Search NASA⌕ Search

SEARCH · Search NASA

Results for “Design Visualization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Imaging of a van der Waals spin-orbit torque system using spin ensembles in hBN

Recently, optically active spin defects embedded in two-dimensional (2D) van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science. Taking advantage of excellent solid-state integrability, this new class of spin defects can be readily arranged in nanoscale proximity to target materials, showing great promise for realizing in-situ quantum sensing of microscopic spin and charge behaviors in vdW heterostructures. Here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching and electric current distributions in an all-vdW spin-orbit torque (SOT) system. By visualizing variations of nanoscale magnetic stray field profile of room-temperature 2D magnet Fe 3 GaTe 2 under different SOT conditions, we show how the magnetic switching evolves from deterministic to stochastic behavior due to the interplay between spin orientations, anisotropy and Joule heating. Micromagnetic simulations rationalize our results well, revealing the role of field-like SOT in inhibiting thermal fluctuation driven stochastic switching and chaotic multi-domain competition. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights into material design, testing, and performance evaluation of next-generation vdW spintronic devices.

Imaging techniques↗
DOE OSTI2025

ACTIVE

The Automated Control Testbed for Integration, Verification, and Emulation (ACTIVE) framework is a software platform designed to support the optimized operation and management of a wide range of building types. It enables the development, testing, and validation of diverse control strategies, including AI-based, rule-based, and model-based approaches. The platform facilitates a seamless transition from simulation-based evaluation of control strategies to real-world field validation and deployment. ACTIVE supports the full building management lifecycle, encompassing data acquisition and management, system monitoring, optimized control, adaptive learning services, device dispatch and coordination, as well as advanced analytics and visualization. Together, these capabilities provide an integrated environment for improving building performance, operational efficiency, reducing energy cost, and reliability.

Smith, Robert [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2024

Atom Probe Tomography Investigation of Clustering in Model P 2 O 5 -Doped Borosilicate Glasses for Nuclear Waste Vitrification

Atom probe tomography (APT) has been utilized to investigate the microstructure of two model borosilicate glasses designed to understand the solubility limits of phosphorous pentoxide (P 2 O 5 ). This component is found in certain high-level radioactive defence wastes destined for vitrification, where phase separation can potentially lead to a number of issues relating to the processing of the glass and its long-term chemical and structural stability. The development of suitable focused ion beam (FIB)-preparation routes and APT analysis conditions were initially determined for the model glasses, before examining their detailed microstructures. In a 3.0 mol% P 2 O 5 -doped glass, both visual inspection and sensitive statistical analysis of the APT data show homogeneous microstructures, while raising the content to 4.0 mol% initiates the formation of phosphorus-enriched nanoscale precipitates. This study confirms the expected inhomogeneities and phase separation of these glasses and offers routes to characterizing these at near-atomic scale resolution using APT.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Optical Test Bench (SYSM 5620 Final Report)

The National Ignition Facility (NIF) is a research facility that focuses on High Energy Density Science and Inertial Confinement Fusion. In the NIF, 192 laser beams are directed into a miniscule Target Capsule to generate an implosion – this is called a NIF Shot. Many NIF Users conduct experiments using different Targets and laser inputs to generate reactions that are of interest to the scientific community. Those reactions are monitored using various Target Diagnostic instruments, including Shot Time Photography – which provides crucial images of the Target as the implosion occurs. A subset of these NIF Users is less interested in the reaction itself and more interested in subjecting materials or devices to the intense environment that these reactions can create. Using the Target as a source of x-rays, neutrons, or blast loading for particular materials has been significant to the shock physics community and to those who work in extreme design spaces. However, the Material and Radiation Effects team – that performs these experiments on behalf of the NIF Users – has not been able to make good use of the existing Shot Time Photography Diagnostics. The STP cameras are focused on the Targets rather than the MRE Customers’ materials, the current system is not oriented to have a good view of the MRE Customers’ materials, and the cameras are limited in their capabilities (black and white, poor resolution, etc.). As MRE experiments increase in quantity and importance to the scientific community, the desire for visual monitoring of the experiments to substantiate models and inform other data is also rising.

42 ENGINEERING↗
DOE OSTI2025

Designing a User Interface for Real-Time Magnetometer Data Acquisition

The Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) is a next-generation quantum sensor designed to search for ultralight dark matter and explore new frontiers in quantum mechanics. Due to the experiment s sensitivity to magnetic interference, a magnetometer trolley system was developed to scan magnetic fields along a vacuum tube. Interacting with the system required command-line inputs, creating usability challenges. To improve accessibility and streamline data acquisition, I developed a graphical user interface (GUI) using Python and the customtkinter library. The GUI supports real-time data display, state/mode switching, command execution, and CSV file management. I collaborated with another intern to integrate data visualization features into the GUI, allowing users to generate 3D plots of post-acquisition magnetic field data. In the future, I aim to fix the real-time plotting feature as it results in an unresponsive GUI.

Mendez, Milagros [DuPage Coll.]↗
DOE OSTI2025

Designing a User Interface for Real-Time Magnetometer Data Acquisition

The Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) is a next-generation quantum sensor designed to search for ultralight dark matter and explore new frontiers in quantum mechanics. Due to the experiment’s sensitivity to magnetic interference, a magnetometer trolley system was developed to scan magnetic fields along a vacuum tube. Interacting with the system required command-line inputs, creating usability challenges. To improve accessibility and streamline data acquisition, I developed a graphical user interface (GUI) using Python and the customtkinter library. The GUI supports real-time data display, state/mode switching, command execution, and CSV file management. I collaborated with another intern to integrate data visualization features into the GUI, allowing users to generate 3D plots of post-acquisition magnetic field data. In the future, I aim to fix the real-time plotting feature as it results in an unresponsive GUI.

Mendez, Milagros [DuPage Coll.]↗
DOE OSTI2025

Landscaper v1

Understanding the inner workings of machine learning models through their loss landscapes offers crucial insights into model properties, optimization dynamics, and generalizability. However, accessing these insights has traditionally required specialized mathematical expertise, limiting broader adoption. Landscaper is an open-source Python package designed to bridge this gap. Landscaper seamlessly integrates a suite of multi-dimensional loss landscape analyses with cutting-edge topological data analysis (TDA) methods. This powerful combination makes both fundamental loss landscape analysis and advanced TDA techniques accessible to the broader scientific ML community, without requiring deep pre-existing mathematical knowledge. Landscaper offers three key functionalities: * Construction: Builds detailed loss landscape representations through versatile low and high-dimensional sampling techniques. * Quantification: Applies advanced metrics, including a novel topological data analysis (TDA) based smoothness metric, enabling new perspectives on model behavior. * Visualization: Offers intuitive tools to visualize and interpret loss landscapes, providing actionable insights beyond traditional performance metrics.

Weber, Gunther [Lawrence Berkeley National Laborat↗
DOE OSTI2025

Collaborative: in situ visual analytics technologies for extreme scale combustion simulations

This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Evolution of highly multimodal Rayleigh–Taylor instabilities

Rayleigh–Taylor (RT) instabilities are important fluid instabilities that arise in inertial confinement fusion (ICF) capsule implosions, and many other contexts. Multi-mode coupling is observed in experiments and plays a substantial role in material mix from RT instabilities. In this work, we study the evolution of highly multimodal perturbations (power law distribution) that approximate those found at manufactured material interfaces. We use simulations of over 2000 different perturbations in the LANL code xRAGE to identify distinct phases in the processes of bubble growth and bubble merger which can be visualized in a 2D phase portrait with clear regimes of mode growth and decay. Our results show that the dynamic evolution of the instability strongly depends on the mode of the perturbations and mode interactions. The merger process accelerates bubble growth. A non-Markovian region and a transition of the instability from: (1) initial exponential growth to (2) linear growth and to (3) quadratic growth and asymptotic behavior, are clearly captured in the phase space. We have developed a quantitative model of bubble growth that reproduces the dynamic behavior of ensembles of perturbations. Implications for ICF capsules designed for robustness against instabilities are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

rcsb-api : Python Toolkit for Streamlining Access to RCSB Protein Data Bank APIs

The Protein Data Bank (PDB) was founded in 1971 as the first open-access digital data resource in biology to serve as the single global archive for three-dimensional (3D) macromolecular structure data. Current PDB holdings exceed 230,000 experimentally determined structures of proteins, nucleic acids, viruses, and macromolecular machines. The RCSB Protein Data Bank RCSB.org research-focused web portal facilitates search, analyses, and visualization of every PDB structure along with more than one million Computed Structure Models from AlphaFold DB and the ModelArchive. It is powered by a set of publicly available Application Programming Interfaces (APIs) that both support RCSB.org users and provide programmatic access to PDB data. Given the breadth and levels of granularity encompassed in this rich data collection, efficiently accessing the information programmatically may be challenging for new users. RCSB PDB has developed a Python software package, rcsb-api , that facilitates easy and efficient use of RCSB PDB APIs within a Python environment. This software tool is designed to streamline access to the extensive corpus of data housed within the PDB, enabling researchers to search, retrieve, and analyze 3D biostructure data seamlessly. Its use will accelerate research in structural biology, molecular biology and biochemistry, drug discovery, and bioinformatics by providing more efficient tools for data integration and analysis. The new toolkit is available on GitHub (github.com/rcsb/py-rcsb-api) and published to the public Python package repository (PyPI) to foster wider usage and support basic and applied research in fundamental biology, biomedicine, and the energy sciences.

FAIR principles↗
DOE OSTI2025

Tool-Based Case Studies on Strategic Deployment of Untapped Micro-Pumped Hydro Storage in Michigan

With most classical hydropower sites already utilized and the global push for rapid integration of renewable energy sources accelerating, there is a critical need to identify alternative energy storage solutions. Pumped hydro energy storage, which accounts for the vast majority of global grid-scale storage, remains one of the most cost-effective and long-duration storage technologies available. Hence, this study presents a novel tool designed to assess the untapped potential of inland lakes and reservoirs for micro-PSH, using Michigan’s relatively flat landscape as a case study due to its extensive but underutilized water infrastructure. To ensure accuracy and reliability, the tool incorporates extensive data gathered from authorized sources, covering more than 420 water facilities and potential reservoirs in the state. The tool evaluates key parameters such as horizontal and vertical distances, volume, and the total storage capacity of each reservoir. Its robust assessment framework integrates these metrics to evaluate each site’s potential. The tool’s intuitive interface and geospatial visualizations support actionable insights for planners and scalable deployment of distributed storage infrastructure.

13 HYDRO ENERGY↗
DOE OSTI2025

Nanopolysaccharide Builder: A User-Friendly Tool for Atomistic Models of Polysaccharide-Based Nanostructures

Here, we introduce Nanopolysaccharide Builder (NPB), a user-friendly software tool designed to construct polysaccharide nanostructures─mainly those based on cellulose, chitin, and chitosan─using experimental data or user-defined parameters. NPB enables the generation of cellulose and chitin allomorphs with customizable biochemical topologies and also facilitates the construction of large bundles that replicate nanostructures found in biological support systems, including plant cell walls and arthropod cuticles. The software outputs atomic Cartesian coordinates in Protein Data Bank (PDB) format and also provides atom connectivity files in PSF and PARM formats, ensuring seamless integration with major molecular dynamics (MD) engines such as NAMD, CHARMM, GROMACS, AMBER, OpenMM, and LAMMPS. Built on an interactive visualization framework, NPB features a graphical user interface (GUI) and supports both macOS and Linux operating systems. By enabling detailed atomic-scale studies of polysaccharide evolution in extracellular matrices and cell walls of algae, bacteria, fungi, and plants, NPB is poised to advance AI-guided research in sustainable chemical development and biomass utilization.

Wan, Zhangmin [Univ. of British Columbia, Vancouve↗
DOE OSTI2024

FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants

Abstract FatPlants, an open-access, web-based database, consolidates data, annotations, analysis results, and visualizations of lipid-related genes, proteins, and metabolic pathways in plants. Serving as a minable resource, FatPlants offers a user-friendly interface for facilitating studies into the regulation of plant lipid metabolism and supporting breeding efforts aimed at increasing crop oil content. This web resource, developed using data derived from our own research, curated from public resources, and gleaned from academic literature, comprises information on known fatty-acid-related proteins, genes, and pathways in multiple plants, with an emphasis on Glycine max, Arabidopsis thaliana, and Camelina sativa. Furthermore, the platform includes machine-learning based methods and navigation tools designed to aid in characterizing metabolic pathways and protein interactions. Comprehensive gene and protein information cards, a Basic Local Alignment Search Tool search function, similar structure search capacities from AphaFold, and ChatGPT-based query for protein information are additional features. Database URL: https://www.fatplants.net/

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Updimensioning strategy derived from synthetic equiaxed grain structures for approximating 3D grain size distributions from 2D visualizations with 1D parameters

We generated synthetic equiaxed grain structures using computer graphics software to explore the relationship between various grain size determination methods and true three-dimensional (3D) grain diameters. Mirroring grain measurement techniques, the synthetic 3D grain structures are imaged as 2D micrographs which are measured to yield 1D grain size parameters. Synthetic grain structures provide data at a mass scale and permit exploration of both polished and fractured surface micrographs, revealing one-to-one correspondence between exposed 2D grain cross-sections and individual 3D grains. Analysis of this correspondence yielded a procedure to approximate 3D equiaxed grain size and volume distributions based on the mode of the 2D fractograph grain size distribution. The 3D approximation procedure is shown to be less susceptible to different imaging conditions that affect small, undiscernible grains compared to the standard planimetric and linear intercept methods, which by design also tend to underestimate the 3D grain diameter. The procedure requires larger sample sizes to lower variance and a deeper analysis which could become more practical with machine learning (ML) models for grain boundary segmentation, which synthetic grain structures can help train. This work lays the foundation for analyzing other grain distributions such as columnar and composite grains in similar depth.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

New perspectives on materials and device dynamics using time-resolved full-field diffraction X-ray imaging

Understanding how materials evolve during synthesis, processing, or device operation requires experimental access to structural dynamics across wide ranges of length and time scales, often in bulk samples or even within packaged devices. Time-resolved full-field diffraction X-ray microscopy has recently emerged as a powerful way to meet this need by combining the penetration and structural sensitivity of X-ray diffraction with objective-lens-based magnification, sensitive high-resolution X-ray imaging detectors, and pump-probe and real-time imaging strategies. Advances in full-field X-ray diffraction microscopy, often termed dark-field X-ray microscopy (DFXM), enable simultaneous imaging of extended fields of view while retaining crystallographic selectivity. Time-resolved DFXM promises to enable advances in materials processing and dynamics, electrochemical and photochemical processes, and the design of electronic devices. This Perspective summarizes the key instrumental concepts that define the performance of these methods, including the choice of imaging optics, detector considerations, and the impact of source time structure at synchrotron light sources and X-ray free-electron lasers (XFELs). We discuss the simultaneous use of complementary imaging modes that are increasingly used in practice. The early demonstrations of the potential of time-resolved DFXM include real-time defect and grain-boundary dynamics during metal annealing, stroboscopic imaging of functional devices with high strain sensitivity, and ultrafast pump-probe implementations at XFELs that directly visualize acoustic-wave propagation and energy dissipation in bulk crystals.

Dark-field X-ray microscopy↗
DOE OSTI2026

A Review and Outlook on Experimental Advances and Innovations in Geological CO 2 Storage: Insights from Depleted Gas Reservoirs and Saline Aquifers

Geological storage of carbon dioxide (CO 2 ) in depleted gas reservoirs and deep saline aquifers is a key part of global decarbonization efforts. As carbon capture and storage advances toward commercial-scale deployment, the credibility and scalability of laboratory experiments are increasingly vital for guiding safe and effective field implementation. This review offers a comprehensive, cross-scale evaluation of experimental methodologies, including core flooding, high-pressure, high-temperature systems, microfluidic visualization, and emerging systems such as multilayer commingled/compartmentalized core flooding, 3D-printed micromodels, and AI-powered digital twins. These innovations are demonstrated to enhance representativeness, reproducibility, and real-time insight, thereby addressing the limitations of conventional workflows. A critical analysis of methodological gaps, such as inconsistent pressure–temperature conditions, oversimplified brine chemistry, and a lack of standardization, reveals experimental sources of scale translation errors and performance uncertainty. By comparing the unique challenges of depleted gas reservoirs (such as low water saturation and legacy well leakage) to those of saline aquifers (including pressure buildup and caprock integrity), this review identifies formation-specific priorities for experimental design. Novel contributions include a synthesis of best practices, integration strategies for model calibration, and recommendations for standardizing core handling, saturation procedures, and reporting protocols. Furthermore, this work serves as a guide for developing robust, field-relevant experimental strategies that can increase the deployment and regulatory acceptance of CO 2 storage technologies at scale.

58 GEOSCIENCES↗
DOE OSTI2024

Measurement of Photovoltaic Module Deformation Dynamics During Hail Impact Using Digital Image Correlation

Stereo high-speed video of photovoltaic modules undergoing laboratory hail tests was processed using digital image correlation to determine module surface deformation during and immediately following impact. The purpose of this work was to demonstrate a methodology for characterizing module impact response differences as a function of construction and incident hail parameters. Video capture and digital image analysis were able to capture out-of-plane module deformation to a resolution of ±0.1 mm at 11 kHz on an in-plane grid of 10 × 10 mm over the area of a 1 × 2 m commercial photovoltaic module. With lighting and optical adjustments, the technique was adaptable to arbitrary module designs, including size, backsheet color, and cell interconnection. Furthermore, impacts were observed to produce an initially localized dimple in the glass surface, with peak deflection proportional to the square root of incident energy. Subsequent deformation propagation and dissipation were also captured, along with behavior for instances when the module glass fractured. Natural frequencies of the module were identifiable by analyzing module oscillations postimpact. Limitations of the measurement technique were that the impacting ice ball obscured the data field immediately surrounding the point of contact, and both ice and glass fracture events occurred within 100 μs, which was not resolvable at the chosen frame rate. Increasing the frame rate and visualizing the back surface of the impact could be applied to avoid these issues. Applications for these data include validating computational models for hail impacts, identifying the natural frequencies of a module, and identifying damage initiation mechanisms.

14 SOLAR ENERGY↗
DOE OSTI2025

UrbanScaping: Community Spatial Data Visualization & Analytics

Evaluating the electrification potential of buildings through retrofitting is crucial for reducing carbon emissions and the carbon footprint of built environments. This study leverages the Automatic Building Energy Modeling (AutoBEM) software, integrating the Model America database to create an urban context-based spatial analysis platform for community engagement and development. We selected Camp Hill Borough, PA, as a case study to analyze building-specific energy performance and evaluate the electrification potential of each building by switching to different Heating, Ventilation, and Air Conditioning (HVAC) systems and measurement components. The simulation results generated by the workflow provide retrofitting suggestions to help mitigate the carbon footprint as well as energy saving statistics of buildings. Additionally, the developed web-based interface serves as a community engagement platform, allowing residents to provide feedback and further develop interactive communication protocols. The outcomes of this project offer a baseline for community electrification planning and contribute to the design of low-carbon communities.

Chowdhury, Shovan [ORNL]↗