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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 OSTI2022

Noodles: Cooking Up Collaborative Visualization

NOODLES is a new cross-domain collaborative visualization and analysis capability being developed at NREL. The NOODLES specification is a minimal protocol that can tie different software packages and platforms together. As an example, a simulation code that speaks this protocol could stream iso-surfaces to an immersive VR space and a web browser. Another example is a team (with some members across the country) classifying and discovering features in a statistical data plot, driven from a researcher's existing Python-based workflow. In this talk, we will discuss some background on the problems that this protocol intends to solve, basic principles of the specification, the current state of supporting libraries, and some demonstrations of the protocol in action.

3D↗
DOE OSTI2016

MSAViewer: interactive JavaScript visualization of multiple sequence alignments

The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is ‘web ready’: written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

MO-E-18C-06: Enriching Medical Physics Education By Visualizing The Invisible

Purpose: To enhance the understanding of medical physics concepts and develop higher levels of learning relating to invisible physics phenomena such as radiation. To provide medical physics educators in all countries of the world with understanding of knowledge structures in the human brain, the different levels of learning, and the types of knowledge required for higher level functions such as problem solving, creative innovations, and applied clinical applications. To provide medical physics educators with an open access resource (tool) that they can use in their teaching activities to enrich and elevate the level of learning for their students, residents, etc. with respect to the invisible realm of medical physics. Methods: An experienced clinical medical physicist and educator has created and provided with open access three complementary web-based resources to achieve the purposes described above. One is a module focusing on the medical physics learning process with respect to mental knowledge structures, how they relate to outcomes and applications, and learning activities that are required to develop the required knowledge structures. The second is an extensive set of visuals that educators can use in their activities (classes, small group discussions, etc.) to visualize the invisible. The third is an interactive online simulation where learners can adjust factors and visually observe changes in x-radiation.These resources are available online at www.BLINDED FOR REVIEW . Results: Medical physics education, especially for non-physicists, is becoming much more interesting and useful especially with respect to invisible radiation. The global impact is that medical imaging professionals can be more effective in optimizing x-ray imaging procedures and risk management when they have knowledge levels that enhance problem solving, innovation, and creativity. Conclusion: Medical physics educators in all institutions can be much more effective and efficient in the sharing of their knowledge and experience when enhanced with high-quality visuals.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗
DOE OSTI2024

Dynamic CCS-EJ-SJ Database and Web Application - What's New

At the 2024 FECM/NETL Carbon Management Research Project Review Meeting, within the Carbon Transport and Storage Breakout Session 3, the presentation "Dynamic CCS-EJ-SJ Database and Web Application - What's New" highlights the critical tool designed to integrate environmental and social justice considerations into Carbon Capture and Storage (CCS) projects. Key features include an interactive dashboard for data access and visualization, which supports stakeholders in making informed decisions regarding CCS implementation, and updated data layers. The latest version enhances data integration and usability, providing a comprehensive resource for assessing the social and environmental impacts of CCS projects. There are 7 categories in the CCS EJSJ v2 database (released 03/31/2024): environmental justice, energy justice, economic justice, social justice, ecosystem assets, clean energy, and infrastructure. Most of the layers within each category have been updated in this version. As compared to the old database, there are 3 new categories in the v2 database: ecosystem assets, clean energy, and infrastructure.

Sharma, Maneesh↗
DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗
DOE OSTI2014

Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2.

More information: http://daymet.ornl.gov Presenter: Ranjeet Devarakonda Environmental Sciences Division Oak Ridge National Laboratory (ORNL) Daymet: Daily Surface Weather Data and Climatological Summaries provides gridded estimates of daily weather parameters for North America, including daily continuous surfaces of minimum and maximum temperature, precipitation occurrence and amount, humidity, shortwave radiation, snow water equivalent, and day length. The current data product (Version 2) covers the period January 1, 1980 to December 31, 2013 [1]. The prior product (Version 1) only covered from 1980-2008. Data are available on a daily time step at a 1-km x 1-km spatial resolution in Lambert Conformal Conic projection with a spatial extent that covers the conterminous United States, Mexico, and Southern Canada as meteorological station density allows. Daymet data can be downloaded from 1) the ORNL Distributed Active Archive Center (DAAC) search and order tools (http://daac.ornl.gov/cgi-bin/cart/add2cart.pl?add=1219) or directly from the DAAC FTP site (http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1219) and 2) the Single Pixel Tool [2] and THREDDS (Thematic Real-time Environmental Data Services) Data Server [3]. The Single Pixel Data Extraction Tool allows users to enter a single geographic point by latitude and longitude in decimal degrees. A routine is executed that translates the (lon, lat) coordinates into projected Daymet (x,y) coordinates. These coordinates are used to access the Daymet database of daily-interpolated surface weather variables. Daily data from the nearest 1 km x 1 km Daymet grid cell are extracted from the database and formatted as a table with one column for each Daymet variable and one row for each day. All daily data for selected years are returned as a single (long) table, formatted for display in the browser window. At the top of this table is a link to the same data in a simple comma-separated text format, suitable for import into a spreadsheet or other data analysis software. The Single Pixel Data Extraction Tool also provides the option to download multiple coordinates programmatically. A multiple extractor script is freely available to download at http://daymet.ornl.gov/files/daymet.zip. The ORNL DAAC s THREDDS data server (TDS) provides customized visualization and access to Daymet time series of North American mosaics. Users can subset and download Daymet data via a variety of community standards, including OPeNDAP, NetCDF Subset service, and Open Geospatial Consortium (OGC) Web Map/Coverage Service. The ORNL DAAC TDS also exposes Daymet metadata through its ncISO service to facilitate harvesting Daymet metadata records into 3rd party catalogs. References: [1] Thornton, P.E., M.M. Thornton, B.W. Mayer, N. Wilhelmi, Y. Wei, R. Devarakonda, and R.B. Cook. 2014. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. [2] Devarakonda R., et al. 2012. Daymet: Single Pixel Data Extraction Tool. Available on-line [http://daymet.ornl.go/singlepixel.html]. [3] Wei Y., et al. 2014. Daymet: Thematic Real-time Environmental Data Services. Available on-line [http://daymet.ornl.gov/thredds_tiles.html].

Thornton, Peter E↗
DOE OSTI2015

Knowledge management information tool analytics with distributed database engine - 15737

The D and D KM-IT is a web-based knowledge management information tool custom built for the deactivation and decommissioning (D and D) user community. The system allows interested users to post information which goes through a custom work flow. To better improve the performance and user experience, the analysis of server logs is being conducted using MongoDB. MongoDB is a document database that provides high performance, high availability, and easy scalability. Objectives: - Feasibility study of Distributed Database Engine, MongoDB for web analytics; - Analyze server logs to evaluate D and D KM-IT module usage; - Generate useful information from the analysis. Method: - The server logs were loaded and stored in MongoDB for analysis; - Analysis and visualization was performed using NodeJS and Java Script library. Results: - It was possible to store log files in MongoDB; - Log files with different time stamps and groups from different servers can be aggregated; - Queries can be written to extract meaningful information from aggregated log files (e.g. users from different countries/organizations). Conclusions: - MongoDB is useful for server log analytics as the analyst can immediately access, analyze, and visualize MongoDB data based on the requirements; - The information can be extracted to develop custom reports; - Optimized queries can be run for fast data access. Path forward: - Custom queries need to be developed to extract information leading to improved user information.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Updates to the Alliance of Genome Resources central infrastructure

The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific “landing pages” and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

THE SPITZER SURVEY OF STELLAR STRUCTURE IN GALAXIES (S{sup 4}G): MULTI-COMPONENT DECOMPOSITION STRATEGIES AND DATA RELEASE

The Spitzer Survey of Stellar Structure in Galaxies (S{sup 4}G) is a deep 3.6 and 4.5 μm imaging survey of 2352 nearby (<40 Mpc) galaxies. We describe the S{sup 4}G data analysis pipeline 4, which is dedicated to two-dimensional structural surface brightness decompositions of 3.6 μm images, using GALFIT3.0. Besides automatic 1-component Sérsic fits, and 2-component Sérsic bulge + exponential disk fits, we present human-supervised multi-component decompositions, which include, when judged appropriate, a central point source, bulge, disk, and bar components. Comparison of the fitted parameters indicates that multi-component models are needed to obtain reliable estimates for the bulge Sérsic index and bulge-to-total light ratio (B/T), confirming earlier results. Here, we describe the preparations of input data done for decompositions, give examples of our decomposition strategy, and describe the data products released via IRSA and via our web page (www.oulu.fi/astronomy/S4G-PIPELINE4/MAIN). These products include all the input data and decomposition files in electronic form, making it easy to extend the decompositions to suit specific science purposes. We also provide our IDL-based visualization tools (GALFIDL) developed for displaying/running GALFIT-decompositions, as well as our mask editing procedure (MASK-EDIT) used in data preparation. A detailed analysis of the bulge, disk, and bar parameters derived from multi-component decompositions will be published separately.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

MultiFacet: A Faceted Interface for Browsing Large Multimedia Collections

Faceted browsing is a common technique for exploring collections where the data can be grouped into a number of pre-defined categories, most often generated from textual metadata. Historically, faceted browsing has been applied to a single data type such as text or image data. However, typical collections contain multiple data types, such as information from web pages that contain text, images, and video. Additionally, when browsing a collection of images and video, facets are often created based on the metadata which may be incomplete, inaccurate, or missing altogether instead of the actual visual content contained within those images and video. In this work we address these limitations by presenting MultiFacet, a faceted browsing interface that supports multiple data types. MultiFacet constructs facets for images and video in a collection from the visual content using computer vision techniques. These visual facets can then be browsed in conjunction with text facets within a single interface to reveal relationships and phenomena within multimedia collections. Additionally, we present a use case based on real-world data, demonstrating the utility of this approach towards browsing a large multimedia data collection.

content-based image retrieval↗
DOE OSTI2021

Expanding Accessibility of Energy Modeling in Hawaii

Engage is a free, publicly available web application for energy system modeling. It can augment the energy system planning process by empowering more stakeholders to understand energy system planning options. Engage is user-friendly, free accessible, collaborative, and communicative. The Hawaii Advanced Visualization Environment Nexus (HAVEN) is an outputs-based application for rendering high-impact communicative visualizations of complex data. Engage and HAVEN were developed in collaboration with the U.S. Department of Energy's National Renewable Energy Laboratory and the Hawaii State Energy Office. This use case provides an overview of Hawaii's use of Engage and HAVEN concurrently in working to meet the state's energy goals.

48 EE - Weatherization and Intergovernmental Progr↗
DOE OSTI2026

Retrofit Energy Analysis and Central Thermal modeling (REACT) v1.0

REACT is a website designed to simplify the analysis and decision-making process for retrofitting existing central plant heating and cooling systems with advanced heat pump technologies. The tool evaluates the technical and economic viability of replacing traditional boilers with various options including water-to-water or air-to-water heat pumps, which can provide efficient and lower-cost heating and cooling. It allows users to compare current central plant configurations with retrofit scenarios, assessing energy consumption, life-cycle costs, and environmental impact. Retrofitting traditional boiler and chiller systems with water-to-water or air-to-water heat pumps can significantly reduce energy consumption and lower lifecycle costs. The REACT provides: User-Friendly Tools: A user friendly web interface for quick, intuitive analysis accessible to non-experts. Advanced Modeling: A Python-powered engine for detailed parametric studies, optimization, and research applications. Comprehensive Analysis: Lifecycle cost evaluation, energy consumption modeling, and environmental impact assessment. Visual Insights: A variety of plots to visualize system performance and design trade-offs. The engine for the website (REACT) bases on several Python libraries, and the website will be hosted on an ETA server.

Kim, Donghun [Lawrence Berkeley National Laborator↗
DOE OSTI2022

Pathways to a Sustainable Aviation Ecosystem: Flight DNA: An Anonymized Aviation Data Tool and Repository

The National Renewable Energy Laboratory (NREL) has deep experience developing secure, national data repositories, which it augments with analysis, technology and market expertise, high-performance computing, and innovative data visualization. By adapting the architecture of existing mobility databases (i.e., Fleet DNA, the Transportation Secure Data Center, the National Fuel Cell Technology Evaluation Center), NREL can build a powerful aviation data clearinghouse - Flight DNA - that helps stakeholders navigate the web of pitfalls and possibilities generated by new aviation technologies.

aviation↗
DOE OSTI2018

Evaluation system and web infrastructure for the second cryo-EM model challenge

An evaluation system and a web infrastructure were developed for the second cryo-EM model challenge. The evaluation system includes tools to validate stereo-chemical plausibility of submitted models, check their fit to the corresponding density maps, estimate their overall and per-residue accuracy, and assess their similarity to reference cryo-EM or X-ray structures as well as other models submitted in this challenge. The web infrastructure provides a convenient interface for analyzing models at different levels of detail. As a result, it includes interactively sortable tables of evaluation scores for different subsets of models and different sublevels of structure organization, and a suite of visualization tools facilitating model analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Evaluation of Visual Analytics Environments: The Road to the Visual Analytics Science and Technology Challenge Evaluation Methodology

The evaluation of visual analytics environments was a topic in Illuminating the Path [Thomas 2005] as a critical aspect of moving research into practice. For a thorough understanding of the utility of the systems available, evaluation not only involves assessing the visualizations, interactions or data processing algorithms themselves, but also the complex processes that a tool is meant to support (such as exploratory data analysis and reasoning, communication through visualization, or collaborative data analysis [Lam 2012; Carpendale 2007]). Researchers and practitioners in the field have long identified many of the challenges faced when planning, conducting, and executing an evaluation of a visualization tool or system [Plaisant 2004]. Evaluation is needed to verify that algorithms and software systems work correctly and that they represent improvements over the current infrastructure. Additionally to effectively transfer new software into a working environment, it is necessary to ensure that the software has utility for the end-users and that the software can be incorporated into the end-user’s infrastructure and work practices. Evaluation test beds require datasets, tasks, metrics and evaluation methodologies. As noted in [Thomas 2005] it is difficult and expensive for any one researcher to setup an evaluation test bed so in many cases evaluation is setup for communities of researchers or for various research projects or programs. Examples of successful community evaluations can be found [Chinchor 1993; Voorhees 2007; FRGC 2012]. As visual analytics environments are intended to facilitate the work of human analysts, one aspect of evaluation needs to focus on the utility of the software to the end-user. This requires representative users, representative tasks, and metrics that measure the utility to the end-user. This is even more difficult as now one aspect of the test methodology is access to representative end-users to participate in the evaluation. In many cases the sensitive nature of data and tasks and difficult access to busy analysts puts even more of a burden on researchers to complete this type of evaluation. User-centered design goes beyond evaluation and starts with the user [Beyer 1997, Shneiderman 2009]. Having some knowledge of the type of data, tasks, and work practices helps researchers and developers know the correct paths to pursue in their work. When access to the end-users is problematic at best and impossible at worst, user-centered design becomes difficult. Researchers are unlikely to go to work on the type of problems faced by inaccessible users. Commercial vendors have difficulties evaluating and improving their products when they cannot observe real users working with their products. In well-established fields such as web site design or office software design, user-interface guidelines have been developed based on the results of empirical studies or the experience of experts. Guidelines can speed up the design process and replace some of the need for observation of actual users [heuristics review references]. In 2006 when the visual analytics community was initially getting organized, no such guidelines existed. Therefore, we were faced with the problem of developing an evaluation framework for the field of visual analytics that would provide representative situations and datasets, representative tasks and utility metrics, and finally a test methodology which would include a surrogate for representative users, increase interest in conducting research in the field, and provide sufficient feedback to the researchers so that they could improve their systems.

evaluation↗
DOE OSTI2022

Quantifying the Impact of Advanced Web Platforms on High Performance Computing Usage

The deployment of Science Gateways for High Performance Computing (HPC) systems can alter long-accepted usage patterns on supercomputing systems in positive ways as an ever-increasing number of users migrate their workflows to HPC systems. Idaho National Laboratory (INL) has deployed two separate advanced web platforms, Open OnDemand and NICE DCV, for integration with HPC resources to improve web accessibility for HPC users. Researchers conducted a multi-year study on how HPC usage pat- terns changed in the presence of these platforms. This work reports the results of that study and quantifies the observed impacts, including adoption by visualization and Jupyter Notebook/Lab users, decreased job submission friction, rapid uptake of HPC by Windows users, and increased overall system utilization. The most significant impacts were observed from the deployment of Open OnDemand, and this work also identifies some best practices for Open OnDemand deployment for HPC datacenters.

97 MATHEMATICS AND COMPUTING↗