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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 163 records · Page 9

Tessera: Open source software for accelerated data science

Extracting useful, actionable information from data can be a formidable challenge for the safeguards, nonproliferation, and arms control verification communities. Data scientists are often on the “front-lines” of making sense of complex and large datasets. They require flexible tools that make it easy to rapidly reformat large datasets, interactively explore and visualize data, develop statistical algorithms, and validate their approaches—and they need to perform these activities with minimal lines of code. Existing commercial software solutions often lack extensibility and the flexibility required to address the nuances of the demanding and dynamic environments where data scientists work. To address this need, Pacific Northwest National Laboratory developed Tessera, an open source software suite designed to enable data scientists to interactively perform their craft at the terabyte scale. Tessera automatically manages the complicated tasks of distributed storage and computation, empowering data scientists to do what they do best: tackling critical research and mission objectives by deriving insight from data. We illustrate the use of Tessera with an example analysis of computer network data.

Sego, Landon H.↗

Solar and Energy Efficiency: Resources to Support Local Initiatives for Low-to-Moderate Income Communities

This SolSmart webinar serves as an educational resource for local governments interested in better understanding market barriers and expanding solar and energy efficiency deployment in low to moderate income (LMI) communities. Viewers will be able to explore and visualize data developed by the National Renewable Energy Lab (NREL) focused on how rooftop solar on LMI housing represents an opportunity to help modernize the U.S electric grid and advance energy affordability in LMI communities. NREL and the American Council on an Energy Efficient Economy (ACEEE) also discuss financing options and incentives for solar development and energy efficiency in LMI communities.

14 SOLAR ENERGY↗

DoZen Documentation

DoZen (pronounced “do zen”) is for processing, visualizing, and exploring electromagnetic data that is stored in Zonge’s .z3d format. It was created specifically for processing time-lapse controlled source electromagnetic data.

97 MATHEMATICS AND COMPUTING↗

Model Energy Codes End-Use Opportunity Analysis

Model energy codes (ASHRAE Standard 90.1 and IECC) has significantly impacted programs and policies aimed at improving energy efficiency both in United States and across the globe. Standard 90.1, first published in 1975 (originally referred to as Standard 90) provides minimum energy efficiency guidelines for designing, constructing, operating, and maintaining new construction and renovated buildings. It is updated continuously, with new editions published every 3 years. Pacific Northwest National Laboratory (PNNL) conducts simulated energy and cost savings analysis of model energy codes to determine their expected impact and to track progress toward net-zero goals and efficiency targets. Additionally, the simulation outputs are examined to assess how energy is used across primary systems within prominent U.S. commercial building types to understand how energy is used in each building type at the end-use level and to identify areas for improvements in future code cycles. This end-use opportunity analysis of model energy codes provides ASHRAE technical committees and other interested parties a better understanding of how the Standard affects various building systems and end uses, specifically, those in the Standard that most prominently influence energy efficiency. Additionally, findings provide industry stakeholders guidance in identifying building types and end-uses with the most potential for energy efficiency improvements through energy codes and those that may require beyond code measures to meet energy use reduction targets. This paper summarizes features and functionalities of a webtool created by PNNL to explore and visualize the End-Use opportunity analysis.

ASHRAE 90.1, Energy Codes, Tableau↗

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis

Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses and empirically discuss their scalability, user friendliness, and postvisualization capabilities.

59 BASIC BIOLOGICAL SCIENCES↗

Visualization for Insight and Data Analysis in Energy Research

This talk explores how advanced visualization technologies are transforming analytical reasoning and knowledge discovery in energy research, drawing on recent work at the National Laboratory of the Rockies' Computational Science Center. Through a series of scientific case studies, we demonstrate how immersive and high-resolution visualization environments enable scientists and engineers to identify previously unseen patterns and features - insights that often remain hidden in traditional desktop-based analysis. By embedding richer information into interactive analytics tools, these approaches support the exploration of complex, multivariate parameter spaces, where interaction itself catalyzes understanding. Beyond capability, we emphasize the critical role of visualization design grounded in perception and cognition, showing how visual encodings directly influence analytical outcomes. Spanning applications from materials science to integrated energy systems, these visualization approaches accelerate innovation and improve decision-making by enabling deeper, more reliable insight into increasingly complex energy data.

97 MATHEMATICS AND COMPUTING↗

Geocube

NOTICE: Geocube has been replaced by EDX Spatial, a modern geospatial platform to map, visualize, query and explore spatial data. Online web mapping tool for visualization and simple analysis of Earth-energy data files from public and DOE related sources. Geocube allows users to upload and visualize their own datasets but also comes preloaded with individual spatial datasets as well as spatial data collections that align to topical themes.

carbon storage↗

NASA's Current Evidence and Hypothesis for the Visual Impairment and Intracranial Pressure Risk

While 40 years of human spaceflight exploration has reported visual decrement to a certain extent in a subgroup of astronauts, recent data suggests that there is indeed a subset of crewmembers that experience refraction changes (hyperoptic shift), cotton wool spot formation, choroidal fold development, papilledema, optic nerve sheath distention and/or posterior globe flattening with varying degrees of severity and permanence. Pre and postflight ocular measures have identified a potential risk of permanent visual changes as a result of microgravity exposure, which has been defined as the Visual Impairment and Intracranial Pressure risk (VIIP). The combination of symptoms are referred to as the VIIP syndrome. It is thought that the ocular structural and optic nerve changes are caused by events precipitated by the cephalad fluid shift crewmembers experience during long-duration spaceflight. Three important systems, ocular, cardiovascular, and central nervous, seem to be involved in the development of symptoms, but the etiology is still under speculation. It is believed that some crewmembers are more susceptible to these changes due to genetic/anatomical predisposition or lifestyle (fitness) related factors. Future research will focus on determining the etiology of the VIIP syndrome and development of mechanisms to mitigate the spaceflight risk.

Otto, Christian A.↗

A Visual Analytics Approach to Structured Data Analysis to Enhance Nonproliferation and Arms Control Verification Activities

Analysis activities for Nonproliferation and Arms Control verification require the use of many types of data. Tabular structured data, such as Excel spreadsheets and relational databases, have traditionally been used for data mining activities, where specific queries are issued against data to look for matching results. The application of visual analytics tools to structured data enables further exploration of datasets to promote discovery of previously unknown results. This paper discusses the application of a specific visual analytics tool to datasets related to the field of Arms Control and Nonproliferation to promote the use of visual analytics more broadly in this domain. Visual analytics focuses on analytical reasoning facilitated by interactive visual interfaces (Wong and Thomas 2004). It promotes exploratory analysis of data, and complements data mining technologies where known patterns can be mined for. Also with a human in the loop, they can bring in domain knowledge and subject matter expertise. Visual analytics has not widely been applied to this domain. In this paper, we will focus on one type of data: structured data, and show the results of applying a specific visual analytics tool to answer questions in the Arms Control and Nonproliferation domain. We chose to use the T.Rex tool, a visual analytics tool developed at PNNL, which uses a variety of visual exploration patterns to discover relationships in structured datasets, including a facet view, graph view, matrix view, and timeline view. The facet view enables discovery of relationships between categorical information, such as countries and locations. The graph tool visualizes node-link relationship patterns, such as the flow of materials being shipped between parties. The matrix visualization shows highly correlated categories of information. The timeline view shows temporal patterns in data. In this paper, we will use T.Rex with two different datasets to demonstrate how interactive exploration of the data can aid an analyst with arms control and nonproliferation verification activities. Using a dataset from PIERS (PIERS 2014), we will show how container shipment imports and exports can aid an analyst in understanding the shipping patterns between two countries. We will also use T.Rex to examine a collection of research publications from the IAEA International Nuclear Information System (IAEA 2014) to discover collaborations of concern. We hope this paper will encourage the use of visual analytics structured data analytics in the field of nonproliferation and arms control verification. Our paper outlines some of the challenges that exist before broad adoption of these kinds of tools can occur and offers next steps to overcome these challenges.

arms control↗

MISR Instrument Data Visualization

The MISR Interactive eXplorer (MINX) software functions both as a general-purpose tool to visualize Multiangle Imaging SpectroRadiometer (MISR) instrument data, and as a specialized tool to analyze properties of smoke, dust, and volcanic plumes. It includes high-level options to create map views of MISR orbit locations; scrollable, single-camera RGB (red-greenblue) images of MISR level 1B2 (L1B2) radiance data; and animations of the nine MISR camera images that provide a 3D perspective of the scenes that MISR has acquired. NASA Tech Briefs, September 2008 55 The plume height capability provides an accurate estimate of the injection height of plumes that is needed by air quality and climate modelers. MISR provides global high-quality stereo height information, and this program uses that information to perform detailed height retrievals of aerosol plumes. Users can interactively digitize smoke, dust, or volcanic plumes and automatically retrieve heights and winds, and can also archive MISR albedos and aerosol properties, as well as fire power and brightness temperatures associated with smoke plumes derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data. Some of the specialized options in MINX enable the user to do other tasks. Users can display plots of top-of-atmosphere bidirectional reflectance factors (BRFs) versus camera-angle for selected pixels. Images and animations can be saved to disk in various formats. Also, users can apply a geometric registration correction to warp camera images when the standard processing correction is inadequate. It is possible to difference the images of two MISR orbits that share a path (identical ground track), as well as to construct pseudo-color images by assigning different combinations of MISR channels (angle or spectral band) to the RGB display channels. This software is an interactive application written in IDL and compiled into an IDL Virtual Machine (VM) ".sav" file.

Nelson, David↗

Interaction Junk: User Interaction-Based Evaluation of Visual Analytic Systems

With the growing need for visualization to aid users in understanding large, complex datasets, the ability for users to interact and explore these datasets is critical. As visual analytic systems have advanced to leverage powerful computational models and data analytics capabilities, the modes by which users engage and interact with the information are limited. Often, users are taxed with directly manipulating parameters of these models through traditional GUIs (e.g., using sliders to directly manipulate the value of a parameter). However, the purpose of user interaction in visual analytic systems is to enable visual data exploration – where users can focus on their task, as opposed to the tool or system. As a result, users can engage freely in data exploration and decision-making, for the purpose of gaining insight. In this position paper, we discuss how evaluating visual analytic systems can be approached through user interaction analysis, where the goal is to minimize the cognitive translation between the visual metaphor and the mode of interaction (i.e., reducing the “Interactionjunk”). We motivate this concept through a discussion of traditional GUIs used in visual analytics for direct manipulation of model parameters, and the importance of designing interactions the support visual data exploration.

evaluation↗

Visualization experiences and issues in Deep Space Exploration

The panelists will discuss their experiences in collecting data in deep space, transmitting it to Earth, processing and visualizing it here, and using the visualization to drive the continued mission. This closes the loop, making missions more responsive to their environment, particularly in-situ operations on planetary surfaces and within planetary atmospheres.

visualization↗

Visualization for Scientific Discovery, Decision-Making, and Communication

Visualization–the use of visual elements to explore data, form hypotheses, or convey conclusions–is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes to the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality and AI, visualization has become increasingly essential but also ever more challenging. Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing, with a special focus on DOE-relevant applications and goals. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision-making, and communication.

97 MATHEMATICS AND COMPUTING↗

Report for the ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication

Visualization—the use of visual elements to explore data, form hypotheses, or convey conclusions—is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes for the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality (VR) and artificial intelligence (AI), visualization has become increasingly essential but also ever more challenging. The Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing as well as for DOE-relevant applications and goals in general. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision making, and communication. The first three PRDs describe interconnected research themes addressing the need for new techniques to deal with complex data, uncertainty, and interpretability (PRD 1); the need for scalable and interoperable software stacks (PRD 2); and the challenges and opportunities inherent in new technologies, such as VR, cloud, or exascale computing (PRD 3). The remaining two PRDs describe foundational research themes that recognize the potential of visualizations to provide equitable access to information and to strengthen the scientific discourse (PRD 4); and the need to consider human factors when designing visualizations (PRD 5). Collectively, these PRDs form the pillars for a coherent, long-term research and development strategy in Visualization for Scientific Discovery, Decision-Making, and Communication in the context of the Office of Science’s mission scope.

97 MATHEMATICS AND COMPUTING↗

Workload and strategic adaptation under transformations of visual-coordinative mappings

A study involving a bimanual pursuit-tracking task is conducted to examine strategic exploration of differing visual and motor coordination patterns emphasizing workload as an indicator of strategic behavior. The mappings are conducted for 16 possible variations of order, speed, and combination. Performance is assessed by means of the rms and percent time-on-target, and the NASA task-load index is used to classify subjective reports on workload. The results are broken down into four primary performance mappings and four hybrid mappings called contradictory conditions. The order of difficulty of the conditions is apparently determined by the workload, except that in the case of the three most difficult decoupled conditions some dissociation is reported.

Caird, J. K.↗

Volumetric Data Exploration with Machine Learning-Aided Visualization in Neutron Science

Recent advancements in neutron and X-ray sources, instrumentation and data collection modes have significantly increased the experimental data size (which could easily contain 108–1010 data points), so that conventional volumetric visualization approaches become inefficient for both still imaging and interactive OpenGL rendition in a 3D setting. We introduce a new approach based on the unsupervised machine learning algorithm, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), to efficiently analyze and visualize large volumetric datasets. Here we present two examples of analyzing and visualizing datasets from the diffuse scattering experiment of a single crystal sample and the tomographic reconstruction of a neutron scanning of a turbine blade. We found that by using the intensity as the weighting factor in the clustering process, DBSCAN becomes very effective in de-noising and feature/boundary detection, and thus enables better visualization of the hierarchical internal structures of the neutron scattering data.

Hui, Yawei↗