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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Toward a Smart Metaverse City: Immersive Realism and 3D Visualization of Digital Twin Cities

Metaverse and its related extended reality technologies can enable immersive, realistic, and participatory visualization of 3D data, and their use and the potential within a smart city can be effective for supporting urban research and urban operations management. This book chapter describes a vision for prototyping a “Smart Metaverse City” to combine the unique advantage of the Metaverse technology with the two-way connectivity of a digital twin city application. This synergy aims to create a virtual environment for immersive geovisualization to help researchers and the public understand the complex urban system through science-based and data-driven approaches. This book chapter selectively reviews past technological and paradigm advancements for collecting, analyzing, and visualizing 3D urban big data. Then we present a prototyping Geographic Information System (GIS) framework, together with some relevant data sources and open-source web technologies, to help researchers create a smart Metaverse city. We demonstrate our vision and discuss its application opportunities through a real-world example, a digital twin city developed at the Oak Ridge National Laboratory, to facilitate participatory, smart, and sustainable campus management.

Xu, Haowen↗
DOE OSTI2025

Advanced Interactive 3D Visualization Tool for Customizable Analyses of Tomography Datasets in Material Science

Current methods for visualizing and analyzing 3D tomography datasets in materials science often lack the interactivity and depth required for detailed structural insights. This limitation restricts a researchers' ability to accurately interpret complex data, which is critical for advancing material innovations and understanding structural properties. To address this issue, we have developed a novel, web-based interactive 3D visualization and analysis tool from the Trame framework that offers customizable features to enhance data interpretability. The tool allows users to adjust parameters such as visible range, slice planes, data rotation, and layering, providing a more detailed and dynamic view of complex structures. Its user-friendly web interface increases the accessibility and ease of use for both novice and experienced researchers, to visualize large volumetric datasets. The tool supports a diverse range of data formats, making it versatile for various research applications. Unique capabilities include real-time data manipulation, automated feature detection, context-sensitive feedback, and real-time volume calculations and distributions per sliced region or layer, alongside the ability to quickly generate high-quality screenshots and videos for presentations and reports. These advancements offer a comprehensive solution for enhanced 3D data exploration, significantly improving the analysis process and communication of results in materials science.

36 - MATERIALS SCIENCE↗
DOE OSTI2021

Tracking the evolution of processes occurring in silicon anodes in lithium ion batteries by 3D visualization of relaxation times

An unconventional electroanalytical method has been used for tracking processes in silicon anodes in lithium ion batteries: a 3D visualization of relaxation times. Impedance data of the electrodes were collected at different potentials and different cycles during cyclic voltammetry, and were treated by means of the Distribution of Relaxation Times (DRT) method. A 3D visualization of the results allowed to identify the formation of a solid electrolyte interphase on the anode, composed of two layers with different relaxation times. Such findings are not possible by conventional analysis of impedance data by modeling with equivalent circuits, nor by simple DRT alone. Additionally, it was possible to observe that the characteristic relaxation time of the lithiation of the Si anode becomes smaller upon cycling, indicating that the material experiences structural transformations that allow it to lithiate faster. The result is relevant to motivate the use of micron-sized particles in the anode.

25 ENERGY STORAGE↗
DOE OSTI2021

Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures

Abstract Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.

Sehnal, David↗
DOE OSTI2015

A Real-Time Magnetoencephalography Brain-Computer Interface Using Interactive 3D Visualization and the Hadoop Ecosystem

Ecumenically, the fastest growing segment of Big Data is human biology-related data and the annual data creation is on the order of zetabytes. The implications are global across industries, of which the treatment of brain related illnesses and trauma could see the most significant and immediate effects. The next generation of health care IT and sensory devices are acquiring and storing massive amounts of patient related data. An innovative Brain-Computer Interface (BCI) for interactive 3D visualization is presented utilizing the Hadoop Ecosystem for data analysis and storage. The BCI is an implementation of Bayesian factor analysis algorithms that can distinguish distinct thought actions using magneto encephalographic (MEG) brain signals. We have collected data on five subjects yielding 90% positive performance in MEG mid- and post-movement activity. We describe a driver that substitutes the actions of the BCI as mouse button presses for real-time use in visual simulations. This process has been added into a flight visualization demonstration. By thinking left or right, the user experiences the aircraft turning in the chosen direction. The driver components of the BCI can be compiled into any software and substitute a user’s intent for specific keyboard strikes or mouse button presses. The BCI’s data analytics OPEN ACCESS Brain. Sci. 2015, 5 420 of a subject’s MEG brainwaves and flight visualization performance are stored and analyzed using the Hadoop Ecosystem as a quick retrieval data warehouse.

McClay, Wilbert↗
DOE OSTI2023

3D Visualization of Proteins within Metal–Organic Frameworks via Ferritin‐Enabled Electron Microscopy

Abstract Electron tomography holds great promise as a tool for investigating the 3D morphologies and internal structures of metal‐organic framework‐based protein biocomposites (protein@MOFs). Understanding the 3D spatial arrangement of proteins within protein@MOFs is paramount for developing synthetic methods to control their spatial localization and distribution patterns within the biocomposite crystals. In this study, the naturally occurring iron oxide mineral core of the protein horse spleen ferritin (Fn) is leveraged as a contrast agent to directly observe individual proteins once encapsulated into MOFs by electron microscopy techniques. This methodology couples scanning electron microscopy, transmission electron microscopy, and electron tomography to garner detailed 2D and 3D structural interpretations of where proteins spatially lie in Fn@MOF crystals, addressing the significant gaps in understanding how synthetic conditions relate to overall protein spatial localization and aggregation. These findings collectively reveal that adjusting the ligand‐to‐metal ratios, protein concentration, and the use of denaturing agents alters how proteins are arranged, localized, and aggregated within MOF crystals.

Chemistry↗
DOE OSTI2016

Using Python For 3D Visualizations of MCNP output

MCNP is ubiquitously used within industries, universities and national laboratories as a tool for accurately modeling radiation. With so much focus on the details of transport, attention is seldom given to the visualizations of these meticulously constructed outputs. Python is a programing language designed to promote code readability and has steadily grown in popularity since the 1990's. Python is also a heavily crowd-sourced programing language which generally means that the problems that you are trying to solve with computer codes are already solved; The user is often left with the now-simplified task of cobbling together a good and useful compilation of these tools and adapting them to solve the problem at hand. I have taken advantage of this situation and constructed some visualization tools in python that can be used to duplicate some of the 2D radiation fields that MCNP produces and also produce a meaningful 3D representation of a radiation field. (author)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Neutron-Friendly Li-Ion Battery Coin Cell for In Situ 3D Visualization of Li Plating

Advanced battery characterization using in situ/operando neutron imaging is critical for uncovering degradation modes such as lithium (Li) plating in Li-ion batteries (LIBs). However, conventional LIBs hinder operando neutron radiography (NR) and in situ neutron micro-computed tomography (N-μCT) for visualizing Li plating near the graphite-separator interface due to strong attenuation from hydrogen-rich components like PP–PE–PP separators, electrolyte, and Fe-based spacers. In this work, we designed and tested a neutron-friendly battery (NFB) optimized for in situ Li detection during extreme fast charging (XFC). Guided by neutron attenuation cross-sections and material transmission, the NFB enables clear visualization at the graphite–separator interface, which is typically opaque in standard LIBs. Electrochemical tests show the NFB exhibits voltage/current responses like standard cells for up to 50 XFC cycles. However, its lower reversibility and capacity are likely due to Cu-coated Al spacer degradation from delamination or corrosion. We propose titanium spacers as a more stable alternative, albeit requiring custom machining. Using this optimized cell, we achieved simultaneous neutron tomography of multiple cells, capturing in situ 3D images of dead Li accumulation, particularly near graphite edges. These heterogeneous deposits and disconnected Li clusters suggest localized current density hotspots during XFC.

25 ENERGY STORAGE↗
DOE OSTI2017

In-situ 3D visualization of composite microstructure during polymer-to-ceramic conversion

One route for producing fiber-reinforced ceramic-matrix composites entails repeated impregnation and pyrolysis of a preceramic polymer in a fiber preform. The process relies crucially on the development of networks of contiguous cracks during pyrolysis, thereby allowing further impregnation to attain nearly-full densification. The present study employs in-situ x-ray computed tomography (XCT) to reveal in three dimensions the evolution of matrix structure during pyrolysis of a SiC-based preceramic polymer to 1200 °C. Observations are used to guide the development of a taxonomy of crack geometries and crack structures and to identify the temporal sequence of their formation. A quantitative analysis is employed to characterize effects of local microstructural dimensions on the conditions required to form cracks of various types. Complementary measurements of gas evolution and mass loss of the preceramic polymer during pyrolysis as well as changes in mass density and Young's modulus provide context for the physical changes revealed by XCT. Furthermore, the findings provide a foundation for future development of physics-based models to guide composite fabrication processes.

36 MATERIALS SCIENCE↗
DOE OSTI2017

3D Geometry Visualization Capability for MCNP

The purpose of this white paper is to demonstrate the need for a 3D visualizer and graphical user interface for the Monte Carlo n-particle (MCNP®) code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Large-Scale Visualization of 3D Unstructured Groundwater Model Using Cave Automated Virtual Environment

The immersive three-dimensional (3D) virtual reality (VR) visualization of groundwater models allows us to deepen our understanding of aquifer systems and provide better solutions to present groundwater-related problems, such as groundwater recharge, water quality, and sustainability. Visualization assists in accurately developing groundwater models and revealing important subsurface features, including faulting, folding, and unconformity. However, assessing model accuracy poses challenges due to the complexity of geology and groundwater systems. This research demonstrates a workflow to visualize and analyze raw 3D unstructured groundwater model data using an immersive Cave Automated Virtual Environment (CAVE). To visualize the unstructured groundwater model data, the raw dataset is converted into interactive CAVE-compatible formats utilizing a set of tools: ParaView, Blender, and Unity. This enables researchers to immerse themselves in the data, identifying influential patterns and relationships. e resulting insights can inform the development of sophisticated machine-learning models for groundwater level prediction. The CAVE’s immersive capabilities allow intuitive exploration from various perspectives, providing a more holistic understanding of the factors affecting groundwater levels. These insights are crucial to improve predictive models. The CAVE results also facilitate collaborative analysis and have potential applications in training and education. is research demonstrates the value of immersive VR tools such as the CAVE for unraveling intricacies within high-dimensional scientific data to drive real-world forecasting and modeling applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Web-based Preprocessing and Visualization of 3D FIB Tomography Data for Nuclear Fuel Characterization

Three-dimensional (3D) focused ion beam (FIB) tomography enables reconstruction of internal nuclear fuel features that can't be fully evaluated through surface imaging alone. This capability supports characterization of fuel constituents and defects under thermal and irradiation conditions relevant to microreactor development. However, large tomography datasets can create data-handling, loading, and visualization challenges, especially when image-stack preparation and file conversion must be completed with separate tools. The Computational Ultraspatial Tomography Toolkit for High-Resolution Object Analysis Tools (CUTTRHOAT) is an open-source web application being developed to display FIB tomography datasets available through the Nuclear Research Data System (NRDS). The current alpha version requires prepared HDF5 datasets and has limited integrated data-preparation capabilities. This project improves CUTTHROAT by adding dataset-folder selection, automatic input detection, dataset scanning, missing-slice identification, blank-slice insertion, and image-stack-to-HDF5 conversion. Two applications will be compared: the baseline CUTTHROAT alpha workflow and the updated application containing the integrated data-handling and preprocessing functions. Evaluation will consider dataset detection accuracy, conversion success, loading time, rendering responsiveness, application stability, and user interaction. Preliminary results demonstrate successful loading of existing HDF5 files and converted image stacks, while testing also identified performance reductions caused by excessive blank-slice generation. The updated workflow reduces reliance on external preparation tools and supports more direct movement from image stacks to color-code 3D visualization. Future work includes refining missing-slice handling, integrating additional preprocessing functions, like a denoising feature, parsing TIFF metadata for automatic voxel scaling, and adding manual X, Y, and Z voxel-spacing inputs for PNG and JPEG.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

PowerSystemsData Specification [SWR-25-92]

This repository defines a standardized data format for representing power system datasets, with a focus on supporting time-series visualizations and 3D visualization tools. By providing a consistent and extensible structure, this format aims to streamline the development and interoperability of visualization codebases in the power systems domain. NOODLES is a cross-platform/device/tool protocol for collaborative visualization. NOODLES was Developed at the National Renewable Energy Laboratory (NREL) as a capability of the Insight Center https://www.nrel.gov/computational-science/insight-center.html

Brunhart-Lupo, Nicholas [National Renewable Energy↗
DOE OSTI2022

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D

Abstract Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open‐access global archive housing three‐dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB‐designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro‐electron diffraction). The RCSB PDB research‐focused web portal ( RCSB.org ) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal ( PDB101.RCSB.org ) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB‐designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org ; and (v) supports training, outreach, and education via PDB101.RCSB.org . New tools and features at RCSB.org are presented using examples drawn from high‐resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.

59 BASIC BIOLOGICAL SCIENCES↗