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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 OSTI2025

Visualizing Temporal Topic Embeddings with a Compass

—Dynamic topic modeling is useful at discovering the development and change in latent topics over time. However, present methodology relies on algorithms that separate document and word representations. This prevents the creation of a meaningful embedding space where changes in word usage and documents can be directly analyzed in a temporal context. This paper proposes an expansion of the compass-aligned temporal Word2Vec methodology into dynamic topic modeling. Such a method allows for the direct comparison of word and document embeddings across time in dynamic topics. This enables the creation of visualizations that incorporate temporal word embeddings within the context of documents into topic visualizations. In experiments against the current state-of-the-art, our proposed method demonstrates overall competitive performance in topic relevancy and diversity across temporal datasets of varying size. Simultaneously, it provides insightful visualizations focused on temporal word embeddings while maintaining the insights provided by global topic evolution, advancing our understanding of how topics evolve over time.

Cluster analysis↗
NASA NTRS1986

Temporal sensitivity

Human visual temporal sensitivity is examined. The stimuli used to measure temporal sensitivity are described and the linear systems theory is reviewed in terms of temporal sensitivity. A working model which represents temporal sensitivity is proposed. The visibility of a number of temporal wave forms, sinusoids, rectangular pulses, and pulse pairs, is analyzed. The relation between spatial and temporal effects is studied. Temporal variations induced by image motion and the effects of light adaptation on temporal sensitivity are considered.

Watson, Andrew B.↗
NASA NTRS2011

Coastal On-line Assessment and Synthesis Tool 2.0

COAST (Coastal On-line Assessment and Synthesis Tool) is a 3D, open-source Earth data browser developed by leveraging and enhancing previous NASA open-source tools. These tools use satellite imagery and elevation data in a way that allows any user to zoom from orbit view down into any place on Earth, and enables the user to experience Earth terrain in a visually rich 3D view. The benefits associated with taking advantage of an open-source geo-browser are that it is free, extensible, and offers a worldwide developer community that is available to provide additional development and improvement potential. What makes COAST unique is that it simplifies the process of locating and accessing data sources, and allows a user to combine them into a multi-layered and/or multi-temporal visual analytical look into possible data interrelationships and coeffectors for coastal environment phenomenology. COAST provides users with new data visual analytic capabilities. COAST has been upgraded to maximize use of open-source data access, viewing, and data manipulation software tools. The COAST 2.0 toolset has been developed to increase access to a larger realm of the most commonly implemented data formats used by the coastal science community. New and enhanced functionalities that upgrade COAST to COAST 2.0 include the development of the Temporal Visualization Tool (TVT) plug-in, the Recursive Online Remote Data-Data Mapper (RECORD-DM) utility, the Import Data Tool (IDT), and the Add Points Tool (APT). With these improvements, users can integrate their own data with other data sources, and visualize the resulting layers of different data types (such as spatial and spectral, for simultaneous visual analysis), and visualize temporal changes in areas of interest.

Brown, Richard↗
NASA NTRS1977

Investigation of remote sensing techniques as inputs to operational resource management

The author has identified the following significant results. Visual interpretation of 1:125,000 color LANDSAT prints produced timely level 1 maps of accuracies in excess of 80% for agricultural land identification. Accurate classification of agricultural land via digital analysis of LANDSAT CCT's required precise timing of the date of data collection with mid to late June optimum for western South Dakota. The LANDSAT repetitive nine day cycle over the state allowed the surface areas of stockdams and small reservoir systems to be monitored to provide a timely approximation of surface water conditions on the range. Combined use of DIRS, K-class, and LANDSAT CCT's demonstrated the ability to produce aspen maps of greater detail and timeliness than was available using US Forest Service maps. Visual temporal analyses of LANDSAT imagery improved highway map drainage information and were used to prepare a seven county drainage network. An optimum map of flood-prone areas was developed, utilizing high altitude aerial photography and USGS maps.

Schmer, F. A.↗
NASA NTRS2011

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy~ precipitation processes will be discussed.

Tao, Wei-Kuo↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
DOE OSTI2026

L-VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts

Symptom modelling in head and neck cancer is challenged by the complexity of heterogeneous patient data, leading to an interest in deep learning approaches. Although Long Short-Term Memory Networks (LSTMs) have shown great results in patient risk prediction, their low interpretability requires data modellers to collaborate with clinical experts to validate the results. We present L-VISP, a human–machine solution that uses visual analytics for LSTM modelling in clinical research. L-VISP uses custom visual encodings to make multiple LSTM variants interpretable, supporting a full range of analysis, from understanding model operations and evaluating performance to interpreting results in a clinical context. We evaluate L-VISP with data modellers and a clinical oncologist and present the takeaways from this multidisciplinary collaboration.

LSTM modeling↗
NASA NTRS1993

Visual information for judging temporal range

Work in our laboratory suggests that pilots can extract temporal range information (i.e., the time to pass a given waypoint) directly from out-the-window motion information. This extraction does not require the use of velocity or distance, but rather operates solely on a 2-D motion cue. In this paper, we present the mathematical derivation of this information, psychophysical evidence of human observers' sensitivity, and possible advantages and limitations of basing vehicle control on this parameter.

Kaiser, Mary K.↗
DOE OSTI2022

Similarities behind the high- and low- α disc: small intrinsic abundance scatter and migrating stars

The detailed age-chemical abundance relations of stars measure time-dependent chemical evolution. These trends offer strong empirical constraints on nucleosynthetic processes, as well as the homogeneity of star-forming gas. Characterizing chemical abundances of stars across the Milky Way over time has been made possible very recently, thanks to surveys like Gaia , APOGEE, and Kepler . Studies of the low- α disc have shown that individual elements have unique age–abundance trends and the intrinsic dispersion around these relations is small. In this study, we examine and compare the age distribution of stars across both the high and low- α disc and quantify the intrinsic dispersion of 16 elements around their age–abundance relations at [Fe/H] = 0 using APOGEE DR16. Here, we examine the age–metallicity relation and visualize the temporal and spatial distribution of disc stars in small chemical cells. We find: (1) the high- α disc has shallower age–abundance relations compared to the low- α disc, but similar median intrinsic dispersions of ~0.03 dex; (2) turnover points in the age-[Fe/H] relations across radius for both the high- and low- α disc. The former constrains the mechanisms that set similar intrinsic dispersions, regardless of differences in the enrichment history, for stars in both disc, and the latter indicates the presence of radial migration in both disc. Our study is accompanied by an age catalogue for 64 317 stars in APOGEE derived using THE CANNON with a median uncertainty of 1.5 Gyr (26 per cent; APO-CAN stars), and a red clump catalogue of 22 031 stars with a contamination rate of 2.7 per cent.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Comparison of Daily, Monthly (Lunar), Yearly, Decadal, Quarter-Century, Half-Century, and Centurial Shoreline Change Rates at the Kennedy Space Center, Cape Canaveral, Florida, USA

The Kennedy Space Center (KSC) is North America’s premier spaceport and provides crucial access to space for both government and private entities. The National Aeronautics and Space Administration (NASA) facilities are clustered along a 12 km active shoreline at Cape Canaveral, Florida, USA, with the entire NASA and US Space Force station (SF) shoreline stretching over 32 km (Figure 1). Several Launch Complexes (LC’s) including the modern heavy lift facilities are only a few tens of meters from the active shoreline and are imminently threatened by continued sea level rise and ongoing coastal erosion. The space center was built on the northern part of Cape Canaveral. Images collected in 1943 show that Apollo Heavy Lift Launch Complexes were built in swales on ground that was at or below sea level with Launch Complex 39B constructed on a paleo inlet (Figures 2 and 3). Today the Heavy Lift Launch Complexes are ~220 meters from the shoreline with the area between the complexes retreating at the highest rates along the cape (Figure 4). To better understand the intersection of environmental concerns, limited budgets for shoreline protection, and sheltering critical infrastructure; NASA, The University of Florida, United States Geological Survey (USGS), National Park Service (NPS) and contractors have and continue to conduct numerous studies to characterize and understand the shoreline evolution and rates of change at KSC. This project aims to better understand and visualize the temporal and spatial variability of change along the NASA shoreline beyond a simple point to point solution.

Richard MacKenzie III↗
DOE OSTI2024

Understanding Event Trajectories Across Massive Temporal Datasets with Word Embeddings and Visualization

In collaboration with researchers from Virginia Tech, Savannah River National Laboratory has continued development of a natural language processing pipeline to identify and extract events of interest from massive open data sources in the domain of worldwide state-sponsored civil nuclear energy. The foundation of the pipeline is built on compass aligned temporal word embedding models, whereby contextual shifts are automatically identified by comparing keyword embedding vectors across successive time windows. Within the approach, a contextual shift indicates the occurrence of a potential event of interest. However, in such a broad topical domain that captures events at a global scale, across various life cycle stages, and across numerous different technology types, a user that is monitoring events may have broad interests in capturing many different event types with varying degrees of signal. As such, the quantity of information that may be returned from an automated event extraction pipeline can be substantial, requiring manual effort to sift through the information to identify any relevant bits of information. Therefore, a more streamlined workflow that aids in directing a user toward specific information at different points in time is necessary. The workflow presented here has been developed with this concept in mind, built on top of the initial prototype event extraction pipeline, whereby a user can analyze temporal text-based data sources at multiple different contextual levels to isolate key points in time and key subdomains captured within a data corpus. Using multiple corpuses that consist of approximately 7 million Tweets and 7 million news articles, the team has extended compass aligned temporal word embedding models to establish an interconnected and hierarchical structure that relates known key words of interest to documents, local topics (i.e., within a time window), and global topics across the corpuses. All of this information is packaged into a visual analytics system that is linked to the information extraction pipeline and enables a user to identify contextual information that describes the evolution of a high dimensional embedding space across time to isolate changes of interest and explore associated events. This report demonstrates the use of these analytics and a means to fuse information across multiple datasets.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Effects of Spatio-Temporal Aliasing on Out-the-Window Visual Systems

Designers of out-the-window visual systems face a challenge when attempting to simulate the outside world as viewed from a cockpit. Many methodologies have been developed and adopted to aid in the depiction of particular scene features, or levels of static image detail. However, because aircraft move, it is necessary to also consider the quality of the motion in the simulated visual scene. When motion is introduced in the simulated visual scene, perceptual artifacts can become apparent. A particular artifact related to image motion, spatiotemporal aliasing, will be addressed. The causes of spatio-temporal aliasing will be discussed, and current knowledge regarding the impact of these artifacts on both motion perception and simulator task performance will be reviewed. Methods of reducing the impact of this artifact are also addressed

image generator↗
DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness - An Introduction to the Open-Source Tool and Use Cases

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility. RAVIS uses a technology suite that is assembled to provide optimum visualization facility while maintaining a wide pool of potential deployment and client environments. The tool is designed to take advantage of web application technologies, open source visualization libraries and tooling. Utilizing this technology will enable deployment in any environment, using any operating system, and is scalable to much higher spatial and temporal scales of visualization. As a prototype of the tool and demonstrating a use case of variable renewable integration, RAVIS currently integrates site-specific solar power forecasts in the California Independent System Operator (CAISO) and Mid-continent ISO (MISO) footprint from the IBM WattSun forecasting platform, and also superimposes market simulation data for CAISO footprint from as in-house NREL market clearing tool. The tool has the ability to alert the viewer for excessive up or down ramps for both individual solar sites as well as regionally aggregated net-load ramps, and alerts can also be qualified with respect to available flexible generation. This report will provide an introduction to the RAVIS tool, and summarize the above mentioned capabilities, typical use cases and possible extensions of the tool. The RAVIS development team believes there are likely to be high economic and reliability benefits of integrating probabilistic forecasts of variable renewables into control center visualizations and improved ramp events situational awareness for system operators and forecasting teams in the ISOs and electric utilities in comparison with their business as usual practices.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Imaging Carrier Dynamics and Transport in Hybrid Perovskites with Transient Absorption Microscopy

In this review, the recent progress in using transient absorption microscopy to image charge transport and dynamics in semiconducting hybrid organic–inorganic perovskites is discussed. The basic principles, instrumentation, and resolution of transient absorption microscopy are outlined. With temporal resolution as high as 10 fs, sub-diffraction-limit spatial resolution, and excited-state structural resolution, these experiments have provided crucial details on charge transport mechanisms that have been previously obscured in conventional ultrafast spectroscopy measurements. Morphology-dependent mapping unveils spatial heterogeneity in carrier recombination and cooling dynamics. By spatially separating the pump and probe beams, carrier transport across grain boundaries has been directly visualized. Further, femtosecond temporal resolution allows for the examination of nonequilibrium transport directly, revealing extraordinarily long-range hot carrier migration. The application of transient absorption microscopy is not limited to hybrid perovskites but can also be useful for other polycrystalline materials in which morphology plays an important role in carrier transport.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Conceptual Model Update of Mercury Sources and Flux at Y-12 and Upper East Fork Poplar Creek, Oak Ridge,Tennessee

The interactions between the key processes that control the fate and transport of mercury (Hg) in the sediments, groundwater, and stream water within the Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee are complex, and many aspects are not well understood. In contaminated environments such as Y-12, conceptual models are frequently developed to aid in visualizing and understanding the dynamic nature of the hydrologic, geochemical, and physical environment. These conceptual models integrate data in an internally consistent manner to understand processes that control the fate and transport of contaminants. Over the past few decades of environmental investigation at Y-12, a number of conceptual models have been developed to identify and define various technical processes at various scales. The main purpose of the activities described in this report is to update the 2011 conceptual model for Upper East Fork Poplar Creek using the most recent Hg concentration and flux data and informed scientific interpretation. Emphasis was placed on improving the previous model by implementing a more detailed spatial and temporal approach to visualize transport pathways in the watershed and trends in flux and concentration over time, and to compare baseflow and stormflow system dynamics. Detailed descriptions of historical and current Hg sources and transport pathways are also provided for the east and west ends of the facility. This conceptual model will allow the US Department of Energy to evaluate past and present remedial activities and provide a strong technical basis for prioritizing and optimizing remedial responses in a cost-effective and efficient manner. Twenty years ago, Hg flux from Outfall (OF) 200 at the headwaters of East Fork Poplar Creek represented approximately 20% of the overall flux leaving Y-12. By the time of the 2011 conceptual model report, that percentage had increased to 70%–80%. Flux estimates compiled for this report using data from 2009 to 2018 show that OF200 accounted for roughly 60% of the flux leaving Y-12. The relative role of the four storm drain conduits to OF200 appeared similar to 2011, with OF163 being the greatest contributor to downstream flux. An increase in Hg concentrations and flux occurred throughout and downstream of west end storm drains in 2011 in response to a storm drain cleanout. Leading up to the 2011 storm drain cleanout, annual baseflow flux was higher at OF200A6 than at Station 17. From 2011 to 2018, the trend reversed with concentrations and flux being higher at Station 17 than at OF200A6. A spike in concentrations occurred in July 2018, potentially due to a one-time influx of Hg that occurred during COLEX decontamination and decommissioning activities at Y-12. This report includes recommendations for improving our conceptual understanding of Hg sources, transport pathways, and flux at Y-12. Important recommendations include further evaluation of transport pathways, concurrent measurement of Hg concentration and flux under baseflow and stormflow conditions at multiple sites, and research to understand the connections among periphyton and methylmercury concentration, bioavailability, and bioaccumulation. Ongoing facility decontamination and decommissioning efforts, site characterization, remedial actions, and research are facilitating the collection of new Hg data at Y-12. The conceptual model update provided herein takes advantage of the extensive recent Hg sampling to provide an updated assessment of Hg mass balance and support a refined understanding of Hg behavior at or near Y-12. This assessment should assist in future environmental management decisions and in mitigating the impacts of Hg on the surrounding environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗