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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Bridging Theory with Practice: An Exploratory Study of Visualization Use and Design for Climate Model Comparison

Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domain experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

The primary challenge motivating this team’s work is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who are able to perform analysis only on a small fraction of the data they compute, resulting in the very real likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, an approach that is known as in situ processing. The idea in situ processing was not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by DOE science projects. In large, our objective was produce and enable use of production-quality in situ methods and infrastructure, at scale, on DOE HPC facilities, though we expected to have impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve that objective, we assembled a unique team of researchers consisting of representatives from DOE national laboratories, academia, and industry, and engaged in software technology R&D, as well as engaged in close partnerships with DOE science code teams, to produce software technologies that were shown to run effectively at scale on DOE HPC platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

BioenergyKDF: Enabling Spatiotemporal Data Synthesis and Research Collaboration

The Bioenergy Knowledge Discovery Framework (BioenergyKDF) is a scalable, web-based collaborative environment for scientists working on bioenergy related research in which the connections between data, literature, and models can be explored and more clearly understood. The fully-operational and deployed system, built on multiple open source libraries and architectures, stores contributions from the community of practice and makes them easy to find, but that is just its base functionality. The BioenergyKDF provides a national spatiotemporal decision support capability that enables data sharing, analysis, modeling, and visualization as well as fosters the development and management of the U.S. bioenergy infrastructure, which is an essential component of the national energy infrastructure. The BioenergyKDF is built on a flexible, customizable platform that can be extended to support the requirements of any user community especially those that work with spatiotemporal data. While there are several community data-sharing software platforms available, some developed and distributed by national governments, none of them have the full suite of capabilities available in BioenergyKDF. For example, this component-based platform and database independent architecture allows it to be quickly deployed to existing infrastructure and to connect to existing data repositories (spatial or otherwise). As new data, analysis, and features are added; the BioenergyKDF will help lead research and support decisions concerning bioenergy into the future, but will also enable the development and growth of additional communities of practice both inside and outside of the Department of Energy. These communities will be able to leverage the substantial investment the agency has made in the KDF platform to quickly stand up systems that are customized to their data and research needs.

Bioenergy.↗
DOE OSTI2012

A National Collaboratory to Advance the Science of High Temperature Plasma Physics for Magnetic Fusion

This report summarizes the work of the National Fusion Collaboratory (NFC) Project to develop a persistent infrastructure to enable scientific collaboration for magnetic fusion research. The original objective of the NFC project was to develop and deploy a national FES Grid (FusionGrid) that would be a system for secure sharing of computation, visualization, and data resources over the Internet. The goal of FusionGrid was to allow scientists at remote sites to participate as fully in experiments and computational activities as if they were working on site thereby creating a unified virtual organization of the geographically dispersed U.S. fusion community. The vision for FusionGrid was that experimental and simulation data, computer codes, analysis routines, visualization tools, and remote collaboration tools are to be thought of as network services. In this model, an application service provider (ASP provides and maintains software resources as well as the necessary hardware resources. The project would create a robust, user-friendly collaborative software environment and make it available to the US FES community. This Grid's resources would be protected by a shared security infrastructure including strong authentication to identify users and authorization to allow stakeholders to control their own resources. In this environment, access to services is stressed rather than data or software portability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Comparative analysis of data collection methods for individualized modeling of radiologists' visual similarity judgments

Rationale and Objectives: We conducted an observer study to investigate how the data collection method affects the efficacy of modeling individual radiologists judgments regarding the perceptual similarity of breast masses on mammograms. Materials and Methods: Institutional review board approval was obtained prior to the study. Six observers of variable experience levels in breast imaging were recruited to assess the perceptual similarity of mammographic masses. The observers subjective judgments were collected using: (i) a rating method, (ii) a preference method, and (iii) a hybrid method combining rating and ranking. Personalized user models were developed with the collected data to predict observers opinions. The relative efficacy of each data collection method was assessed based on the classification accuracy of the resulting user models. Results: The hybrid data collection method produced significantly more accurate individualized user models of perceptual opinions with comparable and sometimes better time efficiency than the other two data collection methods. The user models derived from hybrid data were clearly superior even when developed with a dramatically smaller number of training cases. Conclusions: A hybrid method combining rating and ranking is an intuitive and efficient way for collecting subjective similarity judgments to model human perceptual opinions with a higher accuracy than other more commonly used data collection methods.

breast imaging↗
DOE OSTI2021

ALPINE Overview

Data-driven sampling enables probabilistic identification of interesting regions in the data automatically, prioritizing important regions. Applied in situ to Nyx, important halo regions are preserved.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Three-dimensional (3D) analysis of white etching bands (WEBs) in AISI M50 bearing steel using automated serial sectioning

Dark etching regions (DER) and white etching bands (WEB) form in the subsurface stressed regions of bearing raceways and rolling elements. Also, “butterfly” formations form around non-metallic inclusions and large carbides. The formation of WEBs, DERs and butterfly are dependent on operating conditions, material alloying elements and heat treatment. The DER, WEB and butterfly formations are well studied in two dimensions (2D). The objective of this study was to analyze WEB formation in three dimensions (3D) that will allow better understanding of material transformation after stress cycling. Three rolling contact fatigue (RCF) tested vacuum induction melted vacuum arc re-melted (VIM-VAR) AISI M50 samples (from a bench test, sub-scale test and commercial gas turbine engine) were analyzed using automated serial sectioning to map WEB networks and a butterfly formation in 3D. Automated serial sectioning and 2D optical microstructural data for 3D reconstructions and analysis was done using a fully automated serial sectioning system – Robo-Met.3D®. 3D analysis was performed using Image-Pro Premier 3D. The data set allowed 3D visualization and analysis of the evolution and propagation of WEB and butterfly in M50 bearing steel, including the positive microscopic identification of a ceramic inclusion that was the source of a WEB.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Contextual Compression of Large-Scale Wind Turbine Array Simulations

Data sizes are becoming a critical issue particularly for HPC applications. We have developed a user-driven lossy wavelet-based storage model to facilitate the analysis and visualization of large-scale wind turbine array simulations. The model stores data as heterogeneous blocks of wavelet coefficients, providing high-fidelity access to user-defined data regions believed the most salient, while providing lower-fidelity access to less salient regions on a block-by-block basis. In practice, by retaining the wavelet coefficients as a function of feature saliency, we have seen data reductions in excess of 94 percent, while retaining lossless information in the turbine-wake regions most critical to analysis and providing enough (low-fidelity) contextual information in the upper atmosphere to track incoming coherent turbulent structures. Our contextual wavelet compression approach has allowed us to deliver interative visual analysis while providing the user control over where data loss, and thus reduction in accuracy, in the analysis occurs. We argue this reduced but contextualized representation is a valid approach and encourages contextual data management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants

Abstract FatPlants, an open-access, web-based database, consolidates data, annotations, analysis results, and visualizations of lipid-related genes, proteins, and metabolic pathways in plants. Serving as a minable resource, FatPlants offers a user-friendly interface for facilitating studies into the regulation of plant lipid metabolism and supporting breeding efforts aimed at increasing crop oil content. This web resource, developed using data derived from our own research, curated from public resources, and gleaned from academic literature, comprises information on known fatty-acid-related proteins, genes, and pathways in multiple plants, with an emphasis on Glycine max, Arabidopsis thaliana, and Camelina sativa. Furthermore, the platform includes machine-learning based methods and navigation tools designed to aid in characterizing metabolic pathways and protein interactions. Comprehensive gene and protein information cards, a Basic Local Alignment Search Tool search function, similar structure search capacities from AphaFold, and ChatGPT-based query for protein information are additional features. Database URL: https://www.fatplants.net/

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Data and Communications in Basic Energy Sciences: Creating a Pathway for Scientific Discovery

This report is based on the Department of Energy (DOE) Workshop on “Data and Communications in Basic Energy Sciences: Creating a Pathway for Scientific Discovery” that was held at the Bethesda Marriott in Maryland on October 24-25, 2011. The workshop brought together leading researchers from the Basic Energy Sciences (BES) facilities and Advanced Scientific Computing Research (ASCR). The workshop was co-sponsored by these two Offices to identify opportunities and needs for data analysis, ownership, storage, mining, provenance and data transfer at light sources, neutron sources, microscopy centers and other facilities. Their charge was to identify current and anticipated issues in the acquisition, analysis, communication and storage of experimental data that could impact the progress of scientific discovery, ascertain what knowledge, methods and tools are needed to mitigate present and projected shortcomings and to create the foundation for information exchanges and collaboration between ASCR and BES supported researchers and facilities. The workshop was organized in the context of the impending data tsunami that will be produced by DOE’s BES facilities. Current facilities, like SLAC National Accelerator Laboratory’s Linac Coherent Light Source, can produce up to 18 terabytes (TB) per day, while upgraded detectors at Lawrence Berkeley National Laboratory’s Advanced Light Source will generate ~10TB per hour. The expectation is that these rates will increase by over an order of magnitude in the coming decade. The urgency to develop new strategies and methods in order to stay ahead of this deluge and extract the most science from these facilities was recognized by all. The four focus areas addressed in this workshop were: Workflow Management - Experiment to Science: Identifying and managing the data path from experiment to publication. Theory and Algorithms: Recognizing the need for new tools for computation at scale, supporting large data sets and realistic theoretical models. Visualization and Analysis: Supporting near-real-time feedback for experiment optimization and new ways to extract and communicate critical information from large data sets. Data Processing and Management: Outlining needs in computational and communication approaches and infrastructure needed to handle unprecedented data volume and information content. It should be noted that almost all participants recognized that there were unlikely to be any turn-key solutions available due to the unique, diverse nature of the BES community, where research at adjacent beamlines at a given light source facility often span everything from biology to materials science to chemistry using scattering, imaging and/or spectroscopy. However, it was also noted that advances supported by other programs in data research, methodologies, and tool development could be implemented on reasonable time scales with modest effort. Adapting available standard file formats, robust workflows, and in-situ analysis tools for user facility needs could pay long-term dividends. Workshop participants assessed current requirements as well as future challenges and made the following recommendations in order to achieve the ultimate goal of enabling transformative science in current and future BES facilities: Theory and analysis components should be integrated seamlessly within experimental workflow. Develop new algorithms for data analysis based on common data formats and toolsets. Move analysis closer to experiment. Move the analysis closer to the experiment to enable real-time (in-situ) streaming capabilities, live visualization of the experiment and an increase of the overall experimental efficiency. Match data management access and capabilities with advancements in detectors and sources. Remove bottlenecks, provide interoperability across different facilities/beamlines and apply forefront mathematical techniques to more efficiently extract science from the experiments. This workshop report examines and reviews the status of several BES facilities and highlights the successes and shortcomings of the current data and communication pathways for scientific discovery. It then ascertains what methods and tools are needed to mitigate present and projected data bottlenecks to science over the next 10 years. The goal of this report is to create the foundation for information exchanges and collaborations among ASCR and BES supported researchers, the BES scientific user facilities, and ASCR computing and networking facilities. To jumpstart these activities, there was a strong desire to see a joint effort between ASCR and BES along the lines of the highly successful Scientific Discovery through Advanced Computing (SciDAC) program in which integrated teams of engineers, scientists and computer scientists were engaged to tackle a complete end-to-end workflow solution at one or more beamlines, to ascertain what challenges will need to be addressed in order to handle future increases in data

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Methods and system for siting advanced nuclear reactors and evaluating energy policy concerns

There is a growing sociopolitical desire to develop cleaner energy sources in the United States and maintain energy security. Regardless of politics, many coal-fired electric plants have already been shut down and many utilities are vowing to retire their current coal-fired assets within the next two decades. Replacement power assets require consideration of appropriate siting. A geographic information system (GIS)-based multicriteria decision analysis approach is useful to assist utility and energy companies, as well as policymakers, to evaluate potential areas for siting new plants in the contiguous United States. A GIS-based framework is simply a database of location information that allows for mapping, querying, modeling, and analyzing data based on location. The spatial output can be structured to be visual, allowing for easier analysis of location data. The need to site additional power assets, including renewable resources and clean power sources, such as nuclear, led to the development of the Oak Ridge Siting Analysis for power Generation Expansion (OR-SAGE) tool discussed in this paper. The tool takes inputs such as population growth, water availability, environmental indicators, and tectonic and geological hazards to provide an in-depth visual analysis for siting options. Energy companies and other stakeholders can use OR-SAGE to procure feedback quickly and effectively on land suitability based on technology specific inputs. Policymakers can use OR-SAGE to analyze the impacts of future energy technology decisions, while balancing competing resource use. Overall, this paper discusses the recent use of OR-SAGE for these purposes and plans for future development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

A Dynamic Contingency Analysis Visualization Tool

We are developing a web-based visualization that shows the results of running a contingency analysis on a power grid system. Power grid analysists will be able to use this tool to visualize power event simulations and be better prepared for contingencies that may arise. The tool consists of a map, showing the power grid and its current state, and tables and charts showing the current status of various elements on the grid. The user can iterate over a number of cascading contingencies to visualize how the power grid will change under various scenarios.

Contingency analysis, power grid, smart grid, visu↗
DOE OSTI2021

py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Interactive Data Visualization

Interactive data visualization leverages human visual perception and cognition to improve the accuracy and effectiveness of data analysis. When combined with automated data analytics, data visualization systems orchestrate the strengths of humans with the computational power of machines to solve problems neither approach can manage in isolation. In the intelligent transportation system domain, such systems are necessary to support decision making in large and complex data streams. In this chapter, we provide an introduction to several key topics related to the design of data visualization systems. In addition to an overview of key techniques and strategies, we will describe practical design principles. The chapter is concluded with a detailed case study involving the design of a multivariate visualization tool.

information visualization↗