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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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DOE OSTI2021

Abell 1430: A merging cluster with exceptional diffuse radio emission

Diffuse radio emission has been found in many galaxy clusters, predominantly in massive systems which are in the state of merging. The radio emission can usually be classified as relic or halo emission, which are believed to be related to merger shocks or volume-filling turbulence, respectively. Recent observations have revealed radio bridges for some pairs of very close galaxy clusters. The mechanisms that may allow one to explain the high specific density of relativistic electrons, which are necessary to explain the radio luminosity of these bridge regions, have been poorly explored until now. When inspecting the first data release of the LOFAR Two-Metre Sky Survey (LoTSS), we discovered diffuse radio emission in the galaxy cluster Abell 1430. Here, for this work, we aim to determine the dynamical state of the cluster and characterise the diffuse radio emission. We analysed the LoTSS data in detail and complemented them with recent Karl G. Jansky Very Large Array observations in the L-band. To study the dynamical state of the cluster, we analysed XMM-Newton data, Chandra data, and Sloan Digital Sky Survey data. Moreover, we compared our results to clusters extracted from THE THREE HUNDRED PROJECT cosmological simulation. We find that Abell 1430 consists of two components, namely A1430-A and A1430-B, with a mass ratio of about 2:1. The massive component shows diffuse radio emission which can be classified as radio halo which shows a low radio power at 1.4 GHz with respect to the mass of the cluster. Most interestingly, there is extended diffuse radio emission in the following dubbed as the ‘Pillow’ according to its morphology, which is apparently related to A1430-B and which is neither typical halo nor typical relic emission. The origin of this emission is puzzling. We speculate that the two components of Abell 1430 undergo an off-axis merger. In this scenario, A1430-B is moving towards the main cluster component and may have compressed and stirred the medium in the filament between the two cluster components. We have discovered evidence for diffuse radio emission related to the low-density intracluster or intergalactic medium in Abell 1430. To date, only a few examples of emission originating from such regions are known. These discoveries are crucial to constrain possible acceleration mechanisms which may allow us to explain the presence of relativistic electrons in these regions. In particular, our results indicate a spectral index of α 144 MHz 1.5 GHz = -1.4±0.5 for the Pillow. If upcoming observations confirm a slope as flat as -1.4 or even flatter, this would pose a challenge for the electron acceleration scenarios.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

The research data alliance photon and neutron science interest group

Scientific research data provides unique challenges that are distinct from classic “Big Data” sources. One common element in research data is that the experiment, observations, or simulation were designed, and data were specifically acquired, to shed light on an open scientific question. The data and methods are usually “owned” by the researcher(s) and the data itself might not be viewed to have long-term scientific significance after the results have been published. Often, the data volume was relatively low, with data sometimes easier to reproduce than to catalog and store. Some data and meta-data were not collected in a digital form, or were stored on antiquated or obsolete media. Generally speaking, policies, tools, and management of digital research data have reflected an ad hoc approach that varies domain by domain and research group by research group. This model, which treats research data as disposable, is proving to be a serious limitation as the volume and complexity of research data explodes. Changes are required at every level of scientific research: within the individual groups, and across scientific domains and interdisciplinary collaborations. Enabling researchers to learn about available tools, processes, and procedures should encourage a spirit of cooperation and collaboration, allowing researchers to come together for the common good. In conclusion, these community-oriented efforts provide the potential for targeted projects with high impact.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Enhancing the Impact of Science Data: Toward Data Discovery and Reuse

The amount of data produced in support of scientific research continues to grow rapidly. Despite the accumulation and demand for scientific data, relatively little data are actually made available for the broader scientific community. We surmise that one root of this problem is the perceived difficulty of electronically publishing scientific data and associated metadata in a way that makes it discoverable. We propose exploiting Semantic Web technologies and best practices to make metadata both discoverable and easy to publish. We share experiences in curating metadata to illustrate the cumbersome nature of data reuse in the current research environment. We also make recommendations with a real-world example of how data publishers can provide their metadata by adding limited additional markup to HTML pages on the Web. With little additional effort from data publishers, the difficulty of data discovery, access, and sharing can be greatly reduced and the impact of research data greatly enhanced.

Data Curation↗
DOE OSTI2023

The Eighteenth Data Release of the Sloan Digital Sky Surveys: Targeting and First Spectra from SDSS-V

The eighteenth data release (DR18) of the Sloan Digital Sky Survey (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs or “Mappers”: the Milky Way Mapper (MWM), the Black Hole Mapper (BHM), and the Local Volume Mapper. This data release contains extensive targeting information for the two multiobject spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration and scientifically focused components. DR18 also includes ~25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Sloan Digital Sky Survey Quasar Catalog: Sixteenth Data Release

We present the final Sloan Digital Sky Survey IV (SDSS-IV) quasar catalog from Data Release 16 of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). This catalog comprises the largest selection of spectroscopically confirmed quasars to date. The full catalog includes two subcatalogs (the current versions are DR16Q_v4 and DR16Q_Superset_v3 at https://data.sdss.org/sas/dr16/eboss/qso/DR16Q/): a "superset" of all SDSS-IV/eBOSS objects targeted as quasars containing 1,440,615 observations and a quasar-only catalog containing 750,414 quasars, including 225,082 new quasars appearing in an SDSS data release for the first time, as well as known quasars from SDSS-I/II/III. We present automated identification and redshift information for these quasars alongside data from visual inspections for 320,161 spectra. Here, the quasar-only catalog is estimated to be 99.8% complete with 0.3%-1.3% contamination. Automated and visual inspection redshifts are supplemented by redshifts derived via principal component analysis and emission lines. We include emission-line redshifts for Hα, Hβ, Mg II, C III], C IV, and Lyα. Identification and key characteristics generated by automated algorithms are presented for 99,856 broad absorption-line quasars and 35,686 damped Lyman alpha quasars. In addition to SDSS photometric data, we also present multiwavelength data for quasars from the Galaxy Evolution Explorer, UKIDSS, the Wide-field Infrared Survey Explorer, FIRST, ROSAT/2RXS, XMM-Newton, and Gaia. Calibrated digital optical spectra for these quasars can be obtained from the SDSS Science Archive Server.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Throughput Estimation of Data Transport Networks From Digital Twin Measurements

Digital twins of networked infrastructures, known as Virtual Infrastructure Twins (VITs), are increasingly used for software development, pre-deployment testing, and design space exploration. While VITs avoid the costs and potential disruptions associated with experiments on operational networks, their throughput measurements are typically not sufficiently accurate for performance profiling of wide-area networks that they emulate. Here, machine learning (ML) methods are developed to transform these inaccurate VIT network throughput measurements to closely match in peak and overall profile of those from a physical testbed or production network. First, a micro kernel network reflecting a physical network is utilized to collect one-time measurements on a host to support this ML transformation. Then, a generic multi-modal ML method is developed to learn a map that transforms measurements from subsequent VITs on the same host to match past, current and follow-on testbed and cloud networks. ML generalization equations are derived to establish its correctness and probabilistically guarantee its generalization accuracy. Experimental results are presented for a variety of VIT hosts with target testbed and cloud networks; they include a case study of a four-site science ecosystem wherein inaccurate convex VIT measurement profiles are transformed into accurate concave profiles of target networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

UCNB_Analyzer

The purpose of this software is to interpret and analyze data taken using the NI PXIe-5171R digitizer based data acquisition system for the UCNB and Nab experiments. The detection and data acquisition systems are identical for the 2 experiments, with some differences in analysis requirements. The software converts raw binary files produced by the NI DAQ into ROOT TTree format, performs waveform analysis using trapezoidal filter algorithms, pulse fitting, and noise analysis routines, and applies variable criteria to identify valid events in the data stream. The software will be used to perform analysis of the events for multi-channel coincidences, timing and energy studies, and event rates under different experimental conditions.

Broussard, LeahJ↗
DOE OSTI2016

Public Data Set: On Virial Analysis at Low Aspect Ratio

This public data set contains openly-documented, machine readable digital research data published in M.W. Bongard, et al., 'On Virial Analysis at Low Aspect Ratio,' Phys. Plasmas 23, 072508 (2016).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Public Data Set: Erratum: "Multi-point, high-speed passive ion velocity distribution diagnostic on the Pegasus Toroidal Experiment" [Rev. Sci. Instrum. 83, 10D516 (2012)]

This data set contains openly-documented, machine readable digital research data corresponding to figures published in M.G. Burke et al., 'Erratum: "Multi-point, high-speed passive ion velocity distribution diagnostic on the Pegasus Toroidal Experiment" [Rev. Sci. Instrum. 83, 10D516 (2012)],' Rev. Sci. Instrum. 87, 079902 (2016).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗