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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Plans for the extreme ultraviolet explorer data base

The paper presents an approach for storage and fast access to data that will be obtained by the Extreme Ultraviolet Explorer (EUVE), a satellite payload scheduled for launch in 1991. The EUVE telescopes will be operated remotely from the EUVE Science Operation Center (SOC) located at the University of California, Berkeley. The EUVE science payload consists of three scanning telescope carrying out an all-sky survey in the 80-800 A spectral region and a Deep Survey/Spectrometer telescope performing a deep survey in the 80-250 A spectral region. Guest Observers will remotely access the EUVE spectrometer database at the SOC. The EUVE database will consist of about 2 X 10 to the 10th bytes of information in a very compact form, very similar to the raw telemetry data. A history file will be built concurrently giving telescope parameters, command history, attitude summaries, engineering summaries, anomalous events, and ephemeris summaries.

Marshall, Herman L.↗
NASA NTRS1995

Interactive data exploration and particle tracking for general circulation models

The SCENE environment for interactive visualization of complex data sets is discussed. This environment is used to create tools for graphical exploration of atmospheric flow models. These tools may be extended by the user in a seamless manner, so that no programming is required. A module for accurately tracing field lines and particle trajectories in SCENE is presented. This is used to examine the flowfield qualitatively with streamlines and pathlines and to identify critical points in the velocity field. The paper also describes a visualization tool for general circulation models on which the primary features of the environment are demonstrated.

Rosenbaum, R. I.↗
DOE OSTI2022

High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration

Abstract With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs) for electronic, optoelectronic, and energy storage applications, we present a dataset of predicted electronic structure properties for thousands of MOFs carried out using multiple density functional approximations. Compared to more accurate hybrid functionals, we find that the widely used PBE generalized gradient approximation (GGA) functional severely underpredicts MOF band gaps in a largely systematic manner for semi-conductors and insulators without magnetic character. However, an even larger and less predictable disparity in the band gap prediction is present for MOFs with open-shell 3 d transition metal cations. With regards to partial atomic charges, we find that different density functional approximations predict similar charges overall, although hybrid functionals tend to shift electron density away from the metal centers and onto the ligand environments compared to the GGA point of reference. Much more significant differences in partial atomic charges are observed when comparing different charge partitioning schemes. We conclude by using the dataset of computed MOF properties to train machine-learning models that can rapidly predict MOF band gaps for all four density functional approximations considered in this work, paving the way for future high-throughput screening studies. To encourage exploration and reuse of the theoretical calculations presented in this work, the curated data is made publicly available via an interactive and user-friendly web application on the Materials Project.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Data-Intensive Science meets Inquiry-Driven Pedagogy: Interactive Big Data Exploration, Threshold Concepts, and Liminality

Threshold concepts in any discipline are the core concepts an individual must understand in order to master a discipline. By their very nature, these concepts are troublesome, irreversible, integrative, bounded, discursive, and reconstitutive. Although grasping threshold concepts can be extremely challenging for each learner as s/he moves through stages of cognitive development relative to a given discipline, the learner's grasp of these concepts determines the extent to which s/he is prepared to work competently and creatively within the field itself. The movement of individuals from a state of ignorance of these core concepts to one of mastery occurs not along a linear path but in iterative cycles of knowledge creation and adjustment in liminal spaces - conceptual spaces through which learners move from the vaguest awareness of concepts to mastery, accompanied by understanding of their relevance, connectivity, and usefulness relative to questions and constructs in a given discipline. For example, challenges in the teaching and learning of atmospheric science can be traced to threshold concepts in fluid dynamics. In particular, Dynamic Meteorology is one of the most challenging courses for graduate students and undergraduates majoring in Atmospheric Science. Dynamic Meteorology introduces threshold concepts - those that prove troublesome for the majority of students but that are essential, associated with fundamental relationships between forces and motion in the atmosphere and requiring the application of basic classical statics, dynamics, and thermodynamic principles to the three dimensionally varying atmospheric structure. With the explosive growth of data available in atmospheric science, driven largely by satellite Earth observations and high-resolution numerical simulations, paradigms such as that of dataintensive science have emerged. These paradigm shifts are based on the growing realization that current infrastructure, tools and processes will not allow us to analyze and fully utilize the complex and voluminous data that is being gathered. In this emerging paradigm, the scientific discovery process is driven by knowledge extracted from large volumes of data. In this presentation, we contend that this paradigm naturally lends to inquiry-driven pedagogy where knowledge is discovered through inductive engagement with large volumes of data rather than reached through traditional, deductive, hypothesis-driven analyses. In particular, data-intensive techniques married with an inductive methodology allow for exploration on a scale that is not possible in the traditional classroom with its typical problem sets and static, limited data samples. In addition, we identify existing gaps and possible solutions for addressing the infrastructure and tools as well as a pedagogical framework through which to implement this inductive approach.

Ramachandran, Rahul↗
NASA NTRS2017

VISAGE Visualization for Integrated Satellite, Airborne and Ground-Based Data Exploration

The primary goal of the VISAGE project is to facilitate more efficient Earth Science investigations via a tool that can provide visualization and analytic capabilities for diverse coincident datasets. This proof-of-concept project will be centered around the GPM Ground Validation program, which provides a valuable source of intensive, coincident observations of atmospheric phenomena. The data are from a wide variety of ground-based, airborne and satellite instruments, with a wide diversity in spatial and temporal scales, variables, and formats, which makes these data difficult to use together. VISAGE will focus on "golden cases" where most ground instruments were in operation and multiple research aircraft sampled a significant weather event, ideally while the GPM Core Observatory passed overhead. The resulting tools will support physical process studies as well as satellite and model validation.

Data fusion↗
DOE OSTI2025

Exploring Data Set Bias and Decision Support with Predictive Uncertainty Through Bayesian Approximations and Convolutional Neural Networks

Individual seismic catalogs can contain multiscale observations from fault level to global scales and associated waveforms from discrete events reflect crustal structure across many different scales and locations. Seismic network aperture, geographic location, and observation distance may not provide informative guidance or intuition on how different catalogs will behave across models trained under different conditions. We rely on uncertainty to provide guardrails for when to trust model decisions, but understanding when our uncertainty is trustworthy is an open challenge. Here, in this work, we explore Bayesian approximation methods for assigning predictive uncertainty in seismic event classification problems. We find that computationally expensive Bayesian approximations do not outperform simple ensemble methods. We also find that when exploiting multiple seismic event catalogs, joint training with data from all the catalogs combined with Bayesian approximations and supervised training for classification can obscure bias and result in less robust uncertainty while also not providing substantial performance benefits compared to training individual models for each catalog.

58 GEOSCIENCES↗
NASA NTRS1988

Dynamics explorer data analysis

The project has shown unambiguously that auroral acceleration is caused by electric fields aligned parallel to the Earth's magnetic field. Evidence was shown of significant ion heating as ions are accelerated upwards in auroral electric fields. This heating is most likely caused by the two-stream instability. The fate of upward ion beams associated with auroral arcs is shown; they appear in the opposite hemisphere as dispersive ion precipitation events. Magnetic merging of the Interplanetary Magnetic Field occurs with both closed dayside magnetospheric field lines and open tail lobe field lines simultaneously nearly 30 percent of the time. The sunward flow in the dawnside plasma sheet is 20 percent smaller, on average, than in the duskside. The convection throat is displaced slightly more toward dawn for B sub y greater than 0 than for B sub y less than 0.

Reiff, Patricia H.↗
NASA NTRS1993

Dynamics explorer data analysis

Work in the following areas is discussed: plasma physics of the auroral acceleration region; electrodynamic coupling as a function of substorm phase and interplanetary magnetic field (IMF) direction; and particle injection in the magnetospheric cusp.

Reiff, Patricia H.↗