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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
NASA NTRS2021

PIXLISE-C: Exploring The Data Analysis Needs of NASA Scientists for Mineral Identification

NASA JPL scientists working on the micro x-ray fluorescence (microXRF) spectroscopy data collected from Mars surface perform data analysis to look for signs of past microbial life on Mars. Their data analysis workflow mainly involves identifying mineral com- pounds through the element abundance in spatially distributed data points. Working with the NASA JPL team, we identified pain points and needs to further develop their existing data visualization and analysis tool. Specifically, the team desired improvements for the process of creating and interpreting mineral composition groups. To address this problem, we developed an interactive tool that enables scientists to (1) cluster the data using either manual lasso-tool selection or through various machine learning clustering algorithms, and (2) compare the clusters and individual data points to make informed decisions about mineral compositions. Our preliminary tool supports a hybrid data analysis workflow where the user can manually refine the machine-generated clusters.

Davidoff, Scott↗
DOE OSTI2023

An Integrated Testbed for Trojans in Printed Circuit Boards with Fuzzing Capabilities

This paper showcases an all-in-one testing environment that combines Trojan detection and fuzzing capabilities for printed circuit boards using the OpenPLC “NYU Trojan Edition” and a dedicated Trojan detection framework. The demo system is self-contained and equipped with two OpenPLC-based boards (one with a Trojan and one without), and automated tools for inserting the Trojan and collecting side-channel data. We developed a graphical user interface for interactive Trojan selection, data visualization, and anomaly detection analysis.

Trojan detection, anomaly detection, PCB, timing l↗
NASA NTRS2008

Concept of Operations Visualization in Support of Ares I Production

Boeing was selected in 2007 to manufacture Ares I Upper Stage and Instrument Unit according to NASA's design which would require the use of the latest manufacturing and integration processes to meet NASA budget and schedule targets. Past production experience has established that the majority of the life cycle cost is established during the initial design process. Concept of Operations (CONOPs) visualizations/simulations help to reduce life cycle cost during the early design stage. Production and operation visualizations can reduce tooling, factory capacity, safety, and build process risks while spreading program support across government, academic, media and public constituencies. The NASA/Boeing production visualization (DELMIA; Digital Enterprise Lean Manufacturing Interactive Application) promotes timely, concurrent and collaborative producibility analysis (Boeing)while supporting Upper Stage Design Cycles (NASA). The DELMIA CONOPs visualization reduced overall Upper Stage production flow time at the manufacturing facility by over 100 man-days to 312.5 man-days and helped to identify technical access issues. The NASA/Boeing Interactive Concept of Operations (ICON) provides interactive access to Ares using real mission parameters, allows users to configure the mission which encourages ownership and identifies areas for improvement, allows mission operations or spacecraft detail to be added as needed, and provides an effective, low coast advocacy, outreach and education tool.

Chilton, James H.↗
DOE OSTI2019

Energy Modeling in Urban Districts: Forecast of Multi-Sector Energy Use and GHG Emissions

This document reports the findings of the energy use and greenhouse gases (GHG) emissions model loosely based on three districts in the San Francisco Bay Area, District A, District B, and District C. Modeling platforms exist for city energy benchmarking, inventorying, and GHG emissions forecasting and planning. However, the wide variety and features of today’s tools, their focus on a sub-set or snapshot data from various energy generation and consumption sectors, and the fact that many of them are not open data models, create sub-optimal environments for the energy analysis districts are seeking to conduct. Hence, we have developed a new software tool with customized data and dynamic visualization; DEPICT (Decision-support and Emissions Prediction Interactive Cities Tool) to obtain energy and emissions forecasts at different stages of the districts’ build-out by varying selected design parameters. This report presents the methodology and framework we have developed to estimate whole district emissions and details the results by district, with the objective of finding insights into the main sources of emissions, and the available levers to reduce them efficiently. This document details the impact of each emissions mitigation measure investigated, along with the assumption and models that were used to reach these values

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1993

A virtual reality browser for Space Station models

The Graphics Analysis Facility at NASA/JSC has created a visualization and learning tool by merging its database of detailed geometric models with a virtual reality system. The system allows an interactive walk-through of models of the Space Station and other structures, providing detailed realistic stereo images. The user can activate audio messages describing the function and connectivity of selected components within his field of view. This paper presents the issues and trade-offs involved in the implementation of the VR system and discusses its suitability for its intended purposes.

Goldsby, Michael↗
NASA NTRSDate not supplied

Virtual Diagnostics Interface (ViDI) for Planning Laser-Based Wind Tunnel Experiments

Virtual Diagnostics Interface (ViDI), originally introduced by Richard Schwartz in 2004 and described again by Alderfer, et. al., in 2007, is an interactive 3D software tool developed at NASA Langley Research Center to serve three main purposes: assist in pre-test planning, enhance post-test image analysis and visualization, and serve as a central location for data storage and distribution.1,2 ViDI is composed of custom-developed software and Autodesk® 3ds Max® as it incorporates Computer Aided Design (CAD) models with the results obtained from optical diagnostics.3 This software tool has proven useful in the field of optical diagnostics where pre-test planning of beam paths, optical elements, and test articles must be carried out to avoid interference, ensure spatial resolution is sufficient, and the camera Field of View (FoV) is adequate for the field of interest. Typically, practical considerations such as the distance a camera is from the region of interest, the angles at which the camera is oriented and issues such as the size of the camera and its sensor and size and focal length lens as well as the path of the laser need to be taken into account to predict a successful measurement. An example application of ViDI is shown in Fig.1 where an experiment to investigate flow separation over the wing of the High Lift Common Research Model (HL-CRM) is currently being planned in the National Transonic Facility (NTF) at NASA Langley Research Center.

virtual diagnostics interface↗
NASA NTRS2022

An Earth System Digital Twin for Flood Prediction and Analysis

An Earth System Digital Twin (ESDT) is a dynamic, interactive, digital replica of the state and temporal evolution of Earth systems. It integrates multiple models along with observation data, and connecting them with analysis, AI, and visualization tools. Together, these enable users to explore the current state of the Earth system, predict future conditions, and run hypothetical scenarios to understand how the system would evolve under various assumptions. The NASA’s Advanced Information Systems Technology (AIST)’s Integrated Digital Earth Analysis System (IDEAS) project is to establish an extensible architectural solution to develop digital twins of our physical environment for Earth Science. IDEAS delivers a formal system architecture with mechanisms for the outputs of one model to feed into others; for driving models with observation data; and for harmonizing observation data and model outputs for analysis. To validate and demonstrate the IDEAS architecture, this project collaborates with the Space Climate Observatory (SCO)’s FloodDAM project and the Centre National d’Etudes Spatiales (CNES) to focus on floods detection, prediction and their impacts.

Kettig, Peter↗
NASA NTRSDate not supplied

The Future of NASA Earth Science in the Commercial Cloud: Challenges and Opportunities

NASA produces a large volume and variety of data products that are used every day to support research, decision making, and education. The widespread use of NASA’s Earth Science data is enabled by NASA’s Earth Science Data System (ESDS) program, which oversees the archiving and distribution of these data and invests in the development of new data systems and tools. However, NASA’s current approach to Earth Science data distribution — based on distributed institutional archives with individual on-premises high-performance computing capabilities — faces some significant challenges, including massive increases in data volume from upcoming missions, a greater need for transdisciplinary science that synthesizes many different kinds of observations, and a push to make science more open, inclusive, and accessible. To address these challenges, NASA is aggressively migrating its Earth Science data and related tools and services into the commercial cloud. Migration of data into the commercial cloud can significantly improve NASA’s existing data system capabilities by (1) providing more flexible options for storage and compute (including rapid, as-needed access to state-of-the-art capabilities); (2) by centralizing and standardizing data access, which gives all of NASA’s institutional data centers access to all of each other’s datasets; and (3) by facilitating “analysis-in-place”, whereby users can bring their own computational workflows and tools to the data rather than having to maintain their own copies of NASA datasets. However, migration to the commercial cloud also poses some significant challenges, including (1) managing costs under a “pay-as-you-go” model; (2) incompatibility with existing tools and data formats with object-based storage and network access; (3) vendor lock-in; (4) challenges with data access for workflows that mix on-premise and cloud computing; and (5) standardization for highly diverse data as is present in NASA’s data archive. I conclude with two examples of recent NASA activities showcasing capabilities enabled by the commercial cloud: An interactive analysis and development platform for analyzing airborne imaging spectroscopy data, and a new collection of tools and services for data discovery, analysis, publication, and data-driven storytelling (Visualization, Exploration, and Data Analysis, VEDA).

Alexey N Shiklomanov↗
DOE OSTI2022

Netostat: analyzing dynamic flow patterns in high-speed networks

Understanding flow traffic patterns in networks, such as the Internet or service provider networks, is crucial to improving their design and building them robustly. However, as networks grow and become more complex, it is increasingly cumbersome and challenging to study how the many flow patterns, sizes and the continually changing source-destination pairs in the network evolve with time. Here, we present Netostat, a visualization-based network analysis tool that uses visual representation and a mathematics framework to study and capture flow patterns, using graph theoretical methods such as clustering, similarity and difference measures. Netostat generates an interactive graph of all traffic patterns in the network, to isolate key elements that can provide insights for traffic engineering. We present results for U.S. and European research networks, ESnet and GEANT, demonstrating network state changes, to identify major flow trends, potential points of failure, and bottlenecks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗
DOE OSTI2020

Visualizing biomolecular electrostatics in virtual reality with UnityMol-APBS

The APBS software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages. APBS has enjoyed widespread adoption throughout the biomedical community and is used in numerous applications involving biomolecular structures. However, visualization of complex biomolecular electrostatic properties can be challenging for two-dimensional graphics systems. Therefore, advanced visualization and manipulation capabilities have been incorporated. In particular, APBS tools have been integrated with the UnityMolX virtual reality platform to provide an immersive experience for preparing biomolecular systems for calculations as well as visualizing and comparing calculated results.

electrostatics, molecular visualization, solvation↗
NASA NTRS2010

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Liu, Zhong↗
NASA NTRS1998

Modeling Controller Tasks for Safety Analysis

As control systems become more complex, the use of automated control has increased. At the same time, the role of the human operator has changed from primary system controller to supervisor or monitor. Safe design of the human computer interaction becomes more difficult. In this paper, we present a visual task modeling language that can be used by system designers to model human-computer interactions. The visual models can be translated into SpecTRM-RL, a blackbox specification language for modeling the automated portion of the control system. The SpecTRM-RL suite of analysis tools allow the designer to perform formal and informal safety analyses on the task model in isolation or integrated with the rest of the modeled system.

Brown, Molly↗
DOE OSTI2019

Final Report: Modeling coupled ice sheet-ocean interactions in the Model for Prediction Across Scales (MPAS) and in DOE Earth System Models

Ice sheet-ocean interactions are involved in a potential climate tipping point in the climate system. Weakening of dynamical ocean barriers that currently hold warmer waters off the Antarctic continental shelf could lead to warming under Antarctica’s largest ice shelves, causing as much as a hundredfold increase in sub-ice-shelf melting. Increased ice-sheet melting could trigger dynamical instabilities in the ice sheet itself if sufficient buttressing from ice shelves is lost. This project developed and tested several modeling capabilities needed to investigate these phenomena. In collaboration with a number of international groups, notably the climate modeling group at Los Alamos National Laboratory (LANL), the following capabilities were added to the Energy Exascale Earth System Model (E3SM) and its ocean component (the Model for Prediction Across Scales Ocean, MPAS-Ocean): 1) a new vertical coordinate appropriate for ice-shelf cavities; 2) an initialization procedure appropriate for damping waves from imbalances in ocean pressure and that of the overlying ice shelf; 3) A suite of idealized test cases related to ice shelf-ocean interactions; 4) A set of diagnostics for tracking freshwater fluxes and heat budgets from ice-shelf melting; 5) infrastructure for computing ice sheet-ocean fluxes in the E3SM coupler; and 6) A set of analysis and visualization tools for E3SM ocean and sea-ice validation with a particular focus on Antarctic and Southern Ocean climate. Additionally, the project included participation and leadership in a number of international model intercomparison projects (MIPs). Most notably, the PI was a co-chair of the Marine Ice Sheet-Ocean Model Intercomparison Project (MISOMIP), designing the experiment, coordinating participation in the MIP and performing the bulk of the analysis. Although the project was cut short when the PI accepted a staff scientist position at LANL, the project played a role in seven publications and has segued smoothly into ongoing Department of Energy projects in the “ecosystem” surrounding E3SM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

WebGIobe - A cloud-based geospatial analysis framework for interacting with climate data

While climate models have evolved over time to produce high fidelity and high resolution climate forecasts, visualization and analysis of the output of the model simulations has been limited, typically constrained to single dimensional charts for visualization and basic aggregate statistics for analytics. Same is true for the large troves of observational data available from meteorological stations all over the world. For richer understanding of climate and the impact of climate change, one needs computational tools that allow researchers, policymakers, and general public, to interact with the climate data. In this paper, we describe, webGlobe, a browser based GIS framework for interacting with climate data, and other datasets available in similar format. webGlobe is a unique resource that allows unprecedented access to climate data through a browser. The framework also allows for deploying machine learning based analytical applications on the climate data without putting computational burden on the client. Instead, webGlobe uses a client-server framework, where the server, deployed on a cloud infrastructure, allows for dynamic allocation of resources for running compute-intensive applications. The capabilities of the framework will be discussed in context of a use case: identifying extreme events from real and simulated climate data using a Gaussian process based change detection algorithm.

Sharma, Arun↗
DOE OSTI2021

EPIsembleVis: A geo-visual analysis and comparison of the prediction ensembles of multiple COVID-19 models

In this work, we present EPIsembleVis, a web-based comparative visual analysis tool for evaluating the consistency of multiple COVID-19 prediction models. Our approach analyzes a collection of COVID-19 predictions from different epidemiological models as an ensemble and utilizes two metrics to quantify model performance. These metrics include (a) prediction uncertainty (represented as the dispersion of predictions in each ensemble) and (b) prediction error (calculated by comparing individual model predictions with the recorded data). Through an interactive visual interface, our approach provides a data-driven workflow for (a) selecting and constructing the COVID-19 model prediction ensemble based on the spatiotemporal overlap of available predictions of multiple epidemiological models, (b) quantifying the model performance using both the uncertainty of each model prediction ensemble, and the error of each ensemble member that represents individual model predictions, and (c) visualizing the spatiotemporal variability in the projection performance of individual models using a suite of novel ensemble visualization techniques, such as the data availability map, a spatiotemporal textured-tile calendar, multivariate rose chart, and time-series leaflet glyph. We demonstrate the capability of our ensemble visual interface through a case study that investigates the performance of weekly COVID-19 predictions, which are provided through the COVID-19 Forecast Hub UMass-Amherst Influenza Forecasting Center of Excellence [47] for the United States and United States Territories. The EPIsembleVis tool is implemented using open-source web technologies and adaptive system design, rendering it interoperable with Elasticsearch and Kibana for automatically ingesting COVID-19 predictions from online repositories, and it is generalizable for analyzing worldwide projections from more epidemiological models.

60 APPLIED LIFE SCIENCES↗