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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Simulation process and data flow for a large system dynamics model

This paper documents the workflow and supporting technologies that a large system dynamics model, the biomass scenario model, employs to streamline the data preparation, simulation, quality control, and analysis process at the National Renewable Energy Laboratory. The workflow centers on automation of routine aspects of the flow of data between data stores, simulations, and visualizations. It enforces quality checks on data, reproducibility of computations, and traceability of results, while maintaining complete archives of modeling and analysis artifacts. The resulting frictionless simulation/analysis environment supports large-scale sensitivity analysis, interactive creation of ensembles of simulations, and rapid visualization-based exploration of simulation results.

09 BIOMASS FUELS↗

DOE OSTI2015

A Software Developer’s Guide to Informal Evaluation of Visual Analytics Environments Using VAST Challenge Information

The VAST Challenge has been a popular venue for academic and industry participants for over ten years. Many participants comment that the majority of their time in preparing VAST Challenge entries is discovering elements in their software environments that need to be redesigned in order to solve the given task. Fortunately, there is no need to wait until the VAST Challenge is announced to test out software systems. The Visual Analytics Benchmark Repository contains all past VAST Challenge tasks, data, solutions and submissions. This paper details the various types of evaluations that may be conducted using the Repository information. In this paper we describe how developers can do informal evaluations of various aspects of their visual analytics environments using VAST Challenge information. Aspects that can be evaluated include the appropriateness of the software for various tasks, the various data types and formats that can be accommodated, the effectiveness and efficiency of the process supported by the software, and the intuitiveness of the visualizations and interactions. Researchers can compare their visualizations and interactions to those submitted to determine novelty. In addition, the paper provides pointers to various guidelines that software teams can use to evaluate the usability of their software. While these evaluations are not a replacement for formal evaluation methods, this information can be extremely useful during the development of visual analytics environments.

evaluation↗

NASA NTRS1976

Quantitative observation of light flash sensations experiment MA-106

Light flashes caused by the interaction of cosmic particles with the visual apparatus have been observed by astronauts on all space missions since Apollo 11. This Apollo Soyuz Test Project experiment compared measurements of the observer's visual sensitivity with measurements of the ambient radiation environment and with the frequency and character of the flashes observed. The data obtained reveal a latitude dependence of the frequency of observed flashes. This distribution of flashes is correlated with the distribution of cosmic particles with stopping power greater than 15 keV/ micrometers in the eye. The interaction of dark adaptation, specific ionization, and range of particles in the retina as factors in the visualization of particle passage is discussed.

Budinger, T. F.↗

DOE OSTI2022

Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensembles

Visualizing the uncertainty of ensemble simulations is challenging due to the large size and multivariate and temporal features of en-semble data sets. One popular approach to studying the uncertainty of ensembles is analyzing the positional uncertainty of the level sets. Probabilistic marching cubes is a technique that performs Monte Carlo sampling of multivariate Gaussian noise distributions for positional uncertainty visualization of level sets. However, the technique suffers from high computational time, making interactive visualization and analysis impossible to achieve. This paper introduces a deep-learning-based approach to learning the level-set uncertainty for two-dimensional ensemble data with a multivariate Gaussian noise assumption. We train the model using the first few time steps from time-varying ensemble data in our workflow. We demonstrate that our trained model accurately infers uncertainty in level sets for new time steps and is up to 170X faster than that of the original probabilistic model with serial computation and 10X faster than that of the original parallel computation.

Han, Mengjiao↗

NASA NTRS2023

Analysis of VFR Traffic Uncertainty and its Impact on Uncrewed Aircraft Operational Capacity at Regional Airports

This paper proposes a method to characterize Visual Flight Rules traffic around a regional airport. The applicability of the method is discussed in the context of Uncrewed Aircraft operations at a regional airport. The relation between traffic interaction uncertainty and operational capacity at the runway is also investigated. The spatio-temporal distribution of traffic operating under Visual Flight Rules is analyzed from historical track data and visualized as heat maps generated at different altitudes. These are used to characterize the spatio-temporal uncertainty associated with traffic density, around a given airport, down to the runway. The traffic patterns at the runway are used to compute the runway capacity as a function of the probability of interaction with traffic operating under visual flight rules. Fort Worth Alliance is used as a representative regional airport for the study. Applications of the traffic characterization methods developed in this paper are also discussed.

VFR traffic, uncertainty, air mobility↗

NASA NTRS2023

Analysis of VFR Traffic Uncertainty and its Impact on Uncrewed Aircraft Operational Capacity at Regional Airports

VFR traffic↗

DOE OSTI2023

Quantum Computing – Real-Time Data Processing from a Dilution Refrigerator

This poster presents a real-time data visualization system for monitoring and displaying data from a Bluefors control unit connected to a dilution refrigerator. The goal is to provide an aesthetically pleasing and user-friendly web-based interface that continuously updates and displays critical data such as temperature and flow rates at various points within the refrigerator. Leveraging WebSocket technology, the system establishes multiple connections to the dilution refrigerators, enabling simultaneous monitoring of several units. The interactive webpage dynamically updates the data, providing researchers and operators with instant insights into the system's performance. The system's ability to stream and visualize data in real-time enhances the understanding of the dilution refrigerator's behavior, aiding in optimizing its operation and ensuring efficient scientific experiments. The application's web-based nature makes it easily accessible from any device with internet connectivity, promoting seamless collaboration and remote monitoring capabilities. Overall, this poster offers a comprehensive solution for real-time data visualization and analysis of dilution refrigerators, catering to the needs of researchers and scientists working in low-temperature physics and quantum computing fields.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance

Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of automation recalibrates the dynamic between humans and automating technology. To explore this question, we conducted a scoping review encompassing twenty years of mixed-initiative visual analytic systems. To describe and contrast the relationship between humans and automation, we developed an integrated taxonomy to delineate the objectives of these mixed-initiative visual analytics tools, how much automation they support, and the assumed roles of humans. Here, we describe our qualitative approach of integrating existing theoretical frameworks with new codes we developed. Our analysis shows that the visualization research literature lacks consensus on the definition of mixed-initiative systems and explores a limited potential of the collaborative interaction landscape between people and automation. Our research provides a scaffold to advance the discussion of human-AI collaboration during visual data analysis. Our integrated taxonomy is available in the form of a web application on https://smonadjemi.github.io/miva.

Monadjemi, Shayan [ORNL] (ORCID:0000000293855969)↗

DOE OSTI2018

Coupling Visualization, Simulation, and Deep Learning for Ensemble Steering of Complex Energy Models

We describe a new framework that allows users to explore and steer ensembles of energy systems simulations by coupling multiple energy models and interactive visualization through a dataflow API. Through the visual interface, users can interactively explore complex parameter spaces populated by hundreds, or thousands, of simulation runs and interactively spawn new simulations to 'fill in' regions of interest in the parameter space. The computational and visualization capabilities reside within a general-purpose dataflow architecture for connecting producers of multidimensional timeseries data, such as energy simulations, with consumers of that data, whether they be visualizations, statistical analyses, or datastores. Fast computation and agile dataflow can enhance the engagement with energy simulations, allowing users to populate the parameter space in real time. However, many energy simulations are far too slow to provide an interactive response. To support interactive feedback, we are creating reduced-form simulations developed through machine learning techniques, which provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost. These reduced-form simulations have response times on the order of seconds, suitable for real-time human-in-the-loop design and analysis. The approximation methods apply to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. Such reduced-form representations do not replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and exploration for large ensembles of simulations. The improved understanding, facilitated by the reduced-form models, dataflow API, and visualization tools, allows researchers to better allocate computational resources to capture informative relationships within the system as well as provide a low-cost method for validating and quality-checking large-scale modeling efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as “black-boxes” due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user’s data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

Hohman, Frederick M.↗

DOE OSTI2024

exadigitUE5

This project provides the AR/VR interface to ORNL's exascale digital twin. The main functionality is implemented using Unreal Engine 5.1 for Desktop or Microsoft Hololens2 based visualization and interation with the system. The digital twin provides data ingestion from telemetry, as well as triggering and interacting with simulations developed for the wider ExaDigiT project at ORNL, as well as for the LUMI system at CSC and other CrayEX Supercomputers. For the overarching project, see ExaDigiT at https://exadigit.github.io, with the code repositories at https://code.ornl.gov/exadigit.

Maiterth, Matthias [Oak Ridge National Laboratory ↗

DOE OSTI2023

Staffing Analyses Tool

The Staffing Analyses Tool is an interactive resource planning tool used for visualizing programmatic staffing financial information. This dashboard provides historical and current staff charging data under organizations’ and/or programs’ views. This tool is used to manage staffing cost and inform outyear planning. It was developed in collaboration with Associate Laboratory Directorate for Infrastructure and Capital Projects (ALDICP) Planning Office.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS2009

Aerothermal Testing for Project Orion Crew Exploration Vehicle

The Project Orion Crew Exploration Vehicle aerothermodynamic experimentation strategy, as it relates to flight database development, is reviewed. Experimental data has been obtained to both validate the computational predictions utilized as part of the database and support the development of engineering models for issues not adequately addressed with computations. An outline is provided of the working groups formed to address the key deficiencies in data and knowledge for blunt reentry vehicles. The facilities utilized to address these deficiencies are reviewed, along with some of the important results obtained thus far. For smooth wall comparisons of computational convective heating predictions against experimental data from several facilities, confidence was gained with the use of algebraic turbulence model solutions as part of the database. For cavities and protuberances, experimental data is being used for screening various designs, plus providing support to the development of engineering models. With the reaction-control system testing, experimental data were acquired on the surface in combination with off-body flow visualization of the jet plumes and interactions. These results are being compared against predictions for improved understanding of aftbody thermal environments and uncertainties.

Berry, Scott A.↗

NASA NTRS2006

The Synergistic Engineering Environment

The Synergistic Engineering Environment (SEE) is a system of software dedicated to aiding the understanding of space mission operations. The SEE can integrate disparate sets of data with analytical capabilities, geometric models of spacecraft, and a visualization environment, all contributing to the creation of an interactive simulation of spacecraft. Initially designed to satisfy needs pertaining to the International Space Station, the SEE has been broadened in scope to include spacecraft ranging from those in low orbit around the Earth to those on deep-space missions. The SEE includes analytical capabilities in rigid-body dynamics, kinematics, orbital mechanics, and payload operations. These capabilities enable a user to perform real-time interactive engineering analyses focusing on diverse aspects of operations, including flight attitudes and maneuvers, docking of visiting spacecraft, robotic operations, impingement of spacecraft-engine exhaust plumes, obscuration of instrumentation fields of view, communications, and alternative assembly configurations. .

Cruz, Jonathan↗

NASA NTRS2012

Exploring Remote Sensing Products Online with Giovanni for Studying Urbanization

Recently, a Large amount of MODIS land products at multi-spatial resolutions have been integrated into the online system, Giovanni, to support studies on land cover and land use changes focused on Northern Eurasia and Monsoon Asia regions. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC) providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data. The customized Giovanni Web portals (Giovanni-NEESPI and Giovanni-MAIRS) are created to integrate land, atmospheric, cryospheric, and social products, that enable researchers to do quick exploration and basic analyses of land surface changes and their relationships to climate at global and regional scales. This presentation documents MODIS land surface products in Giovanni system. As examples, images and statistical analysis results on land surface and local climate changes associated with urbanization over Yangtze River Delta region, China, using data in Giovanni are shown.

Shen, Suhung↗

NASA NTRS2017

NASA's Solar System Treks: Online Portals for Planetary Mapping and Modeling

NASA's Solar System Treks are a suite of web-based of lunar and planetary mapping and modeling portals providing interactive visualization and analysis tools enabling mission planners, planetary scientists, students, and the general public to access mapped lunar data products from past and current missions for the Moon, Mars, Vesta, and more. New portals for additional planetary bodies are being planned. This presentation will recap significant enhancements to these toolsets during the past year and look ahead to future features and releases. Moon Trek is a new portal replacing its predecessor, the Lunar Mapping and Modeling Portal (LMMP), that significantly upgrades and builds upon the capabilities of LMMP. It features greatly improved navigation, 3D visualization, fly-overs, performance, and reliability. Additional data products and tools continue to be added. These include both generalized products as well as polar data products specifically targeting potential sites for NASA's Resource Prospector mission as well as for missions being planned by NASA's international partners. The latest release of Mars Trek includes new tools and data products requested by NASA's Planetary Science Division to support site selection and analysis for Mars Human Landing Exploration Zone Sites. Also being given very high priority by NASA Headquarters is Mars Trek's use as a means to directly involve the public in upcoming missions, letting them explore the areas the agency is focusing upon, understand what makes these sites so fascinating, follow the selection process, and get caught up in the excitement of exploring Mars. Phobos Trek, the latest effort in the Solar System Treks suite, is being developed in coordination with the International Phobos/Deimos Landing Site Working Group, with landing site selection and analysis for JAXA's MMX (Martian Moons eXploration) mission as a primary driver.

Day, Brian↗

DOE OSTI2021

Visualization of Multi-Fidelity Approximations of Stochastic Economic Dispatch

As renewable energy generation deployment increases, the operation of electrical grids becomes more complex. Economic dispatch is part of a grid operator's regular decision process where the amount of energy to generate is determined based on the number of available generators and the actual level of energy demand. Renewable generators are inherently stochastic due to the chaotic nature of weather patterns, and thus, real-time decisions of economic dispatch become increasingly complex. Modeling efforts to assist in these decisions in the highest fidelity typically take hours to days to solve on leadership-class computers; too long for the 5-minute operational time-frame demanded of operators. Alternatively, multi-fidelity approximations can be used to predict generation levels quickly and with sufficient accuracy to be used for real-time operations. We have developed a visualization tool to demonstrate the utility of multi-fidelity approximations by displaying contextual results of economic dispatch approximations, comparisons across fidelity levels of generation levels and possible failures to meet demand, and meta-data on the modeling setup.

interactive visualization↗

NASA NTRS2011

Simulating Visual Attention Allocation of Pilots in an Advanced Cockpit Environment

This paper describes the results of experiments conducted with human line pilots and a cognitive pilot model during interaction with a new 40 Flight Management System (FMS). The aim of these experiments was to gather human pilot behavior data in order to calibrate the behavior of the model. Human behavior is mainly triggered by visual perception. Thus, the main aspect was to setup a profile of human pilots' visual attention allocation in a cockpit environment containing the new FMS. We first performed statistical analyses of eye tracker data and then compared our results to common results of familiar analyses in standard cockpit environments. The comparison has shown a significant influence of the new system on the visual performance of human pilots. Further on, analyses of the pilot models' visual performance have been performed. A comparison to human pilots' visual performance revealed important improvement potentials.

Frische, F.↗