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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A 15-Year Retrospective on Immersive Visualization Lessons from the Applied Visualization Laboratory

This article shares the experiences of operating an immersive visualization laboratory over a 15-year period. The paper discusses valuable insights into the lessons learned from various projects, including the challenges they faced, such as technical difficulties, user adoption, and opportunities, and practical solutions for overcoming them. One crucial element for successful immersive visualization projects is interdisciplinary collaboration. The paper presents the advantages of immersive visualization technology, such as improved data comprehension, enhanced communication, and increased engagement in complex scenarios. We present the dynamic realm of virtual and augmented truth (VR/AR) technology in the context of a immersive laboratory system. We spotlight rising trends inside the integration of VR/AR tools for visualization. We also present our experience in dealing with the hardware and software additives in an immersive VR/AR labs, dropping light on the demanding situations and successes encountered throughout everyday operations. Furthermore, it offers practical knowledge and guidance based on years of experience in the field, which can help you overcome challenges and achieve success in your project.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

SciDAC Institute for Ultra-Scale Visualization: Activity Recognition for Ultra-Scale Visualization

Understanding the science behind ultra-scale simulations requires extracting meaning from data sets of hundreds of terabytes or more. Developing scalable parallel visualization algorithms is a key step enabling scientists to interact and visualize their data at this scale. However, at extreme scales, the datasets are so huge, there is not even enough time to view the data, let alone explore it with basic visualization methods. Automated tools are necessary for knowledge discovery -- to help sift through the information and isolate characteristic patterns, thereby enabling the scientist to study local interactions, the origin of features and their evolution in large volumes of data. These tools must be able to operate on data of this scale and work with the visualization process. In this project, we developed a framework for activity detection to allow scientists to model and extract spatio-temporal patterns from time-varying data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A High-Speed, Real-Time Visualization and State Estimation Platform for Monitoring and Control of Electric Distribution Systems: Implementation and Field Results

Continued deployment of renewable and distributed energy resources is fundamentally changing the way that electric distribution systems are controlled and operated; more sophisticated active system control and greater situational awareness are needed. Real-time measurements and distribution system state estimation (DSSE) techniques enable more sophisticated system control and, when combined with visualization applications, greater situational awareness. This paper presents a novel demonstration of a high-speed, real-time DSSE platform and related control and visualization functionalities, implemented using existing open-source software and distribution system monitoring hardware. Live scrolling strip charts of meter data and intuitive annotated map visualizations of the entire state (obtained via DSSE) of a real-world distribution circuit are shown. The DSSE implementation is validated to demonstrate provision of accurate voltage data. This platform allows for enhanced control and situational awareness using only a minimum quantity of distribution system measurement units and modest data and software infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

NeRVI: Compressive neural representation of visualization images for communicating volume visualization results

We present NeRVI, a new deep-learning approach that compresses a large collection of visualization images generated from time-varying data for communicating volume visualization results. Based on an image-based implicit neural representation, our approach represents tens of thousands of high-resolution rendering images parametrized by different parameters via a hybrid model of multilayer perceptrons and convolutional neural networks. Here, our model predicts images and corresponding masks, and the masks are utilized for loss computation and network training to capture fine structural details and small components. In conjunction with model quantization and weight encoding, NeRVI yields highly compact compressive neural representations while preserving the image fidelity well. We demonstrate the effectiveness of NeRVI with isosurface rendering and direct volume rendering images generated from multiple data sets and compare NeRVI with other state-of-the-art deep learning-based (InSituNet, SIREN, NeRF, and NeRV) methods. Quantitative and qualitative results show that NeRVI provides an alternative solution that augments domain scientists' ability to manage, represent, and communicate scientific visualization output.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization

In topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse–Smale complexes play an essential role in capturing the shape of scalar field data. Herein we present a state–of–the–art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time–varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Ergodic theory and visualization. II. Fourier mesochronic plots visualize (quasi)periodic sets

We present an application and analysis of a visualization method for measure-preserving dynamical systems introduced by I. Mezić and A. Banaszuk [Physica D 197, 101 (2004)], based on frequency analysis and Koopman operator theory. This extends our earlier work on visualization of ergodic partition [Z. Levnajić and I. Mezić, Chaos 20, 033114 (2010)]. Our method employs the concept of Fourier time average [I. Mezić and A. Banaszuk, Physica D 197, 101 (2004)], and is realized as a computational algorithms for visualization of periodic and quasi-periodic sets in the phase space. The complement of periodic phase space partition contains chaotic zone, and we show how to identify it. The range of method's applicability is illustrated using well-known Chirikov standard map, while its potential in illuminating higher-dimensional dynamics is presented by studying the Froeschlé map and the Extended Standard Map.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Visualizing the Connections in the EXFOR Database

The EXFOR database contains many datasets (over 6160) in which the measured values are reaction combinations, which means that they are not an absolute measurement of an experimental quantity. Rather, they are ratios of quantities, sums of quantities, or some other mathematical relation of experimental quantities. These reaction combinations couple large numbers of data sets together in non-trivial ways. Here a visualization is presented of the coupled data used to derive cross material covariances for the COMMARA-3 library. Links are provided to other larger visualizations on the NNDC website.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Interactive visualization of multi-data-set Rietveld analyses using Cinema:Debye-Scherrer [nteractive Visualization of Multi-Dataset Rietveld Analyses using Cinema:Debye-Scherrer]

A tool named Cinema:Debye-Scherrer to visualize the results of a series of Rietveld analyses is presented. The multi-axis visualization of the high-dimensional data sets resulting from powder diffraction analyses allows identification of analysis problems, prediction of suitable starting values, identification of gaps in the experimental parameter space and acceleration of scientific insight from the experimental data. The tool is demonstrated with analysis results from 59 U–Nb alloy samples with different compositions, annealing times and annealing temperatures as well as with a high-temperature study of the crystal structure of CsPbBr 3 . A script to extract parameters from a series of Rietveld analyses employing the widely used GSAS Rietveld software is also described. Finally, both software tools are available for download.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Direct Visualization of Li Dendrite Effect on LiCoO 2 Cathode by In Situ TEM

Li dendrites are known to cause deterious, and in many cases catastrophic, effect on the performance of Li rechargeable batteries. However, the mechanistic failure mechanism of cathodes upon in contact with Li metal is far from clear. In this study, using in situ transmission electron microscopy, we directly visualize at an atomic scale the interaction of Li dendrites with well-defined, epitaxial thin films of LiCoO2, the most widely used cathode material. We show that a spontaneous and prompt chemical reaction is trigged once the Li contact is made, leading to expansion and amorphization of the LiCoO2 structure, with Li2O and Co metal being the final reaction products. A topotactic phase transition is identified close to the reaction front, resulting in the formation of CoO as a metastable intermediate. Dynamic structural and chemical imaging in combination with ab inito simulations reveal that a high density of antiphase grain boundaries are formed at the reaction front, which are critical for enabling the short-range topotactic reactions and long-range Li propagation. The fundamental insights are of general importance in mitigating Li dendrites related issues and guiding the design principle for more robust energy materials.

In situ transmission electron microscopy (TEM), Li↗
DOE OSTI2025

Cryo-EM Visualization of Intermolecular π-Electron Interactions within π-Conjugated Peptidic Supramolecular Polymers

The self-assembly of “π-peptides” – molecules with π-electron cores substituted with two or more oligopeptide chains – brings organic electronic function into biologically relevant nanomaterials. π-Peptides assemble into fibrillar nanomaterials as driven by enthalpic peptide-based hydrogen bonding networks and pi-core-based quadrupolar interactions. A large body of spectroscopic, morphological and computational studies informs on the nature of the self-assembly process and the resulting nanostructures, but detailed structural information has remained elusive. Here, inspired by the recent use of cryogenic electron microscopy (cryo-EM) to provide high-resolution structures for synthetic peptide nanomaterials, we present here the use of cryo-EM to offer ca. 3 Å resolution of π-peptide nanomaterial assemblies, visualizing for the first time the nature of the intermolecular π-core electronic interactions responsible for energy transport through these supramolecular materials.

Group theory↗
DOE OSTI2015

Direct Visualization of Catalytically Active Sites at the FeO-Pt(111) Interface

Within the area of surface science, one of the “holy grails” is to directly visualize a chemical reaction at the atomic scale. Whereas this goal has been reached by high-resolution scanning tunneling microscopy (STM) in a number of cases for reactions occurring at flat surfaces, such a direct view is often inhibited for reaction occurring at steps and interfaces. Here we have studied the CO oxidation reaction at the interface between ultrathin FeO islands and a Pt(111) support by in situ STM and density functional theory (DFT) calculations. Time-lapsed STM imaging on this inverse model catalyst in O2 and CO environments revealed catalytic activity occurring at the FeO-Pt(111) interface and directly showed that the Fe-edges host the catalytically most active sites for the CO oxidation reaction. This is an important result since previous evidence for the catalytic activity of the FeO-Pt(111) interface is essentially based on averaging techniques in conjunction with DFT calculations. The presented STM results are in accord with DFTþU calculations, in which we compare possible CO oxidation pathways on oxidized Fe-edges and O-edges. We found that the CO oxidation reaction is more favorable on the oxidized Fe-edges, both thermodynamically and kinetically.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Xi-cam : a versatile interface for data visualization and analysis

Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam 's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam 's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.

Pandolfi, Ronald J. (ORCID:0000000308248548)↗
DOE OSTI2018

A visual wikipedia for satellite imagery

GeoVisipedia (Geospatial Visual Wikipedia) is a new and novel approach to sharing knowledge about complex geospatial entities such as facilities. Facilities are composed of interconnected objects such as buildings, chemical processing units, electrical generation equipment and similar structures. Satellite imagery of a facility reveals a great deal about the organization and visual appearance of objects in a facility, but very little about the identity or function of the object. For example, given a satellite imagery of an oil refinery, an expert in refining readily identifies distillation units and can explain how they work. A non-expert would have a very difficult time identifying these objects let alone explaining how they function. To make highly complex information accessible to non-experts, GeoVisipedia associates a wiki page with objects in satellite imagery. A user selects an object in the image and a wiki page appears that provides the user with detailed information about the object. Experts can author information into the wiki and this information is shared with other users. Additionally, GeoVisipedia automatically transfers all wiki pages from one image of a facility to other imagery of the facility. Consequentially, knowledge about objects in the facility integrates over time as new imagery becomes available and as new wiki pages are created and additional information is added to existing wiki pages. In this respect, satellite imagery becomes a portal to expert knowledge and insight about objects in a facility.

Roberts, Randy↗