as orbit and bump control in accelerators. Phase 1 should produce a well defined, reviewed, and agreed upon definition of the metadata required for these services. A Phase 2 grant would provide tools that implemented archiving, general array, imaging, and directory applications.

43 PARTICLE ACCELERATORS↗