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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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All sourcesNASA NTRSDOE OSTI
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 OSTI2024

In-Line Optical Transmission Imaging of Decals for Quality Control - Task 3

Quality monitoring is a critical aspect for manufacturing systems. Ideally the monitoring would be done in-line, be non-contact, non-destructive, and fast. This would enable reduced scrap and higher throughput. This poster presents an optical transmission method for evaluating and mapping coatings. With the method shown in the poster we can visualize optical variations on the macro and micro scales. This allows us to see the overall trend in loading in both the cross web and down web directions. Furthermore, we can visualize defects such dewetting spots, streaks, clumps, and pinholes where there is a lack of coating. The optical transmission signal has been found to be proportional to the IrOx loading signal using XRF measurements. Therefore, an optical transmission setup can be installed in-line and allow for a fast, non-contact method for mapping loading variations and defects.

coating uniformity↗
DOE OSTI2020

Multiscale and Multivariate Transportation System Visualization for Shopping District Traffic and Regional Traffic

In this paper, we present a suite of visualization techniques for sensor-based transportation system data at different scales to facilitate the exploration of interconnected traffic dynamics at intersections and highways. Additionally, these techniques are designed for analyzing multivariate traffic data from radar-based highway sensors and camera-based intersection sensors recording turn movements and vehicle speed, in the Chattanooga Metropolitan Area, with the capability of (a) revealing multiscale mobility patterns using different levels of data aggregation (e.g., individual sensor for microscale, multiple sensors along a corridor for mesoscale, and a larger number of sensors across the region for macroscale visualization) at different intervals (e.g., 5-min intervals, time of day, full day, and day-of-the-week), and (b) exploring the spatial variation of multiple traffic-related variables (e.g., volumes, speeds, turn movements, and traffic light colors) provided by the sensors. We close with a case study to demonstrate the effectiveness of our multiscale and multivariate visualization techniques. At microscale, we focused on intersection data from a shopping district around Shallowford Road in East Chattanooga. For mesoscale visualization, we studied the Shallowford Road corridor and an adjacent stretch of I-75. At macroscale, we included highway data from the Chattanooga Metropolitan Area. All visualizations were integrated into a web-based situational awareness tool to promote user access and interaction. At a minimum, each visualization provides the option for selecting dates for real-time (depending on sensor availability) and historical data, and additional information on hovering, though most provide more detailed information, including different views of the selected data, or interactive highlights.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

A Visual Analytics Paradigm Enabling Trillion-Edge Graph Exploration

We present a visual analytics paradigm and a system prototype for exploring web-scale graphs. A web-scale graph is described as a graph with ~one trillion edges and ~50 billion vertices. While there is an aggressive R&D effort in processing and exploring web-scale graphs among internet vendors such as Facebook and Google, visualizing a graph of that scale still remains an underexplored R&D area. The paper describes a nontraditional peek-and-filter strategy that facilitates the exploration of a graph database of unprecedented size for visualization and analytics. We demonstrate that our system prototype can 1) preprocess a graph with ~25 billion edges in less than two hours and 2) support database query and visualization on the processed graph database afterward. Based on our computational performance results, we argue that we most likely will achieve the one trillion edge mark (a computational performance improvement of 40 times) for graph visual analytics in the near future.

graph visualization↗
DOE OSTI2016

Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration

Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Global trends in Akkermansia muciniphila research: A bibliometric visualization

Background Akkermansia muciniphila is a member of the gut microbiome, using mucin as sources of carbon, nitrogen, and energy. Since the first discovery of this unique bacterium in 2004, A. muciniphila has been extensively studied. It is considered a promising “next-generation beneficial microbe.” The purpose of this paper is to sort out the research status and summarize the hotspots through bibliometric analysis of the publications of A. muciniphila. Methods The publications about A. muciniphila from January 2004 to February 2022 were obtained from the Web of Science Core Collection. Visualization analyses were performed using three bibliometric tools and GraphPad Prism. Results A total of 1,478 published documents were analyzed. Annual publication number grew from 1 in 2004 to 336 in 2021, with China being the leading producer (33.36%). De Vos, Willem M was the most productive author with the highest H-index (documents = 56, H-index = 37), followed by Cani, Patrice D (documents = 35, H-index = 25). And Scientific Reports published the most papers. PNAS was the keystone taxa in this field, with high betweenness centrality (0.11) and high frequency. The keywords with high frequency in recent years include: oxidative stress, diet, metformin, fecal microbiota transplantation, short-chain fatty acids, polyphenols, microbiota metabolites and so on. The keyword “oxidative stress” was observed to be increasing in frequency recently. Conclusion Over time, the scope of the research on the clinical uses of A. muciniphila has gradually increased, and was gradually deepened and developed toward a more precise level. A. muciniphila is likely to remain a research hotspot in the foreseeable future and may contribute to human health.

Li, Zitong↗
DOE OSTI2026

Model Assessment Wizard (MAW)

SAND2026-18710O The Model Assessment Wizard (MAW) is a tool for evaluating ontologies and provides users with a comprehensive workbench for analysis. MAW features sub-modules for visualization, alignment, Shapes Constraint Language (SHACL) and Web Ontology Language (OWL) constraints, and simplification. Users can upload data, identify missing information, visualize ontologies, and update constraints. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Murdock, Jaimie [Sandia National Lab. (SNL-CA), Li↗
DOE OSTI2018

Slycat™ User Manual

Slycat™ is a web-based system for performing data analysis and visualization of potentially large quantities of remote, high-dimensional data. Slycat™ specializes in working with ensemble data. An ensemble is a group of related data sets, which typically consists of a set of simulation runs exploring the same problem space. An ensemble can be thought of as a set of samples within a multi-variate domain, where each sample is a vector whose value defines a point in high-dimensional space. To understand and describe the underlying problem being modeled in the simulations, ensemble analysis looks for shared behaviors and common features across the group of runs. Additionally, ensemble analysis tries to quantify differences found in any members that deviate from the rest of the group. The Slycat™ system integrates data management, scalable analysis, and visualization. Results are viewed remotely on a user’s desktop via commodity web clients using a multi-tiered hierarchy of computation and data storage, as shown in Figure 1. Our goal is to operate on data as close to the source as possible, thereby reducing time and storage costs associated with data movement. Consequently, we are working to develop parallel analysis capabilities that operate on High Performance Computing (HPC) platforms, to explore approaches for reducing data size, and to implement strategies for staging computation across the Slycat™ hierarchy. Within Slycat™, data and visual analysis are organized around projects, which are shared by a project team. Project members are explicitly added, each with a designated set of permissions. Although users sign-in to access Slycat™, individual accounts are not maintained. Instead, authentication is used to determine project access. Within projects, Slycat™ models capture analysis results and enable data exploration through various visual representations. Although for scientists each simulation run is a model of real-world phenomena given certain conditions, we use the term model to refer to our modeling of the ensemble data, not the physics. Different model types often provide complementary perspectives on data features when analyzing the same data set. Each model visualizes data at several levels of abstraction, allowing the user to range from viewing the ensemble holistically to accessing numeric parameter values for a single run. Bookmarks provide a mechanism for sharing results, enabling interesting model states to be labeled and saved.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Interactive Visualization of Complex Seismic Data and Models Using Bokeh

Visualizing multidimensional data and models becomes more challenging as the volume and resolution of seismic data and models increase. But thanks to the development of powerful and accessible computer systems, a model web browser can be used to visualize complex scientific data and models dynamically. In this paper, we present four examples of seismic model visualization using an open-source Python package Bokeh. One example is a visualization of a surface-wave dispersion data set, another presents a view of three-component seismograms, and two illustrate methods to explore a 3D seismic-velocity model. Unlike other 3D visualization packages, our visualization approach has a minimum requirement on users and is relatively easy to develop, provided you have reasonable programming skills. Finally, utilizing familiar web browsing interfaces, the dynamic tools provide us an effective and efficient approach to explore large data sets and models.

58 GEOSCIENCES↗
DOE OSTI2019

GenomeGraphR: A user-friendly open-source web application for foodborne pathogen whole genome sequencing data integration, analysis, and visualization

Food safety risk assessments and large-scale epidemiological investigations have the potential to provide better and new types of information when whole genome sequence (WGS) data are effectively integrated. Today, the NCBI Pathogen Detection database WGS collections have grown significantly through improvements in technology, coordination, and collaboration, such as the GenomeTrakr and PulseNet networks. However, high-quality genomic data is not often coupled with high-quality epidemiological or food chain metadata. We have created a set of tools for cleaning, curation, integration, analysis and visualization of microbial genome sequencing data. It has been tested using Salmonella enterica and Listeria monocytogenes data sets provided by NCBI Pathogen Detection (160,000 sequenced isolates in 2018). GenomeGraphR presents foodborne pathogen WGS data and associated curated metadata in a user-friendly interface that allows a user to query a variety of research questions such as, transmission sources and dynamics, global reach, and persistence of genotypes associated with contamination in the food supply and foodborne illness across time or space. The application is freely available (https://fda-riskmodels.foodrisk.org/ genomegraphr/).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SLoWPoKES-II: 100,000 WIDE BINARIES IDENTIFIED IN SDSS WITHOUT PROPER MOTIONS

We present the Sloan Low-mass Wide Pairs of Kinematically Equivalent Stars (SLoWPoKES)-II catalog of low-mass visual binaries identified from the Sloan Digital Sky Survey (SDSS) by matching photometric distances. The candidate pairs are vetted by comparing the stellar information. The candidate pairs are vetted by comparing the stellar density at their respective Galactic positions to Monte Carlo realizations of a simulated Milky Way. In this way, we are able to identify large numbers of bona fide wide binaries without the need for proper motions. Here, 105,537 visual binaries with angular separations of ∼1–20″ were identified, each with a probability of chance alignment of ≤5%. This is the largest catalog of bona fide wide binaries to date, and it contains a diversity of systems—in mass, mass ratios, binary separations, metallicity, and evolutionary states—that should facilitate follow-up studies to characterize the properties of M dwarfs and white dwarfs. There is a subtle but definitive suggestion of multiple populations in the physical separation distribution, supporting earlier findings. We suggest that wide binaries are composed of multiple populations, most likely representing different formation modes. There are 141 M7 or later wide binary candidates, representing a seven-fold increase over the number currently known. These binaries are too wide to have been formed via the ejection mechanism. Finally, we found that 6% of spectroscopically confirmed M dwarfs are not included in the SDSS STAR catalog; they are misclassified as extended sources due to the presence of a nearby or partially resolved companion. The SLoWPoKES-II catalog is publicly available to the entire community on the World Wide Web via the Filtergraph data visualization portal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A Framework to Support Generator Ramping Uncertainty Analysis and Visualization

Power system operation requires maintaining a continuous balance between system demand and generation within certain constraints. Traditionally, the balancing processes are based on deterministic models, which do not consider possible random deviations of system generation and load from their predicted values. With the increasing penetration of the renewable generation, unexpected balancing problems can happen due to the deviations. This can result in serious risks to system reliability and efficiency. When the available balancing reserve is not enough to cover the predicted net load range with uncertainty, deficiency of balancing needs occurs. In this case, it is necessary to commit or de-commit additional conventional generators to achieve the desired confidence level for the balancing needs. The framework is built for solving this problem. The ramping tool engine is used to predict additional balancing requirements caused by the variability and uncertainty of the renewable energy, under the constraints of the generation ramping capability and interchange schedule. The web browser- based GUI is used to visualize the data in web-environment, which provides flexibility to allow user to see the ramping outputs in any platform. The GOSS structure provides strong support to allow easy communication between ramping engine, and system inputs, as well as the GUI.

Chen, Yousu↗
DOE OSTI2022

Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data

With the advent of the next-generation traffic monitoring systems, there has been a significant increase in the spatial-temporal resolution of vehicle mobility data in many cities. Effective analysis and visualization of such data can provide transportation planners with data-driven insights, which can facilitate the understanding of multiscale traffic dynamics. In this paper, we present a web-based traffic emulator for emulating and visualizing near-real-time and historical traffic flows on highways using data from road-side sensors. To construct a continuous traffic flow, the emulator adopts an analytical pipeline that can (a) integrate traffic data collected from discrete road-side radar detection sensors, (b) interpolate traffic conditions (vehicle speed and volume) on unmeasured road segments based on traffic flow theory, and (c) generate lane-specific vehicle trajectories and movements using a mathematically optimized representation of the road network. Our app also provides an integrated visual workflow that allows users to explore the interconnected traffic dynamics using an appropriate traffic flow visualization selected based on the level of detail. We devise two innovative geo-visualization techniques that utilize an animated strips-network representation and a lane usage matrix to visualize lane performances. To ensure a smooth emulation of large-scale traffic flow in an easy-to-access web environment, we implement the emulator using client-side GPU-accelerated techniques. Lastly, we close with a case study that visualizes traffic dynamics of two scenarios - an afternoon peak hour and a traffic accident - in Chattanooga, Tennessee. Our app visualizes the responses of traffic dynamics during different traffic conditions, and to the presence of the traffic accident at different spatial scales.

42 ENGINEERING↗
DOE OSTI2019

Tracking materials science data lineage to manage millions of materials experiments and analyses

Abstract In an era of rapid advancement of algorithms that extract knowledge from data, data and metadata management are increasingly critical to research success. In materials science, there are few examples of experimental databases that contain many different types of information, and compared with other disciplines, the database sizes are relatively small. Underlying these issues are the challenges in managing and linking data across disparate synthesis and characterization experiments, which we address with the development of a lightweight data management framework that is generally applicable for experimental science and beyond. Five years of managing experiments with this system has yielded the Materials Experiment and Analysis Database (MEAD) that contains raw data and metadata from millions of materials synthesis and characterization experiments, as well as the analysis and distillation of that data into property and performance metrics via software in an accompanying open source repository. The unprecedented quantity and diversity of experimental data are searchable by experiment and analysis attributes generated by both researchers and data processing software. The search web interface allows users to visualize their search results and download zipped packages of data with full annotations of their lineage. The enormity of the data provides substantial challenges and opportunities for incorporating data science in the physical sciences, and MEAD’s data and algorithm management framework will foster increased incorporation of automation and autonomous discovery in materials and chemistry research.

Soedarmadji, Edwin↗
DOE OSTI2017

IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets

IslandViewer is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer’s integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.

59 BASIC BIOLOGICAL SCIENCES↗