SEARCH · Search NASA

Results for “interactive data visualization”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 919 records · Page 51

All sources NASA NTRS DOE OSTI

NASA NTRS2006

LiveView3D: Real Time Data Visualization for the Aerospace Testing Environment

This paper addresses LiveView3D, a software package and associated data visualization system for use in the aerospace testing environment. The LiveView3D system allows researchers to graphically view data from numerous wind tunnel instruments in real time in an interactive virtual environment. The graphical nature of the LiveView3D display provides researchers with an intuitive view of the measurement data, making it easier to interpret the aerodynamic phenomenon under investigation. LiveView3D has been developed at the NASA Langley Research Center and has been applied in the Langley Unitary Plan Wind Tunnel (UPWT). This paper discusses the capabilities of the LiveView3D system, provides example results from its application in the UPWT, and outlines features planned for future implementation.

Schwartz, Richard J.↗

NASA NTRS2010

Evaluation of Mixed-Mode Data-Link Communications for NextGen 4DT and Equivalent Visual Surface Operations

By 2025, U.S. air traffic is predicted to increase 3-fold and may strain the current air traffic management system, which may not be able to accommodate this growth. In response to this challenge, a revolutionary new concept has been proposed for U.S. aviation operations, termed the Next Generation Air Transportation System or NextGen. Many key capabilities are being identified to enable NextGen, including the use of data-link communications. Because NextGen represents a radically different approach to air traffic management and requires a dramatic shift in the tasks, roles, and responsibilities for the flight deck, there are numerous research issues and challenges that must be overcome to ensure a safe, sustainable air transportation system. Flight deck display and crew-vehicle interaction concepts are being developed that proactively investigate and overcome potential technology and safety barriers that might otherwise constrain the full realization of NextGen. The paper describes simulation research examining data-link communications during 4DT and equivalent visual surface operations.

Prinzel, Lawrence J., III↗

DOE OSTI2023

RadVolViz: An Information Display-Inspired Transfer Function Editor for Multivariate Volume Visualization

In volume visualization transfer functions are widely used for mapping voxel properties to color and opacity. Typically, volume density data are scalars which require simple 1D transfer functions to achieve this mapping. If the volume densities are vectors of three channels, one can straightforwardly map each channel to either red, green or blue, which requires a trivial extension of the 1D transfer function editor. Here, we devise a new method that applies to volume data with more than three channels. These types of data often arise in scientific scanning applications, where the data are separated into spectral bands or chemical elements. Our method expands on prior work in which a multivariate information display, RadViz, was fused with a radial color map, in order to visualize multi-band 2D images. In this work, we extend this joint interface to blended volume rendering. The information display allows users to recognize the presence and value distribution of the multivariate voxels and the joint volume rendering display visualizes their spatial distribution. We design a set of operators and lenses that allow users to interactively control the mapping of the multivariate voxels to opacity and color. This enables users to isolate or emphasize volumetric structures with desired multivariate properties. Furthermore, it turns out that our method also enables more insightful displays even for RGB data. We demonstrate our method with three datasets obtained from spectral electron microscopy, high energy X-ray scanning, and atmospheric science.

36 MATERIALS SCIENCE↗

NASA NTRS2008

Creating User-Friendly Tools for Data Analysis and Visualization in K-12 Classrooms: A Fortran Dinosaur Meets Generation Y

During the summer of 2007, as part of the second year of a NASA-funded project in partnership with Christopher Newport University called SPHERE (Students as Professionals Helping Educators Research the Earth), a group of undergraduate students spent 8 weeks in a research internship at or near NASA Langley Research Center. Three students from this group formed the Clouds group along with a NASA mentor (Chambers), and the brief addition of a local high school student fulfilling a mentorship requirement. The Clouds group was given the task of exploring and analyzing ground-based cloud observations obtained by K-12 students as part of the Students' Cloud Observations On-Line (S'COOL) Project, and the corresponding satellite data. This project began in 1997. The primary analysis tools developed for it were in FORTRAN, a computer language none of the students were familiar with. While they persevered through computer challenges and picky syntax, it eventually became obvious that this was not the most fruitful approach for a project aimed at motivating K-12 students to do their own data analysis. Thus, about halfway through the summer the group shifted its focus to more modern data analysis and visualization tools, namely spreadsheets and Google(tm) Earth. The result of their efforts, so far, is two different Excel spreadsheets and a Google(tm) Earth file. The spreadsheets are set up to allow participating classrooms to paste in a particular dataset of interest, using the standard S'COOL format, and easily perform a variety of analyses and comparisons of the ground cloud observation reports and their correspondence with the satellite data. This includes summarizing cloud occurrence and cloud cover statistics, and comparing cloud cover measurements from the two points of view. A visual classification tool is also provided to compare the cloud levels reported from the two viewpoints. This provides a statistical counterpart to the existing S'COOL data visualization tool, which is used for individual ground-to-satellite correspondences. The Google(tm) Earth file contains a set of placemarks and ground overlays to show participating students the area around their school that the satellite is measuring. This approach will be automated and made interactive by the S'COOL database expert and will also be used to help refine the latitude/longitude location of the participating schools. Once complete, these new data analysis tools will be posted on the S'COOL website for use by the project participants in schools around the US and the world.

Chambers, L. H.↗

DOE OSTI2025

Real-World Cyber Security Demonstration for Networked Electric Drives

In this article, we present the design and implementation of a cyber-physical security testbed for networked electric drive systems, aimed at conducting real-world security demonstrations. To our knowledge, this is one of the first security testbeds for networked electric drives, seamlessly integrating the domains of power electronics and computer science, and cybersecurity. By doing so, the testbed offers a comprehensive platform to explore and understand the intricate and often complex interactions between cyber and physical systems. The core of our testbed consists of four electric machine drives, meticulously configured to emulate small-scale but realistic information technology (IT) and operational technology (OT) networks. This setup both provides a controlled environment for simulating a wide array of cyber-attacks, and mirrors potential real-world attack scenarios with a high degree of fidelity. The testbed serves as an invaluable resource for the study of cyber-physical security, offering a practical and dynamic platform for testing and validating cybersecurity measures in the context of networked electric drive systems. As a concrete example of the testbed's capabilities, we have developed and implemented a Python-based script designed to execute step-stone attacks over a wireless local area network (WLAN). This script leverages a sequence of target IP addresses, simulating a real-world attack vector that could be exploited by adversaries. To counteract such threats, we demonstrate the efficacy of our developed cyber-attack detection algorithms, which are integral to our testbed's security framework. Furthermore, the testbed incorporates a real-time visualization system using InfluxDB and Grafana, providing a dynamic and interactive representation of networked electric drives and their associated security monitoring mechanisms. This visualization component not only enhances the testbed's usability but also offers insightful, real-time data for researchers and practitioners, thereby facilitating a deeper understanding of cyber-physical security dynamics in networked electric drive systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2008

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Hong, Yang↗

NASA NTRSDate not supplied

An Oculometric Standard to Assess the Performance of the Ocular System for Long Duration Spaceflight

Changes in the human brain, due to spaceflight, have been a challenge to the space program since its inception; a challenge that is becoming more acute as extended International Space Station (ISS) missions become routine, a return to crewed lunar exploration is about to begin, and a multi-year crewed trip to Mars is being planned. Determining the extent to which neurophysiological adaptations may adversely impact performance in operational tasks, assessing the full-time course of these changes, and identifying/mitigating any potential long-term health consequences are crucial steps required to enable safe crew-autonomous, long-duration, deep-space missions. Vision is the predominant perceptual sense used to guide cognition and motor control in humans. Thus, it is critical for the success of any future, long-duration mission to understand how long-term exposure to microgravity and to other stressors of spaceflight and their interactions, impact visual function. This is an especially challenging task given the small and disparate samples from which we have been and will be able to collect human performance data. NASA has recently been carefully tracking spaceflight-induced ophthalmic changes, driven in large part by the fluid shifts related to microgravity. In particular, a recent study of Optical Coherence Tomography (OCT) postflight measures revealed that more than two-thirds of US crew members experience significant increases in retinal thickness after 6month or longer ISS missions. Space Associated Neuro-ocular Syndrome (SANS) also includes visual acuity decrements and other ocular structural changes that could adversely impact in-flight performance as missions become longer. However, the impact of spaceflight on the visual system is not limited to the retina. Recent comparisons of pre-and post-flight brain images have revealed structural changes throughout the brain that implicate visual, visuomotor, and visual-cognitive pathways, consistent with observed functional impacts (e.g., decreased speed/accuracy/timing of fine goal-oriented movements). Current limitations on inflight testing make it very difficult to determine when and under what conditions SANS and other disruptions of human neurological subsystems arise. Currently, one cannot anticipate the time course and extent of impairment and recovery. This study addresses this knowledge gap by creating an integrated framework of the relevant existing literature on visual and oculomotor function during spaceflight with an eye towards complementing current structural measures of visuomotor impairment with new oculometric standard measures. Using eye-movement based visual function assessment and diagnostics would provide a valuable enhancement of crew health and performance monitoring in support of deepspace exploration.

Vision↗

NASA NTRSDate not supplied

Flow Visualization for Plume-Surface Interaction Testing Within Large-Scale Vacuum Environments at Conditions Relevant to Lunar and Martian Landers

Interactions between rocket exhaust plumes and the landing surface during powered spacecraft descent on the Moon and Mars pose significant risks to the landing vehicle, landing site, and nearby infrastructure. Understanding the underlying plume-surface interaction phenomena through ground test data can provide critical insights on the sensitivities of parameters such as the spacecraft altitude and thrust. In the present work, we summarize a scaled ground test recently conducted within a 20-ft vacuum chamber environment located in the historical East Test Area at the NASA Marshall Space Flight Center. The ground test featured a Mach 5.3 inert gas plume impinging upon an instrumented flat plate. Planar laser-induced fluorescence, which is a 2D laser-based flow field measurement technique, was performed at this test area for the first time to visualize salient flow features such as the barrel shock, stagnation shock, and wall jet. Measurements were obtained at discrete lander altitudes, made dimensionless using the nozzle exit diameter, corresponding to h/D = 10, 8, 5, 4, 3, and 2. The stagnation pressures of the plume were varied from approximately 0.04 to 1 MPa, providing sensitivity to the engine thrust of a powered spacecraft. The unique test facility allowed for near-lunar conditions to be obtained at initial vacuum chamber pressures less than 0.1 Pa. Martian-relevant measurements were also performed at ambient pressures near 600 Pa. Furthermore, a third set of measurements were obtained at so called lunar-relevant conditions near 3 Pa chamber pressure

Plume Surface Interaction↗

NASA NTRSDate not supplied

Flow Visualization for Plume-Surface Interaction Testing Within Large-Scale Vacuum Environments at Conditions Relevant to Lunar and Martian Landers

Plume Surface Interaction↗

DOE OSTI2022

AIMSim : An accessible cheminformatics platform for similarity operations on chemicals datasets

The recent advances in deep learning, generative modeling, and statistical learning have ushered in a renewed interest in traditional cheminformatics tools and methods. Quantifying molecular similarity is essential in molecular generative modeling, exploratory molecular synthesis campaigns, and drug-discovery applications to assess how new molecules differ from existing ones. Further, most tools target advanced users and lack general implementations accessible to the larger community. In this work, we introduce Artificial Intelligence Molecular Similarity (AIMSim), an accessible cheminformatics platform for performing similarity operations on collections of molecules called molecular datasets. AIMSim provides a unified platform to perform similarity-based tasks on molecular datasets, such as diversity quantification, outlier and novelty analysis, clustering, dimensionality reduction, and inter-molecular comparisons. AIMSim implements all major binary similarity metrics and molecular fingerprints and is provided as a Python package that includes support for command-line use as well as a Graphical User Interface for code-free utilization with fully interactive plots.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Visualization of Simulation and TAP Interaction

The Temporal Analysis of Products (TAP) Reactor applies transient kinetics to analyze sophisticated chemical reaction mechanisms, rapidly changing temperature, flow rate, pressure or concentration and then monitoring the system’s time dependent response. A simulation tool exists for the TAP reactor, but it requires a visualization platform to interface effectively with researchers. This graphical user interface remedies this problem, fixing many of the difficulties caused by users interacting directly with the simulation code by providing an intuitive web application that satisfies the simulation input parameters for fast generation of data. This tool will ensure robust and repeatable simulation results, expedite the data generating process and enhance the overall ability of TAP to produce significant findings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2012

Entry, Descent, and Landing With Propulsive Deceleration: Supersonic Retropropulsion Wind Tunnel Testing

The future exploration of the Solar System will require innovations in transportation and the use of entry, descent, and landing (EDL) systems at many planetary landing sites. The cost of space missions has always been prohibitive, and using the natural planetary and planet s moons atmosphere for entry, descent, and landing can reduce the cost, mass, and complexity of these missions. This paper will describe some of the EDL ideas for planetary entry and survey the overall technologies for EDL that may be attractive for future Solar System missions. Future EDL systems may include an inflatable decelerator for the initial atmospheric entry and an additional supersonic retro-propulsion (SRP) rocket system for the final soft landing. As part of those efforts, NASA began to conduct experiments to gather the experimental data to make informed decisions on the "best" EDL options. A model of a three engine retro-propulsion configuration with a 2.5 in. diameter sphere-cone aeroshell model was tested in the NASA Glenn 1- by 1-Foot Supersonic Wind Tunnel (SWT). The testing was conducted to identify potential blockage issues in the tunnel, and visualize the rocket flow and shock interactions during supersonic and hypersonic entry conditions. Earlier experimental testing of a 70 Viking-like (sphere-cone) aeroshell was conducted as a baseline for testing of a supersonic retro-propulsion system. This baseline testing defined the flow field around the aeroshell and from this comparative baseline data, retro-propulsion options will be assessed. Images and analyses from the SWT testing with 300- and 500-psia rocket engine chamber pressures are presented here. The rocket engine flow was simulated with a non-combusting flow of air.

Palaszewski, Bryan↗

DOE OSTI2020

Dalton Project: A Python platform for molecular- and electronic-structure simulations of complex systems

The Dalton Project provides a uniform platform access to the underlying full-fledged quantum chemistry codes Dalton and LSDalton as well as the PyFraME package for automatized fragmentation and parameterization of complex molecular environments. The platform is written in Python and defines a means for library communication and interaction. Intermediate data such as integrals are exposed to the platform and made accessible to the user in the form of NumPy arrays, and the resulting data are extracted, analyzed, and visualized. Complex computational protocols that may, for instance, arise due to a need for environment fragmentation and configuration-space sampling of biochemical systems are readily assisted by the platform. The platform is designed to host additional software libraries and will serve as a hub for future modular software development efforts in the distributed Dalton community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗

DOE OSTI2024

Demonstration and Evaluation of Explainable and Trustworthy Predictive Technology for Condition-based Maintenance

The domestic nuclear power plant (NPP) fleet has historically relied on labor-intensive and time-consuming predictive maintenance (PdM) programs, thus driving up operation and maintenance (O&M) costs to achieve high-capacity factors. Artificial intelligence (AI) and machine-learning (ML) can help simplify complex problems such as diagnosing equipment degradation to enable more effective decision-making efforts. The benefits of AI will be felt through more efficient plant O&M, improved work processes, and better integration of people and technology. Together, these benefits hold the promise to make nuclear power more sustainable by reducing O&M costs while improving employee engagement. While AI and ML technologies hold significant promise for the nuclear industry, there are challenges or barriers to their adoption. Explainability and trustworthiness of AI are two salient challenges that need to be addressed for wider deployment of these technologies in NPPs. This research focuses specifically on addressing the explainability and trustworthiness of AI technologies to advance the human, technical, and organization (HTO) readiness levels in adopting a risk-informed PdM strategy at commercial NPPs. In addition, this approach can be adapted to enhance the acceptability of AI in other nuclear applications with a few application-specific modifications. The technical approach ensuring wider adoption of AI technologies was developed by Idaho National Laboratory (INL)—in collaboration with Public Service Enterprise Group (PSEG), Nuclear, LLC—by utilizing the circulating water system (CWS) at two PSEG-owned plant sites for demonstration. Focused user studies were performed in collaboration with subject matter experts (SMEs) from PSEG and other nuclear domains to enhance human and organization readiness by building trust in AI-informed technologies. VIsualization for PrEdictive maintenance Recommendation (VIPER)—a Battelle Energy Alliance, LLC, copyrighted software—was developed and expanded to provide a user-centric visualization by incorporating inputs from the collaborating utility, human factors engineering guidelines, and data analysts. The VIPER software enables users, who may be unfamiliar with ML in general, to be interactively engaged by asking technical questions about PdM, work orders, diagnosis results and their confidence levels, the kind of data being used, and the types of ML algorithms employed. This interactive engagement enhances explainability and builds trust. One of the enabling accomplishments was the integration of large language models (LLMs), both text-based and vision-based, in the VIPER software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2002

Fast interactive real-time volume rendering of real-time three-dimensional echocardiography: an implementation for low-end computers

Real-time three-dimensional echocardiography (RT3DE) is an innovative cardiac imaging modality. However, partly due to lack of user-friendly software, RT3DE has not been widely accepted as a clinical tool. The object of this study was to develop and implement a fast and interactive volume renderer of RT3DE datasets designed for a clinical environment where speed and simplicity are not secondary to accuracy. Thirty-six patients (20 regurgitation, 8 normal, 8 cardiomyopathy) were imaged using RT3DE. Using our newly developed software, all 3D data sets were rendered in real-time throughout the cardiac cycle and assessment of cardiac function and pathology was performed for each case. The real-time interactive volume visualization system is user friendly and instantly provides consistent and reliable 3D images without expensive workstations or dedicated hardware. We believe that this novel tool can be used clinically for dynamic visualization of cardiac anatomy.

NASA Discipline Cardiopulmonary↗

DOE OSTI2018

Xi-cam : a versatile interface for data visualization and analysis

Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam 's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam 's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.

Pandolfi, Ronald J. (ORCID:0000000308248548)↗

NASA NTRS1993

Telemetry Monitoring and Display Using LabVIEW

The Measurement Technology Center of the Instrumentation Section configures automated data acquisition systems to meet the diverse needs of JPL's experimental research community. These systems are based on personal computers or workstations (Apple, IBM/Compatible, Hewlett-Packard, and Sun Microsystems) and often include integrated data analysis, visualization and experiment control functions in addition to data acquisition capabilities. These integrated systems may include sensors, signal conditioning, data acquisition interface cards, software, and a user interface. Graphical programming is used to simplify configuration of such systems. Employment of a graphical programming language is the most important factor in enabling the implementation of data acquisition, analysis, display and visualization systems at low cost. Other important factors are the use of commercial software packages and off-the-shelf data acquisition hardware where possible. Understanding the experimenter's needs is also critical. An interactive approach to user interface construction and training of operators is also important. One application was created as a result of a competative effort between a graphical programming language team and a text-based C language programming team to verify the advantages of using a graphical programming language approach. With approximately eight weeks of funding over a period of three months, the text-based programming team accomplished about 10% of the basic requirements, while the Macintosh/LabVIEW team accomplished about 150%, having gone beyond the original requirements to simulate a telemetry stream and provide utility programs. This application verified that using graphical programming can significantly reduce software development time. As a result of this initial effort, additional follow-on work was awarded to the graphical programming team.

graphical user interface LabVIEW graphical program↗