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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Thermally driven mesoscale chemomechanical interplay in Li 0.5 Ni 0.6 Mn 0.2 Co 0.2 O 2 cathode materials

While Li ion batteries are intended to be operated within a mild temperature window, their structural and chemical complexity could lead to unanticipated local electrochemical events that could cause extreme temperature spikes, which, in turn, could trigger more undesired and sophisticated reactions in the system. Visualizing and understanding the response of battery electrode materials to thermal abuse conditions could potentially offer a knowledge basis for the prevention and mitigation of the safety hazards. Here we show a comprehensive investigation of thermally driven chemomechanical interplay in a Li 0.5 Ni 0.6 Mn 0.2 Co 0.2 O 2 (charged NMC622) cathode material. We report that, at the early stage of the thermal abuse, oxygen release and internal Li migration occur concurrently, and are accompanied by mechanical disintegration at the mesoscale. At the later stage, Li protrusions are observed on the secondary particle surface due to the limited lithium solubility in non-layered lattices. As a result, the extraction of both oxygen and lithium from the host material at elevated temperature could influence the chemistry and safety at the cell level via rearrangement of the electron and ion diffusion pathways, reduction of the coulombic efficiency, and/or causing an internal short circuit that could provoke a thermal runaway.

25 ENERGY STORAGE↗
DOE OSTI2018

Probing one-dimensional systems via noise magnetometry with single spin qubits

The study of exotic one-dimensional states, particularly those at the edges of topological materials, demand new experimental probes that can access the interplay between charge and spin degrees of freedom. One potential approach is to use a single spin probe, such as a nitrogen vacancy center in diamond, which has recently emerged as a versatile tool to probe nanoscale systems in a noninvasive fashion. Here, we present a theory describing how noise magnetometry with spin probes can directly address several questions that have emerged in experimental studies of 1D systems, including those in topological materials. We show that by controlling the spin degree of freedom of the probe, it is possible to measure locally and independently local charge and spin correlations of 1D systems. Visualization of 1D edge states, as well as sampling correlations with wave-vector resolution can be achieved by tuning the probe-to-sample distance. Furthermore, temperature-dependent measurements of magnetic noise can clearly delineate the dominant scattering mechanism (impurities versus interactions)—this is of particular relevance to quantum spin Hall measurements where conductance quantization is not perfect. Here, the possibility to probe both charge and spin excitations in a wide range of length scales opens new pathways to bridging the large gap between atomic scale resolution of scanning probes and global transport measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Memory-Aware External Facelist Calculation: A Data-Parallel Atomic Hash Counting Approach

Unstructured volumetric meshes serve as fundamental data representations in various scientific simulations and analyses. They play a crucial role in representing complex computational domains and are essential for important numerical techniques, such as finite element analysis. Whenever such a mesh is read from a file, streamed in-situ, or generated by algorithms, scientific visualization libraries rely on calculating the external surface of a geometry, named “external facelist”, to produce a polygonal mesh for rendering. Consequently, external facelist calculation has become one of the most widely used algorithms in the scientific visualization domain, necessitating optimal performance. In this paper, we explore relevant work on external facelist calculation algorithms in two common visualization libraries, VTK and Viskores, assess their performance and memory constraints, and introduce a novel memory-aware external facelist calculation algorithm employing an atomic hash counting approach. This algorithm fully leverages Viskores' data-parallel primitive operations, facilitating its execution across diverse many-core architectures. Our algorithm features the lowest memory footprint on the GPU and the second-lowest on the CPU among all evaluated methods, and it also delivers the fastest performance on both CPU and GPU. It has been made available under an open-source license in the VTK and Viskores visualization systems.

Tsalikis, Spiros [Kitware] (ORCID:0000000151137195↗
DOE OSTI2023

Reducing nighttime light exposure in the urban environment to benefit human health and society

Nocturnal light pollution can have profound effects on humans and other organisms. Recent research indicates that nighttime outdoor lighting is increasing rapidly. Evidence from controlled laboratory studies demonstrates that nocturnal light exposure can strain the visual system, disrupt circadian physiology, suppress melatonin secretion, and impair sleep. There is a growing body of work pointing to adverse effects of outdoor lighting on human health, including the risk of chronic diseases, but this knowledge is in a more nascent stage. In this Review, we synthesize recent research on the context-specific factors and physiology relevant to nocturnal light exposure in relation to human health and society, identify critical areas for future research, and highlight recent policy steps and recommendations for mitigating light pollution in the urban environment.

Science & Technology - Other Topics↗
DOE OSTI2018

NDDAV

Web-based Interface for the N-Dimensional Data Analysis and Visualization System.

Liu, Shusen↗
DOE OSTI2019

XVis: Visualization for the Extreme-Scale Scientific Computation Ecosystem (Final Report)

Scientific computing is no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis. This report reviews the accomplishments of the XVis project to prepare scientific visualization for Exascale computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Inefficacy of mallard flight responses to approaching vehicles

Vehicle collisions with birds are financially costly and dangerous to humans and animals. To reduce collisions, it is necessary to understand how birds respond to approaching vehicles. We used simulated (i.e., animals exposed to video playback) and real vehicle approaches with mallards (Anas platyrynchos) to quantify flight behavior and probability of collision under different vehicle speeds and times of day (day vs. night). Birds exposed to simulated nighttime approaches exhibited reduced probability of attempting escape, but when escape was attempted, fled with more time before collision compared to birds exposed to simulated daytime approaches. The lower probability of flight may indicate that the visual stimulus of vehicle approaches at night (i.e., looming headlights) is perceived as less threatening than when the full vehicle is more visible during the day; alternatively, the mallard visual system might be incompatible with vehicle lighting in dark settings. Mallards approached by a real vehicle exhibited a delayed margin of safety (both flight initiation distance and time before collision decreased with speed); they are the first bird species found to exhibit this response to vehicle approach. Our findings suggest mallards are poorly equipped to adequately respond to fast-moving vehicles and demonstrate the need for continued research into methods promoting effective avian avoidance behaviors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Radiography of Dry Cask Storage for Used Nuclear Fuel

Since the U.S. currently only approves of storing used nuclear fuel in pools or dry casks, the demand for dry cask storage is on the rise due to the continuous operation of currently existing nuclear plants which are reaching or have reached the capacity of their used fuel pools. With the rising demand comes additional pressure to ensure the integrity of dry cask systems. Visual inspection is costly and man-power intensive, so alternative nondestructive testing techniques are desired to insure the continued safe and effective storage of fuel. Several approaches being investigated by the University of Florida and the larger multi-university Department of Energy (DOE) Nuclear Energy University Program (NEUP) Integrated Research Project (IRP) are gamma or neutron radiography, both transmission based and interior source emission. Additionally muon radiography is discussed. This work leverages the well-established techniques in medical image reconstruction and applies them to a significantly larger scale with additional considerations due to the dense nuclear materials which serves as effective shields for radiation. Emission source radiography relies on the radiation that is emitted from the used fuel. The main advantage of this technique is the passive nature of the measurement. The fuel is already emitting radiation and only detectors are needed. Transmission radiography uses an external source of radiation to penetrate the side of the cask. Challenges include selecting the external source spectrum to avoid overlap with the spectrum emitted from the fuel, and ensuring the radiation dose limits do not exceed those mandated by the Nuclear Regulatory Commission (NRC). Benefits of this technique include better understanding of the source location allowing for clear image reconstruction, and isolation of the signal from surrounding radiation sources. Muon radiography takes advantage of the natural background flux coming from the interaction of the atmosphere with cosmic radiation. The technique is particularly effective at interrogating large dense objects as the highly energetic muons have smaller cross sections than most typical sources and energies used in nuclear engineering. The various techniques are discussed individually then the conclusion compares them. Finally, future work is identified.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Metallography Box Improvements

The information included in this poster is designed to provide information on a visualization system needed in a hot-cell with a high radiation dose level. The system is necessary to enable real-time remote monitoring of microscope function. The current configuration for viewing function of in-cell equipment is through a single window. This makes for difficult viewing of the microscope workstations which are located away from the window. A properly designed camera system enhances troubleshooting capability in-cell. The poster will aid in the exposition of the design process and implementation of the system described above.

42 ENGINEERING↗
DOE OSTI2024

An Accelerated Clip Algorithm for Unstructured Meshes: A Batch-Driven Approach

The clip technique is a popular method for visualizing complex structures and phenomena within 3D unstructured meshes. Meshes can be clipped by specifying a scalar isovalue to produce an output unstructured mesh with its external surface as the isovalue. Similar to isocontouring, the clipping process relies on scalar data associated with the mesh points, including scalar data generated by implicit functions such as planes, boxes, and spheres, which facilitates the visualization of results interior to the grid. In this paper, we introduce a novel batch-driven parallel algorithm based on a sequential clip algorithm designed for high-quality results in partial volume extraction. Our algorithm comprises five passes, each progressively processing data to generate the resulting clipped unstructured mesh. The novelty lies in the use of fixed-size batches of points and cells, which enable rapid workload trimming and parallel processing, leading to a significantly improved memory footprint and run-time performance compared to the original version. On a 32-core CPU, the proposed batch-driven parallel algorithm demonstrates a run-time speed-up of up to 32.6x and a memory footprint reduction of up to 4.37x compared to the existing sequential algorithm. The software is currently available under an open-source license in the VTK visualization system.

Tsalikis, Spiros↗
DOE OSTI2023

Alternatives to Contour Visualizations for Power Systems Data

Electrical grids are geographical and topological structures whose voltage states are challenging to represent accurately and efficiently for visual analysis. The current common practice is to use colored contour maps, yet these can misrepresent the data. We examine the suitability of four alternative visualization methods for depicting voltage data in a geographically dense distribution system - Voronoi polygons, H3 tessellations, S2 tessellations, and a network-weighted contour map. We find that Voronoi tessellations and network-weighted contour maps more accurately represent the statistical distribution of the data than regular contour maps.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗
DOE OSTI2023

Alternatives to Contour Visualizations for Power Systems Data

Electrical grids are geographical and topological structures whose voltage states are challenging to represent accurately and efficiently for visual analysis. The current common practice is to use colored contour maps, yet these can misrepresent the data. We examine the suitability of four alternative visualization methods for depicting voltage data in a geographically dense distribution system-Voronoi polygons, H3 tessellations, S2 tessellations, and a network-weighted contour map. We find that Voronoi tessellations and network-weighted contour maps more accurately represent the statistical distribution of the data than regular contour maps.

MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Visual HPC Workflows for the Analysis of System Dynamics Models

Visual analytics supported by high performance computing (HPC) accelerates and enhances the discovery, exploration, and analysis of causal patterns in complex system dynamics (SD) models. We present a suite of visualization-assisted ensemble-based techniques for hypothesis generation and testing, and for sensitivity analysis. By employing HPC to provide parallel, on-demand simulation of SD models, one can “steer” an ensemble of simulated scenarios in real time as one first formulates and then informally tests those hypotheses: this provides rapid feedback for analysts to refine their understanding of the causal relationships emergent from a model. Such understandings can be followed and augmented by rigorous application of statistical methods, namely global variance-based sensitivity analysis, Monte-Carlo filtering, adaptive regional sensitivity analysis, and self-organized maps: here timely computation relies on HPC, while effective presentation emphasizes high-dimensional multivariate data visualization. Immersive visualization in virtual 3D environments provides an excellent adjunct to the traditional 2D graphics typically used for SD models, as it generates an embodied understanding of model behavior and facilitates an active, collaborative critique of model structure and output. Finally, we summarize prospects for HPC-enabled visual analytics applied to SD modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

MCP-eGridGPT (MCP-Enabled Chatbot with Electrical Power System Analysis and Interactive Visualization Tool) [SWR-25-126]

This software is an advanced chatbot system that integrates the Model Context Protocol (MCP) to provide intelligent electrical power system analysis and automated visualization generation. The system enables users to interact with complex electrical engineering tools through natural language, automatically analyzes power system data for voltage violations and grid health assessment, and generates professional interactive HTML dashboards and reports. Key features include dynamic tool discovery from MCP servers, multi-LLM provider support, intelligent data interpretation using large language models, automated chart generation, and a web-based interface for real-time analysis. The software bridges sophisticated electrical engineering analysis with user-friendly interfaces, making power system diagnostics accessible through conversational AI.

Choi, Seong [National Laboratory of the Rockies (N↗
DOE OSTI2024

Uncertainty Visualization Challenges in Decision Systems with Ensemble Data & Surrogate Models

Uncertainty visualization is a key component in translating important insights from ensemble simulation data into actionable decision-making by visually conveying various aspects of uncertainty within a system. With the recent advent of fast surrogate models trained on ensemble data, we can substitute computationally expensive simulations, which allows users to interact with more aspects of data spaces than ever before. However, the use of ensemble data with surrogate models in a decision-making tool brings up new challenges for uncertainty visualization, namely how to reconcile and communicate the new and different types of uncertainties brought in by surrogates and how to utilize these new data estimates in actionable ways. In this work, we examine these issues as they relate to high-dimensional data visualization, the integration of discrete datasets and the continuous representations of those datasets, and the unique difficulties associated with systems that allow users to iterate between input and output spaces. We assess the role of uncertainty visualization in facilitating intuitive and actionable interaction with ensemble data and surrogate models, and highlight key challenges in this new frontier of computational simulation.

ensemble data↗
DOE OSTI2024

Uncertainty Visualization Challenges in Decision Systems with Ensemble Data & Surrogate Models: Preprint

Uncertainty visualization is a key component in translating important insights from ensemble data into actionable decision-making by visually conveying various aspects of uncertainty within a system. With the recent advent of fast surrogate models for computationally expensive simulations, users can interact with more aspects of data spaces than ever before. However, the integration of ensemble data with surrogate models in a decision-making tool brings up new challenges for uncertainty visualization, namely how to reconcile and communicate the new and different types of uncertainties brought in by surrogates and how to utilize these new data estimates in actionable ways. In this work, we examine these issues as they relate to high-dimensional data visualization, the integration of discrete datasets and the continuous representations of those datasets, and the unique difficulties associated with systems that allow users to iterate between input and output spaces. We assess the role of uncertainty visualization in facilitating intuitive and actionable interaction with ensemble data and surrogate models, and highlight key challenges in this new frontier of computational simulation.

ensemble visualization↗