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DOE OSTI2019

Slycat v 2.0

Slycat™ is a web-based system for analysis of large, high-dimensional data such as that produced by High Performance Computing (HPC) platforms. The Slycat™ server integrates data ingestion, scalable analysis, data management, and visualization with commodity web clients using a multi-tiered hierarchy of data and model storage. Analysis inputs are pushed or pulled into Slycat™, where models are generated and analysis artifacts are stored in a project database. These artifacts are the basis for visualizations that are delivered to users’ desktops through ordinary web browsers, eliminating the need to build and deploy platform-specific client applications. Slycat™ currently provides four types of analysis: canonical correlation analysis (CCA) to model relationships between inputs and output metrics, time series analysis featuring clustering and comparative visualization of waveforms, parameter space visualization including remote retrieval of images and movies from HPC disks, and VideoSwarm for modeling video similarities over time.

Letter, Matthew↗

DOE OSTI2026

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗

NASA NTRS2023

An Examination of Heavy Ion-Induced Persistent Visual Error Signatures in an Electronic Display Driver Integrated Circuit

Given the ubiquity of electronic displays integration in human-based systems, the impending mission critical, space-based applications of electronic displays will necessitate SEE assessment of components unique to electronic displays. A commercially available DDIC designed to drive a small form factor organic light emitting diode (OLED) was visually monitored during heavy ion irradiation to catalogue radiation induced persistent visual error signatures that require manual intervention (i.e., power cycling) to return to nominal function. These error signatures were able to be reproduced via modification of configuration register values utilizing the instruction set intended for interfacing a microcontroller with the DDIC. This approach to emulation of heavy-ion induced errors on a table-top assists with human perception-based criticality analysis as well as development of mitigation techniques.

Electronic Displays↗

NASA NTRS2021

Teleoperation and Visualization Interfaces for Remote Intervention in Space

Approaches to robotic manufacturing, assembly, and servicing of in-space assets range from autonomous operation to direct teleoperation, with many forms of semi-autonomous teleoperation in between. Because most approaches require one or more human operators at some level, it is important to explore the control and visualization interfaces available to those operators, taking into account the challenges due to significant telemetry time delay. We consider one motivating application of remote teleoperation, which is ground-based control of a robot on-orbit for satellite servicing. This paper presents a model-based architecture that: 1) improves visualization and situation awareness, 2) enables more effective human/robot interaction and control, and 3) detects task failures based on anomalous sensor feedback. We illustrate elements of the architecture by drawing on 10 years of our research in this area. The paper further reports the results of several multi-user experiments to evaluate the model-based architecture, on ground-based test platforms, for satellite servicing tasks subject to round-trip communication latencies of several seconds. The most significant performance gains were obtained by enhancing the operators’ situation awareness via improved visualization and by enabling them to precisely specify intended motion. In contrast, changes to the control interface, including model-mediated control or an immersive 3D environment, often reduced the reported task load but did not significantly improve task performance. Considering the challenges of fully autonomous intervention, we expect that some form of teleoperation will continue to be necessary for robotic in-situ servicing, assembly, and manufacturing tasks for the foreseeable future. We propose that effective teleoperation can be enabled by modeling the remote environment, providing operators with a fused view of the real environment and virtual model, and incorporating interfaces and control strategies that enable interactive planning, precise operation, and prompt detection of errors.

space robotics↗

NASA NTRS1994

Virtual Environments in Scientific Visualization

Virtual environment technology is a new way of approaching the interface between computers and humans. Emphasizing display and user control that conforms to the user's natural ways of perceiving and thinking about space, virtual environment technologies enhance the ability to perceive and interact with computer generated graphic information. This enhancement potentially has a major effect on the field of scientific visualization. Current examples of this technology include the Virtual Windtunnel being developed at NASA Ames Research Center. Other major institutions such as the National Center for Supercomputing Applications and SRI International are also exploring this technology. This talk will be describe several implementations of virtual environments for use in scientific visualization. Examples include the visualization of unsteady fluid flows (the virtual windtunnel), the visualization of geodesics in curved spacetime, surface manipulation, and examples developed at various laboratories.

Bryson, Steve↗

NASA NTRS1994

Virtual Environments in Scientific Visualization

Bryson, Steve↗

NASA NTRS1977

Research on integration of visual and motion cues for flight simulation and ride quality investigation

Vestibular perception and integration of several sensory inputs in simulation were studied. The relationship between tilt sensation induced by moving fields and those produced by actual body tilt is discussed. Linearvection studies were included and the application of the vestibular model for perception of orientation based on motion cues is presented. Other areas of examination includes visual cues in approach to landing, and a comparison of linear and nonlinear wash out filters using a model of the human vestibular system is given.

Young, L. R.↗

NASA NTRS2001

Expression of pH-sensitive green fluorescent protein in Arabidopsis thaliana

This is the first report on using green fluorescent protein (GFP) as a pH reporter in plants. Proton fluxes and pH regulation play important roles in plant cellular activity and therefore, it would be extremely helpful to have a plant gene reporter system for rapid, non-invasive visualization of intracellular pH changes. In order to develop such a system, we constructed three vectors for transient and stable transformation of plant cells with a pH-sensitive derivative of green fluorescent protein. Using these vectors, transgenic Arabidopsis thaliana and tobacco plants were produced. Here the application of pH-sensitive GFP technology in plants is described and, for the first time, the visualization of pH gradients between different developmental compartments in intact whole-root tissues of A. thaliana is reported. The utility of pH-sensitive GFP in revealing rapid, environmentally induced changes in cytoplasmic pH in roots is also demonstrated.

NASA Discipline Plant Biology↗

NASA NTRS2009

MSLICE Science Activity Planner for the Mars Science Laboratory Mission

MSLICE (Mars Science Laboratory InterfaCE) is the tool used by scientists and engineers on the Mars Science Laboratory rover mission to visualize the data returned by the rover and collaboratively plan its activities. It enables users to efficiently and effectively search all mission data to find applicable products (e.g., images, targets, activity plans, sequences, etc.), view and plan the traverse of the rover in HiRISE (High Resolution Imaging Science Experiment) images, visualize data acquired by the rover, and develop, model, and validate the activities the rover will perform. MSLICE enables users to securely contribute to the mission s activity planning process from their home institutions using off-the-shelf laptop computers. This software has made use of several plug-ins (software components) developed for previous missions [e.g., Mars Exploration Rover (MER), Phoenix Mars Lander (PHX)] and other technology tasks. It has a simple, intuitive, and powerful search capability. For any given mission, there is a huge amount of data and associated metadata that is generated. To help users sort through this information, MSLICE s search interface is provided in a similar fashion as major Internet search engines. With regard to the HiRISE visualization of the rover s traverse, this view is a map of the mission that allows scientists to easily gauge where the rover has been and where it is likely to go. The map also provides the ability to correct or adjust the known position of the rover through the overlaying of images acquired from the rover on top of the HiRISE image. A user can then correct the rover s position by collocating the visible features in the overlays with the same features in the underlying HiRISE image. MSLICE users can also rapidly search all mission data for images that contain a point specified by the user in another image or panoramic mosaic. MSLICE allows the creation of targets, which provides a way for scientists to collaboratively name features on the surface of Mars. These targets can also be used to convey instrument-pointing information to the activity plan. The software allows users to develop a plan of what they would like the rover to accomplish for a given time period. When developing the plan, the user can input constraints between activities or groups of activities. MSLICE will enforce said constraints and ensure that all mission flight rules are satisfied.

Powell, Mark W.↗

DOE OSTI2020

eFESTA: Ensemble Feature Exploration with Surface Density Estimates

We propose surface density estimate (SDE) to model the spatial distribution of surface features-isosurfaces, ridge surfaces, and streamsurfaces-in 3D ensemble simulation data. The inputs of SDE computation are surface features represented as polygon meshes, and no field datasets are required (e.g., scalar fields or vector fields). The SDE is defined as the kernel density estimate of the infinite set of points on the input surfaces and is approximated by accumulating the surface densities of triangular patches. We also propose an algorithm to guide the selection of a proper kernel bandwidth for SDE computation. An ensemble Feature Exploration method based on Surface densiTy EstimAtes (eFESTA) is then proposed to extract and visualize the major trends of ensemble surface features. For an ensemble of surface features, each surface is first transformed into a density field based on its contribution to the SDE, and the resulting density fields are organized into a hierarchical representation based on the pairwise distances between them. The hierarchical representation is then used to guide visual exploration of the density fields as well as the underlying surface features. We demonstrate the application of our method using isosurface in ensemble scalar fields, Lagrangian coherent structures in uncertain unsteady flows, and streamsurfaces in ensemble fluid flows.

Computational modeling↗

DOE OSTI2019

Multivariate Pointwise Information-Driven Data Sampling and Visualization

With increasing computing capabilities of modern supercomputers, the size of the data generated from the scientific simulations is growing rapidly. As a result, application scientists need effective data summarization techniques that can reduce large-scale multivariate spatiotemporal data sets while preserving the important data properties so that the reduced data can answer domain-specific queries involving multiple variables with sufficient accuracy. While analyzing complex scientific events, domain experts often analyze and visualize two or more variables together to obtain a better understanding of the characteristics of the data features. Therefore, data summarization techniques are required to analyze multi-variable relationships in detail and then perform data reduction such that the important features involving multiple variables are preserved in the reduced data. To achieve this, in this work, we propose a data sub-sampling algorithm for performing statistical data summarization that leverages pointwise information theoretic measures to quantify the statistical association of data points considering multiple variables and generates a sub-sampled data that preserves the statistical association among multi-variables. Using such reduced sampled data, we show that multivariate feature query and analysis can be done effectively. The efficacy of the proposed multivariate association driven sampling algorithm is presented by applying it on several scientific data sets.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2011

Applying Geospatial Technologies for International Development and Public Health: The USAID/NASA SERVIR Program

Background: SERVIR -- the Regional Visualization and Monitoring System -- helps people use Earth observations and predictive models based on data from orbiting satellites to make timely decisions that benefit society. SERVIR operates through a network of regional hubs in Mesoamerica, East Africa, and the Hindu Kush-Himalayas. USAID and NASA support SERVIR, with the long-term goal of transferring SERVIR capabilities to the host countries. Objective/Purpose: The purpose of this presentation is to describe how the SERVIR system helps the SERVIR regions cope with eight areas of societal benefit identified by the Group on Earth Observations (GEO): health, disasters, ecosystems, biodiversity, weather, water, climate, and agriculture. This presentation will describe environmental health applications of data in the SERVIR system, as well as ongoing and future efforts to incorporate additional health applications into the SERVIR system. Methods: This presentation will discuss how the SERVIR Program makes environmental data available for use in environmental health applications. SERVIR accomplishes its mission by providing member nations with access to geospatial data and predictive models, information visualization, training and capacity building, and partnership development. SERVIR conducts needs assessments in partner regions, develops custom applications of Earth observation data, and makes NASA and partner data available through an online geospatial data portal at SERVIRglobal.net. Results: Decision makers use SERVIR to improve their ability to monitor air quality, extreme weather, biodiversity, and changes in land cover. In past several years, the system has been used over 50 times to respond to environmental threats such as wildfires, floods, landslides, and harmful algal blooms. Given that the SERVIR regions are experiencing increased stress under larger climate variability than historic observations, SERVIR provides information to support the development of adaptation strategies for nations affected by climate change. Conclusions: SERVIR is a platform for collaboration and cross-agency coordination, international partnerships, and delivery of web-based geospatial information services and applications. SERVIR makes a variety of geospatial data available for use in studies of environmental health outcomes.

Hemmings, Sarah↗

NASA NTRS2009

Development of Countermeasures to Aid Functional Egress from the Crew Exploration Vehicle Following Long Duration Spaceflight

Astronauts experience disturbances in sensorimotor function following their return to Earth due to adaptive responses that occur during exposure to the microgravity conditions of space flight. As part of the Crew Exploration Vehicle design requirements, the crewmember adapted to the microgravity state may need to egress the vehicle within a few minutes for safety and operational reasons in various sea state conditions following a water landing. The act of emergency egress includes and is not limited to rapid motor control tasks (including both fine motor such as object manipulation and gross motor such as opening a hatch) and visual acuity tasks while maintaining spatial orientation and postural stability in time to escape safely. Exposure to even low frequency motions (0.2-2.0 Hz) induced by sea conditions surrounding a vessel can cause significant fine and gross motor control problems affecting critical functions. These motion frequencies coupled with the varying sea state conditions (frequencies ranging from 0.125-0.5 Hz) cause performance deficits by affecting the efficacy of motor and visual acuity dependent skills in tasks critical to emergency egress activities such as visual monitoring of displays, actuating discrete controls, operating auxiliary equipment and communicating with Mission Control and recovery teams. Thus, during exploration class missions the sensorimotor disturbances due to the crewmember's adaptation to microgravity may lead to disruption in the ability to maintain postural stability and perform functional egress tasks during the initial introduction to the Earth's gravitational environment. At present, the functional implication of the interactions between a debilitated crewmember during readaptation to Earth s gravity and the environmental constraints imposed by a water landing scenario is not defined and no operational countermeasure has been implemented to mitigate this risk. Stochastic resonance (SR) is a mechanism whereby noise can assist and hence enhance the response of neural systems to relevant, subthreshold sensory signals. Application of subthreshold stochastic resonance noise coupled to sensory input either through the proprioceptive, visual or vestibular sensory systems, has been shown to improve motor function. Crew members who have adapted to microgravity have acquired new sensorimotor strategies that take time to discard. We hypothesize that detection of time-critical subthreshold sensory signals will play a crucial role in improving strategic responses and thus the rate of skill re-acquisition will be faster, leading to faster recovery of function during their re-adaptation to Earth G. Therefore, we expect the use of stochastic resonance mechanisms will enhance the acquisition of new strategic abilities. This process should ensure rapid restoration of functional egress capabilities during the initial return to Earth G after prolonged space flight. Therefore, the overall goals of this project are to investigate performance of motor and visual tasks during varying sea state conditions and develop a countermeasure based on stochastic resonance that could be implemented to enhance sensorimotor capabilities with the aim of facilitating rapid adaptation to Earth s gravity, allowing rapid CEV egress on water in varying sea states following long-duration space flight.

Mulavara, Ajitkumar↗

DOE OSTI2021

SeismoGen: Seismic Waveform Synthesis Using GAN With Application to Seismic Data Augmentation

Abstract Detecting earthquake arrivals within seismic time series can be a challenging task. Visual, human detection has long been considered the gold standard but requires intensive manual labor that scales poorly to large data sets. In recent years, automatic detection methods based on machine learning have been developed to improve the accuracy and efficiency. However, the accuracy of those methods relies on access to a sufficient amount of high‐quality labeled training data, often tens of thousands of records or more. We aim to resolve this dilemma by answering two questions: (1) provided with a limited amount of reliable labeled data, can we use them to generate additional, realistic synthetic waveform data? and (2) can we use those synthetic data to further enrich the training set through data augmentation, thereby enhancing detection algorithms? To address these questions, we use a generative adversarial network (GAN), a type of machine learning model which has shown supreme capability in generating high‐quality synthetic samples in multiple domains. Once trained, our GAN model is capable of producing realistic seismic waveforms of multiple labels (noise and event classes). Applied to real Earth seismic data sets in Oklahoma, we show that data augmentation from our GAN‐generated synthetic waveforms can be used to improve earthquake detection algorithms in instances when only small amounts of labeled training data are available.

Wang, Tiantong↗

DOE OSTI2020

MATBOX (Microstructure Analysis Toolbox) [SWR-20-76]

MATBOX is a MATLAB application for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization, result three-dimensional visualization and result correlation, and microstructure meshing. MATBOX was originally developed to analyze electrode microstructures for lithium ion batteries; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphic-User Interface.

Usseglio Viretta, Francois↗

NASA NTRS1989

Integrating automated support for a software management cycle into the TAME system

Software managers are interested in the quantitative management of software quality, cost and progress. An integrated software management methodology, which can be applied throughout the software life cycle for any number purposes, is required. The TAME (Tailoring A Measurement Environment) methodology is based on the improvement paradigm and the goal/question/metric (GQM) paradigm. This methodology helps generate a software engineering process and measurement environment based on the project characteristics. The SQMAR (software quality measurement and assurance technology) is a software quality metric system and methodology applied to the development processes. It is based on the feed forward control principle. Quality target setting is carried out before the plan-do-check-action activities are performed. These methodologies are integrated to realize goal oriented measurement, process control and visual management. A metric setting procedure based on the GQM paradigm, a management system called the software management cycle (SMC), and its application to a case study based on NASA/SEL data are discussed. The expected effects of SMC are quality improvement, managerial cost reduction, accumulation and reuse of experience, and a highly visual management reporting system.

Sunazuka, Toshihiko↗

NASA NTRS2019

Creating Data-Driven Vector Visualizations of Satellite Orbit Tracks Using NASA GIBS and Worldview

NASA Earth Observing System (EOS) currently operates dozens of remote sensing satellites, many of which can be viewed directly in NASA’s open-source Worldview application. Much of this satellite imagery can be viewed in near-real time as it is processed and served by NASA’s Global Imagery Browse Service (GIBS). To better educate users on the time and location of imagery, GIBS serves orbit track specific layers for each satellite. Worldview has historically served these layers as raster images but recent updates have enabled the application to now serve these layers using vector tiles. With the release of Worldview v3.0, orbit track layers can be displayed using mapbox vector tiles (MVT). This visualization format allows users to not only view and change the color of orbit track layers, as they could do previously with rasters, but also inspect individual vector points and filter layers by specific parameters such as time. The data contained within a MVT is further enhanced in Worldview with the combination of a JSON description file served from GIBS used to describe the MVT data. This presentation will provide an overview of the process of consuming orbit track vector tiles and data files from GIBS using a pipeline to configure, build and ultimately display the orbit tracks in Worldview. Furthermore, the presentation aims to describe how others can leverage our open-source code to display and enhance vector layers in their own applications.

Rice, Zachary↗

NASA NTRS2019

Online Visualization and Analysis of NASA Satellite-Based Global and Regional Precipitation Products Through Giovanni

Observational data are essential for Earth science research and applications. Traditional ground-based observations suffer from many limitations (e.g. costly deployment). As a result, data are often sparse and inconsistent, especially over vast oceans that cover nearly 71% of the Earth's surface, and for remote continents. Precipitation is one of the important physical parameters in the global hydrological cycle and other disciplines. Each year, severe floods and droughts happen in different parts of the world and cause significant damage to the economy, as well as human casualties (e.g. Hurricane Katrina, the Dust Bowl). Accurate and timely precipitation observations and predictions are important for research and applications. However, ground-based precipitation observations are quite limited, especially in remote and mountainous regions. Since the satellite era began, satellite-based precipitation products have gained popularity in Earth science research, applications, and education. Accessing satellite products can be a daunting task to many users, especially those who do not have prior experience or knowledge with satellite data. Recognizing this obstacle, the NASA Goddard Earth Sciences and Data and Information Services Center (GES DISC), home to data archives for the NASA-JAXA Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM), has developed data services including an online visualization and analysis tool, Giovanni (the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure), enabling users at different levels to access, explore, and evaluate NASA satellite-based data products without downloading either data and software, or requiring coding. Currently, global and regional precipitation products from different satellite missions (TRMM, GPM) and projects (e.g. the Modern Era Retrospective-analysis for Research and Applications Version 2 (MERRA-2), and the North American Land Data Assimilation System (NLDAS)), ranging from half-hourly to monthly temporal resolution, are available in Giovanni. There are over 1900 variables in Giovanni, covering measurements in precipitation, hydrology, atmospheric dynamics, atmospheric chemistry, etc. In this poster presentation, we will provide a live demonstration of Giovanni and its latest development, including precipitation-related variables, and new basic features such as polar projections. The session will also provide a Q&A opportunity for attendees.

Giovanni↗