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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Predicting critical heat flux using localized sensing at invisible vapor-liquid interfaces

Predicting critical heat flux (CHF) in two-phase electronics cooling systems remains a significant challenge due to the sudden onset of boiling crisis and the difficulty in directly visualizing vapor-liquid interfaces. Existing sensing methods rely on lagging temperature measurements, optically accessible systems, or spatially averaged signals that cannot pinpoint CHF initiation at localized high-heat-flux regions. Here, we report a planar capacitive sensing approach that enables real-time, localized detection of vapor-liquid interface dynamics for CHF prediction in boiling heat transfer. The capacitive sensor exploits the dielectric constant difference between liquid and vapor phases to capture bubble nucleation, growth, and departure dynamics with a temporal resolution down to 2 ms. The capacitive sensing reveals distinct signals across boiling regimes: from high-frequency fluctuations during strong nucleate boiling to low-frequency fluctuations with increased amplitudes when approaching CHF. The multi-sensor array experiments demonstrate real-time localized sensing, where each sensor responds exclusively to boiling in its immediate vicinity without crosstalk from neighboring regions. This non-intrusive sensing approach provides predictive rather than lagging sensing signals of CHF occurrence, offering predictive diagnosis of two-phase liquid cooling for the thermal management of high-power-density electronics.

CHF↗
DOE OSTI2026

Rasterization with Data-Parallel Primitives

Parallel rasterization can suffer from race conditions during fragment generation, which is traditionally addressed by using specialized hardware accessible via vendor graphics APIs. Unfortunately, graphics APIs are increasingly problematic on high-performance computers, either because they are not provided or because of concerns about dependencies with in situ visualization. In response, we present a hardware-agnostic rasterization algorithm that handles race conditions using only data-parallel primitives (DPPs), enabling efficient rendering on HPC systems without graphics API dependencies and aligning with recent efforts to deliver visualization software with DPPs. Our evaluation consists of three phases: (1) evaluating portability across different CPU and GPU architectures, (2) evaluating competitiveness with a community standard, and (3) evaluating performance across varying workloads and available parallelism. The supporting experiments run on both AMD and NVIDIA GPUs, considering data sets as large as 460 million triangles and 160 million pixels. While performance generally falls short of graphics API baselines, it achieves interactive frame rates on most workloads. As a result, we conclude our approach is a viable solution for rasterization on high-performance computers since our approach is portably performant across different architectures without the need for specialized vendor support.

Buckley, Makani [University of Oregon] (ORCID:0009↗
DOE OSTI2025

Applications of visualization technology in the structural sciences

The structural sciences are undergoing a transformation driven by advancements in visualization technologies that aid researchers in understanding and communicating experimental data from complex molecular systems. New applications of integrative structural biological and biophysical approaches add a wide variety of complementary information from a broad range of scientific disciplines. These approaches extend structural biophysical methodologies to enable research by the incorporation of a variety of data streams and utilization of tools like molecular graphics, virtual reality, and machine learning. To redefine how structural data—particularly from cryo-electron microscopy and x-ray crystallography—are fed forward for scientific exploration and communication, the advances in tools for data visualization and interpretation have been critical. By bringing molecular systems into an interactive three-dimensional space, these novel technologies enhance research workflows, facilitate structure-based drug design, and create engaging educational experiences. Taken together, these visualization innovations are essential tools for advancing the field by making concepts more accessible and compelling.

Eng, Edward T. [New York Structural Biology Center↗
DOE OSTI2025

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Developing a digital twin framework for remotely monitoring nuclear reactor facilities

A digital twin must seek to represent all applicable functional components of the system of interest. Different expertise is required for understanding the physical system being modeled than the skills needed for transforming those models into a functional digital twin through physics modeling, machine learning analysis, and visualization. The diversity of knowledge requires a multi-disciplinary team to ensure all system details are captured. Team members also need a method to verify that the data they generate within their domain can be effectively communicated to professionals in other fields. To address this challenge, this work provides an approach for developing a digital twin framework to remotely monitoring nuclear facilities. Through this, general knowledge of the framework is presented along with two examples to solidify the process. The AGN-201 digital twin and microreactor digital twins provide varying levels of complexity in a potential nuclear facility, where common threads are identified and lessons learned are provided. The goal of this research is to aid future researchers by providing a formula for a successful digital twin and in turn reducing the development time of nuclear system digital twins, specifically for remote monitoring.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A rapid, pulsed laser testing approach for single event latch-up screening in microelectronics

A pulsed laser testing system for rapid screening of single-event latch-up (SEL) in microelectronics with real-time visualization of sensitive nodes via photo-emission is presented. We provide a detailed overview of the system, followed by SEL threshold measurements in an analog-to-digital converter (AD9240). We find that SEL thresholds are comparable to measurements taken with a low-repetition rate, fixed beam system, and demonstrate full-die scanning speeds can be an order of magnitude faster

Andrus, Liam Padraic↗
DOE OSTI2025

Bimodal Visualization of Industrial X-Ray and Neutron Computed Tomography Data

Advanced manufacturing creates increasingly complex objects with material compositions that are often difficult to characterize by a single modality. Our collaborating domain scientists are going beyond traditional methods by employing both X-ray and neutron computed tomography to obtain complementary representations expected to better resolve material boundaries. However, the use of two modalities creates its own challenges for visualization, requiring either complex adjustments of bimodal transfer functions or the need for multiple views. Together with experts in nondestructive evaluation, we designed a novel interactive bimodal visualization approach to create a combined view of the co-registered X-ray and neutron acquisitions of industrial objects. Using an automatic topological segmentation of the bivariate histogram of X-ray and neutron values as a starting point, the system provides a simple yet effective interface to easily create, explore, and adjust a bimodal visualization. Here, we propose a widget with simple brushing interactions that enables the user to quickly correct the segmented histogram results. Our semiautomated system enables domain experts to intuitively explore large bimodal datasets without the need for either advanced segmentation algorithms or knowledge of visualization techniques. We demonstrate our approach using synthetic examples, industrial phantom objects created to stress bimodal scanning techniques, and real-world objects, and we discuss expert feedback.

image segmentation↗
DOE OSTI2024

An open-source data storage and visualization platform for collaborative qubit control

Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization ( QubiCSV ), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Evaluation of the Radioactive Material Released in the Harborview Research and Training Building and Some Implications for Emergency Response

On 2 May 2019, during the 137 Cs source recovery operation, a source capsule in a research irradiator containing approximately 77.1 TBq was breached. Based on a geometric reconstruction analysis of the damage to the capsule, approximately 46.3 GBq (0.04%) was impacted by the chop saw (grinder) inside a mobile hot cell on the loading dock at the University of Washington Harborview Research and Training (HRT) Building. A very small fraction of the material impacted, less than 1%, was released from the mobile hot cell and then to the rest of the HRT Building. The objectives of this project were to assess the accidental release of 137 CsCl and its implications related to emergency response methods and the ramifications of 137 CsCl transport. The phenomenology of this event was also compared with past alkali halide dispersal events. The vast number of measurements and samples collected by the remediation contractors, the Department of Energy’s Nuclear Emergency Support Team, and the small number of retrospective samples collected by the authors informed the analysis. The techniques included (1) autoradiography and electron microscopy of samples collected from the HRT Building and the irradiator, (2) 3D visualization of deposition on surfaces and within the ventilation system, and (3) a study of the damage to the source capsule to evaluate the Cs particle size and particle composition due to the grinding accident. Subsequently, the cesium contaminant transport through the numerous pathways in the building was reconstructed to assess the deposition on surfaces as a function of particle size. Furthermore, the implications for emergency response are relevant to data quality and management. A Data Quality Objective guides data collection methods so that they have appropriate accuracy and precision for the intended application. Recommendations were made with respect to the sample collection protocols and archiving of samples.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

SSAPy - Space Situational Awareness for Python

SSAPy is a fast and flexible orbit modeling and analysis tool for orbits spanning from low-Earth into the cislunar regime. Orbits can be flexibly specified from common input formats such as Keplerian elements or two-line element (TLE) data files. SSAPy allows users to model satellites and specify parameters such as satellite area, mass, and drag coefficients. SSAPy includes a customizable force-propagation with a range of Earth, Lunar, radiation, atmospheric, and maneuvering models. SSAPy makes use of various community integration methods and can calculate time-evolved orbital quantities, including satellite magnitudes and state vectors. Users can specify various space- and ground-based observation models with support for multiple coordinate and reference frames. SSAPy also supports orbit analysis and propagation methods such as multiple hypothesis tracking and has built-in uncertainty quantification. The majority of SSAPy’s methods are vectorized and parallelizable, allowing for effective use of high-performance computer (HPC) systems. Finally, SSAPy has plotting functionality, allowing users to visualize orbits and trajectories. Examples are shown in Figure 1 and Figure 2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Evaluation of the Radioactive Material Release in the Harborview Research and Training Building and Implications for Emergency Response

On May 2, 2019, during the 137 Cs source recovery operation, a source capsule in a research irradiator containing approximately 77.1 TBq was breached. Based on a geometric reconstruction analysis of the damage to the capsule, approximately 46.3 GBq (0.04%) was impacted by the chop saw (grinder) inside a Mobile Hot Cell (MHC) on the loading dock at the University of Washington Harborview Research and Training (HRT) Building. A very small fraction of the material impacted, less than 1%) was released from the Mobile Hot Cell and then to the rest of the HRT Building. The objectives of this project were to assess the accidental release of 137 CsCl and its implications related to emergency response methods and the ramifications of 137 CsCl transport. The phenomenology of this event was also compared with past alkali halide dispersal events. The vast number of measurements and samples collected by the remediation contractors, the Department of Energy's Nuclear Emergency Support Team, and the small number of retrospective samples collected by the authors informed the analysis. The techniques included (1) autoradiography and electron microscopy of samples collected from the HRT Building and the irradiator, (2) 3D visualization of deposition on surfaces and within the ventilation system, and (3) a study of the damage to the source capsule to evaluate the Cs particle size and particle composition due to the grinding accident. Subsequently, the cesium contaminant transport through the numerous pathways in the building was reconstructed to assess the deposition on surfaces as a function of particle size. The implications for emergency response are relevant to data quality and management. A Data Quality Objective (DQO) guides data collection methods so that they have appropriate accuracy and precision for the intended application. Recommendations were made with respect to the sample collection protocols and sample archival.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Analysis of Electricity Price Differentials for the Utah Office of Energy Development

Operation Gigawatt is a vision for Utah to meet its growing energy needs with a focus on doubling energy generation. One of the greatest challenges to meet this goal will be the transmission and distribution system. Utah seeks analysis to inform discussions on new generation, the likely network congestion based on new power flows, and modeling of the state's energy infrastructure. To support this need, LBNL developed a baseline understanding of recent historical congestion in the existing transmission system based on electricity market prices. The resulting products visualize and provide metrics on congestion within Utah and between Utah and its neighbors during 2015-2023.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Electronic Visualization Laboratory's 50th Anniversary Retrospective: Look to the Future, Build on the Past

September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL's introduction of the CAVE Automatic Virtual Environment in 1992, the first widely replicated, projection-based, walk-in, virtual-reality (VR) system in the world, put EVL at the forefront of collaborative, immersive data exploration and analytics. However, the journey did not begin then. Since its founding in 1973, EVL has been developing tools and techniques for real-time, interactive visualizations—pillars of VR. But EVL's culture is also relevant to its successes, as it has always been an interdisciplinary lab that fosters teamwork, where each person's expertise contributes to the development of the necessary tools, hardware, system software, applications, and human interface models to solve problems. Over the years, as multidisciplinary collaborations evolved and advanced scientific instruments and data resources were distributed globally, the need to access and share data and visualizations while working with colleagues, local and remote, synchronous and asynchronous, also became important fields of study. This paper is a retrospective of EVL's past 50 years that surveys the many networked, immersive, collaborative visualization and VR systems and applications it developed and deployed, as well as lessons learned and future plans.

Johnson, Andrew E.↗
DOE OSTI2026

The U.S. Agrivoltaic Shading Tool: A National-Scale Interface for Modeling Light and Shade Patterns in Ten Common Agrivoltaic Configurations

Agrivoltaic systems are dual-use configurations that co-locate agriculture and photovoltaic (PV) infrastructure and require careful design to balance crop performance and energy generation. A critical element of agrivoltaic design is the spatial and temporal distribution of irradiance and shade within and around PV arrays. To support research, planning, and stakeholder decision-making, we introduce the U.S. Agrivoltaic Shading Tool, a novel web-based application that delivers high-resolution irradiance and photosynthetically active radiation (PAR) modeling for ten standardized PV configurations across the conterminous United States. The tool leverages the National Laboratory of the Rockies (NLR) System Advisor Model (SAM) to perform detailed irradiance simulations, using meteorological data from the National Solar Radiation Database (NSRDB). Outputs include seasonal, monthly, weekly, and diurnal patterns of available sunlight, amount of shade, irradiance, and PAR at ground level within agrivoltaic system footprints. For a user's selected location, these results are visualized through interactive visualizations, heatmaps, and time-series plots, designed to be accessible to both technical and non-technical users. In addition to facilitating rapid spatial exploration of agrivoltaic light environments, the tool will offer seamless integration with the InSPIRE Agrivoltaics Design and Analysis Model (ADAM). This optional workflow will allow users to port selected site and configuration parameters into a more advanced modeling environment for further customization of structural layouts, crop-system compatibility, power generation, and technoeconomic performance. Finally, to promote open science, the entire dataset will be hosted and available for open access through the OpenEI platform. By standardizing and disseminating high-quality irradiance data and design tools, the U.S. Agrivoltaic Shading Tool supports a wide range of users, including researchers, landowners, energy developers, and policymakers, in evaluating the agronomic and energetic feasibility of agrivoltaic systems across the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

WELLS Interactive Application

The Wellbore Exploration and Location Logistic System (WELLS) Interactive Application is an interactive tool to enable easy exploration and visualization of the living national wellbore database (WELLS Database (https://edx.netl.doe.gov/dataset/wells_database)). The tool and underlying database were created and are maintained by the National Energy Technology Laboratory (NETL), providing visualization of the more than six million public wellbore records from more than 65 authoritative state, federal, and tribal resources. The WELLS Interactive Application serves up wellbore data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater, and other types of wells in a single, standardized, unified system. In addition to the surface location of these wells, the underlying database combines select key attributes for features such as well age, depth, and operating status. The system also provides users with references back to the original sources used in this unified platform. The underlying data can be accessed through the WELLS Database: https://edx.netl.doe.gov/dataset/wells_database Additional Information: The WELLS Interactive Application (formerly titled CO2-Locate) enables visualization and access to the public wellbore records through an intuitive web-based mapping tool. The WELLS Interactive Application was designed to help users visualize, query, analyze, and download wellbore records. Public wellbore points are included as a layer in the Map page, called Public Wells. Additionally, a multivariate hexagon grid summarizing well density from proprietary well data, called Well Density, is included to identify data gaps between the public and proprietary well data. Filtering functionalities in the tool allow these two layers to be spatially filtered by state, county, or basin as well as by status, type, true vertical depth, and spud year. The WELLS Interactive Application also contains a Near Me tool can be used to search and explore wellbore data within a user-defined distance of a specified location on the map, which can also be downloaded. The Query tool allows users to query the selected or filtered wells in the Public Wells layer and export the data. For additional information on these tool functionalities, see the help documentation on the About page of the tool. Notes for Consideration: The Well Density layer provided in this application is derived from proprietary wellbore data, the records of which do not always contain values for key features (status, type, true vertical depth, or spud year). Therefore, data might not be available when layers are queried for all filter combinations. Additionally, visualizing layers and applying filters may take additional time to load (i.e., draw on the map) due to the large size of the data.

ccs↗
DOE OSTI2024

Multi-Scale Integrated Monitoring System for Enhancing Methane Emission Detection, Quantification & Prediction

This report details the progress and findings of a comprehensive study on reviewing existing solutions, identifying technology gaps, and formulating an “all-in-one” integrated strategy for developing the next-generation multiscale methane monitoring and modeling platform, conducted under grant number DE-FE0032292. Co-led by Dr. David Ebert, Dr. Binbin Weng, and Dr. Chenghao Wang at the University of Oklahoma, the project’s goal was to develop an integrated approach for building this engineering platform to detect, quantify, and mitigate methane emissions across various temporal scale, spatial scales, and sectors. The planning grant study began with an extensive review of various methane sensing and monitoring technologies and systems, surveying over 100 technology providers globally. This review revealed the prevalence of optical methods over chemical methods in commercially available sensors, with Non-Dispersive Infrared (NDIR), Tunable Diode Laser Absorption Spectroscopy (TDLAS), and Optical Gas Imaging (OGI) cameras being the most prevalent options. A trend towards more advanced optical techniques was observed, driven by increased regulatory focus and technological advancements. The technical evaluation of these sensing technologies provided crucial insights into their capabilities and limitations. The study examined emerging technologies such as Differential Absorption LiDAR (DIAL), which show promise for high-precision and long-range detection. The team then investigated the features and application bandwidth of various sensing platforms, including handheld, fixed/stationary, mobile, aerials, and spaceborne monitors. Pilot field studies were conducted to assess the capabilities of solutions for different emission scenarios. Field work with sensor deployments was conducted at three distinct site types: an oil & gas industry site, a cattle ranching operation, and a waste processing facility. The team also conducted a thorough review of methane flux inverse modeling approaches, focused on physically based methods. These approaches were categorized into simple, intermediate, and advanced methods. A realtime WRF-GHG (Weather Research and Forecasting-Greenhouse Gas) modeling system was developed and applied, incorporating multiple data sources to guide field experiments and inform methane plume detection. The project identified and analyzed numerous categories of methane data sources, including satellite measurements, ground-based sensors, and inventory databases. Key platforms examined include EDGAR, EPA GHGI, NASA TROPOMI, Carbon Mapper, and Climate TRACE, among others. The team proposed an architecture for a comprehensive methane monitoring platform. This system incorporates multi-source data acquisition, advanced data processing and assimilation, interactive visualization tools, and analytical capabilities for emissions forecasting and scenario analysis. The proposed platform aims to provide a user-friendly interface catering to various stakeholders, from researchers to policymakers. The architecture includes sophisticated data ingestion methods, a centralized data warehouse, and advanced analytical tools for data fusion and interpretation. To ensure the relevance and effectiveness of the proposed system, a comprehensive survey was conducted to gather stakeholder input on system requirements. Key findings include a strong need for integrating various data types and formats, a preference for real-time data updates and advanced visualization tools, and a demand for user-friendly interfaces catering to different expertise levels.

03 NATURAL GAS↗
DOE OSTI2026

Human-system Interface Style Guide for ACORN Control System

The purpose of this style guide is to provide a clear, consistent framework for the design and development of human system interfaces (HSIs) used throughout the Fermilab accelerator complex. It establishes a shared visual and interaction foundation to ensure that interfaces remain intuitive, effective, and cohesive, regardless of when or by whom they are developed. By adhering to these guidelines, developers can avoid introducing unnecessary deviations that compromise usability or increase system training burden. This consistency is especially critical in long-term, multi-contributor projects where interface continuity and maintainability are paramount. This document serves as a practical reference for all HSI development activities related to the accelerator control environment. While the guidance provided is comprehensive, it is not exhaustive of every potential design scenario. As such, the style guide is intended to function as a living document, subject to regular review and revision. Updates will be made at least annually to incorporate emerging best practices, operational feedback, and evolving system needs. Areas where detailed guidance is still under development are clearly indicated in gray throughout the document and will be addressed in future revisions according to project priorities.

Hill, Rachael [Idaho Natl. Lab.] (ORCID:0000000263↗
DOE OSTI2024

Simulation of Helium Flow Visualization Apparatus for Studies of Blanket Cooling in Fusion Reactors

Flow visualization is essential to understanding helium cooling performance. This article investigates helium flow visualization in an apparatus to support the design of the blanket first wall for a fusion reactor. Helium’s safety advantages make it an attractive coolant, but effective cooling and flow visualization remain challenging. Sophisticated simulations are conducted in different test sections to address three key areas in the design of a test apparatus and cooling channel enhancements: the influence of viewing glass windows on flow patterns, the impact of increased heating, and the effectiveness of cooling structures like baffles. Viewing glass windows introduce flow recirculation region bifurcation and flow asymmetry, affecting flow patterns and necessitating careful analysis in future experiments. Increased heating results in helium flow detachment from the heated surface, leading to hot spots. Cooling structures, particularly baffles, prove effective in maintaining consistent attachment to the heated surface, improving the heat transfer performance. Further, this study also examines a tunable parameter in the turbulence model, highlighting the importance of accurate model tuning for future fusion reactor cooling designs. With an imminent helium flow visualization facility, these simulations will be used to optimize cooling structures on the heated wall to improve flow attachment and heat transfer efficiency. This work serves as a first investigation of the helium flow visualization apparatus for blanket cooling enhancement in fusion reactor design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗