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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Determining Patterns from Radiation Portal Monitor Data: Enabling Data Insight with Visual and Interactive Exploratory Data Analysis

Smuggling of nuclear and radiological material is a complex problem that will need to be analyzed from a variety of angles in order to effectively combat something so rare, yet so hazardous. One crucial tool in the effort to detect and deter smuggling of rad/nuc materials is the radiation portal monitor (RPM)—machines that scan passengers at airports, vehicles and trains at border crossings, and shipping containers at ports throughout the world. While data from RPMs are regularly analyzed at the individual lane level to ensure monitor health and good operation, aggregate analysis of the data has not gone far beyond summary statistics such as number of occupancies and alarm rates. In particular, there are opportunities to carry out interactive exploratory data analysis with the help of tools like the R package Shiny and methods that lend themselves to the visual display of spatiotemporal correlations such as spatial PCA and detrended cross-correlation analysis. By doing so, we discover interesting spatiotemporal patterns in the data that point to specific events or anomalous moments in time that warrant further analysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

A Unified Data-Driven Approach for Programming In Situ Analysis and Visualization Final Scientific/Technical Report

The goal of Kitware’s work has been the study of a unified data-driven approach for programming applications and in situ analysis and visualization. We have especially focused on understanding the interplay between data-centric programming model requirements at extreme-scale and the overall impact of those requirements on the design, capabilities, flexibility, and implementation details for both applications and the supporting in situ infrastructure. We have successfully demonstrated the use of pipeline abstractions within Legion and developed a number of algorithms that were integrated within the Legion simulation framework. This report focuses on describing milestones, mainly those focusing on exploring pipeline abstractions in the context of the Legion programming model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Report of the DOE Workshop on Management, Analysis, and Visualization of Experimental and Observational data – The Convergence of Data and Computing

The Department of Energy (DOE) Office of Science (SC) operates dozens of national science user facilities that span many different disciplines. These facilities include accelerators, colliders, supercomputers, light sources and neutron sources, as well as facilities for studying the nanoworld, the environment, and the atmosphere. In Fiscal Year 2014 over 33,000 researchers from academia, industry, and government laboratories, spanning all fifty states and the District of Columbia, utilized these unique facilities to perform new scientific research. Each of these facilities generates vast amounts of scientific data, and the rate, size, and complexity of this data is rapidly increasing, thanks to advances in technology. A growing concern, which motivates this workshop, is the likely significant adverse impact on science programs that will result without significant advances in the capabilities needed to manage and gain knowledge from these collections of data. The purpose of this workshop, held 29 September 2015 through 1 October 2015 in Bethesda, MD, is to help the Advanced Scientific Computing Research (ASCR) and research community better understand needs related to the management, analysis, and visualization of experimental and observational data (EOD) collected and generated by experimental and observational science projects (EOS) at Office of Science user facilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

SNL ATDM Data and Visualization: IOSS and FAODEL

The SNL ATDM Data and Visualization project is developing data management software to improve how applications store and exchange large datasets efficiently on Exascale platforms. The data portion of this project is composed of two related efforts: (1) production work focused on improving Sandia's IOSS library for mesh datasets and (2) research work focused on developing new communication software named FAODEL that enables applications in a workflow to exchange data more efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Function Preserving Projection (FPP): A Linear Projection Technique for Visual Interpretation of High-Dimensional Functions

In this work, we propose function preserving projection (FPP), a new class of scalable linear projection techniques for finding interpretable structure in highdimensional datasets. Instead of focusing on preserving the structure of highdimensional points as traditional dimensionality reduction methods, we aim to find a 2D view of the data, in which human interpretable patterns of meaningful properties (that defined on the high-dimensional points, i.e., functions in a highdimensional domain) are revealed. Such a visual-centric approach introduces new avenues for exploratory data analysis and allows efficient implementation that provides a scalable tool for exploring potentially unknown or unexpected relationships in complex and large high-dimensional data (e.g., beyond millions of samples and tens of thousands of dimensions).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem (Year-end report FY16 Q4)

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

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Information Theoretic Measures for Visual Analytics: The Silver Ticket?

In the context of text-based analysis workflows, we propose that an effective analytic tool facilitates triage by a) enabling users to identify and set aside irrelevant content (i.e., reduce the complexity of information in a dataset) and b) develop a working mental model of which items are most relevant to the question at hand. This LDRD funded research developed a dataset that is enabling this team to evaluate propose normalized compression distance (NCD) as a task, user, and context-insensitive measure of categorization outcomes (Shannon entropy is reduced as order is imposed). Effective analytics tools help people impose order, reducing complexity in measurable ways. Our concept and research was documented in a paper accepted to the ACM conference "Beyond Time and Error: Novel Methods in Information Visualization Evaluation", part of the IEEE VisWeek Conference, Baltimore, MD, October 16-21, 2016. The paper is included as an appendix to this report.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Polarized Radar for Detection and Automatic Non-Visual Assessment of Unmanned Aerial Systems

This Laboratory Directed Research and Development (LDRD) effort performed fundamental Research and Development (R&D) to develop a robust radar processing algorithm capable of assessing the difference between an Unmanned Aerial System (UAS) and a biological target such as a bird, based on mathematics applied to the polarized radar returns of the target object, alone. The current threats of using such a UAS as a delivery platform for a host of destructive components is a major concern for the protection of various assets. Most recently, on 14th Sept. 2019, dozens of suicide or kamikaze drones (UAV-X) coordinated an attack on two Saudi oil facilities that demonstrated the potential to disrupt global oil supplies. While radar-based UAS detection systems can detect UAS at ranges greater than 1-km, the issues of excessive Nuisance/False Alarm Rates (NAR/FAR) from natural sources (birds in particular) has not been sufficiently addressed. In this effort we describe and utilize the Adaptive Polarization Difference Imaging-based (APDI) algorithms for the detection and automatic non-visual assessment of Unmanned Aerial System applications. Originally developed for optical imaging and sensing of polarization information in nature, the algorithms developed here are modified to serve for the target detection purposes in counter-UAS (cUAS) environments. We exploit the polarization statistics of the observing scene for detection and identification of changes within the scene and assess from these changes for UAS/bird classifications. Several cases are considered from independent data sources, including numerically generated data, anechoic chamber data as well as experimental radar data, to show the applicability of the techniques developed here. The methods developed in this effort are designed to be used in cUAS setups but have shown promise for a multitude of other radar-based classification uses as well.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Enhanced Visualization Capabilities in OpenMC: Report of Activities under a DOE GAIN Voucher

This work was performed under a Cooperative Research and Development Agreement (CRADA) through the U.S. Department of Energy’s Gateway for Accelerated Innovations in Nuclear (GAIN) program in partnership with Oklo Inc., the industry participant. The broad goal of this project was to improve the visualization capabilities of OpenMC related to model development and simulation results. OpenMC is a Monte Carlo particle transport code that is developed and maintained by a broad community of contributors, of which Argonne National Laboratory plays a leading role.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

E3SM Water Cycle Visualization Project (Final Report)

Motivated by the need to improve visualizations of Earth's complex water cycle, this team embarked on non-trivial tasks to push from traditional methods of viewing data from simulations as static line graphs and contour plots into new realms with multiple dimensions (three spatial dimensions and the time component) viewable at once. To do this, we chose to feature the extremes in the general circulation of the atmosphere because these Earth system elements are short-lived, but impactful events. We used simulation data produced by the Department of Energy's (DOE) Energy Exascale Earth System Model (E3SM),which is designed to answer DOE science questions using DOE computing facilities. The E3SM project includes three sets of simulation experiments: cryosphere, bio-geochemical cycles, and the water cycle. The water cycle experiment campaign includes a set of simulations designed to understand how the water cycle will change in coming decades under a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Virtual Blast Furnace - An Integrated High Performance Computing Modeling, Simulation, and Visualization Capability for Steel Manufacturing (Final Report)

Many manufacturing industries require substantial capital and utilize energy intensive processes that involve complex phenomena. One example of such an industry is the steel industry, which is the fourth largest energy consuming industry in the U.S. By harnessing the power of High-Performance Computing (HPC) to enhance current simulation and visualization methods in the steel industry, it should be possible to increase resolution and/or decrease time of these methods by a factor of 1000. In this way, information can be obtained in a time frame that is useful for making business and engineering decisions, optimizing manufacturing processes and, ultimately, improving the completeness of U.S. industries. For example, if coke usage in blast furnaces were optimized such that the average coke rate was reduced from 797 lb/net tonne of hot metal (NTHM) to 604 lb/NTHM, costs could be reduced by $894 million/year. Additionally, members of the steel industry need the flexibility to efficiently operate blast furnaces at a range of production rates in order to meet fluctuating market demands. Large scale parameter studies can be utilized to discover workable operating parameters at a range of production rates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Simplifying and Visualizing the Ontology of Systems Engineering Models

The credibility of an engineering model is of critical importance in large-scale projects. How concerned should an engineer be when reusing someone else's model when they may not know the author or be familiar with the tools that were used to create it? In this report, the authors advance engineers' capabilities for assessing models through examination of the underlying semantic structure of a model--the ontology. This ontology defines the objects in a model, types of objects, and relationships between them. In this study, two advances in ontology simplification and visualization are discussed and are demonstrated on two systems engineering models. These advances are critical steps toward enabling engineering models to interoperate, as well as assessing models for credibility. For example, results of this research show an 80% reduction in file size and representation size, dramatically improving the throughput of graph algorithms applied to the analysis of these models. Finally, four future problems are outlined in ontology research toward establishing credible models--ontology discovery, ontology matching, ontology alignment, and model assessment.

42 ENGINEERING↗
DOE OSTI2022

Visualization Tool for Comparing Low-Carbon Energy Options

This project developed a web based visualization tool for comparing current and future nuclear fuel cycle options to low-carbon and conventional energy technologies in the United States. While nuclear power is well established as the gold-standard for baseload power production and also as the technology with the lowest overall carbon intensity of any commercial form of electricity generation. This project develop a web-based tool for electricity producers and consumers to compare renewable and conventional energy technologies to the conventional and advanced nuclear fuel cycle options. The work leveraged data on land use, carbon intensity, unit cost and pricing data for renewables from the open literature. Input data from the Advanced Fuel Cycle Cost Basis report will be used for current and advanced nuclear power systems. We coupled these data to energy flow and lifecycle models for user-selected energy generation and storage types. We will display economic comparisons from the perspectives of generators and consumers, as well as carbon production, land use, and reliability comparisons.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Tools for Visualization and Analysis of Small-Angle Neutron Scattering Data: Descriptions and Examples

A great deal of progress has been made in improving the data reduction experience for the SANS instruments at the SNS and HFIR at ORNL. The existing data reduction toolset, drtsans, makes it possible to integrate data analysis and visualization tools into the data reduction scripts, thereby providing new opportunities for more automated data processing for users of the SNS and HFIR. Here, the first set of tools developed is described with usage examples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗