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Results for “Interactive visualization and analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Human comfort response to random motions with combined yawing and rolling motions

The effects of random yawing and rolling velocities on passenger ride comfort responses were examined on a visual motion simulator. The effects of power spectral density shape and frequency ranges of peak power from 0 to 2 Hz were studied. The subjective rating data and the physical motion data obtained are presented. No attempt at interpretation or detailed analysis of the data is made. There existed during this study motions in all other degrees of freedom as well as the yawing and rolling motions, because of the characteristics of the simulator. These unwanted motions may have introduced some interactive effects on passenger responses which should be considered in any analysis of the data.

Stone, R. W., Jr.↗
NASA NTRS1992

Advances in tilt rotor noise prediction

The two most serious tilt rotor external noise problems, hover noise and blade-vortex interaction noise, are studied. The results of flow visualization and inflow velocity measurements document a complex, recirculating highly unsteady and turbulent flow due to the rotor-wing-body interactions characteristic of tilt rotors. The wing under the rotor is found to obstruct the inflow, causing a deficit in the inflow velocities over the inboard region of the rotor. Discrete frequency harmonic thickness and loading noise mechanisms in hover are examined by first modeling tilt rotor hover aerodynamics and then applying various noise prediction methods using the WOPWOP code. The analysis indicates that the partial ground plane created by the wing below the rotor results in a primary sound source for hover.

George, A. R.↗
NASA NTRS1994

Experimenter's Laboratory for Visualized Interactive Science

ELVIS (Experimenter's Laboratory for Visualized Interactive Science) is an interactive visualization environment that enables scientists, students, and educators to visualize and analyze large, complex, and diverse sets of scientific data. It accomplishes this by presenting the data sets as 2-D, 3-D, color, stereo, and graphic images with movable and multiple light sources combined with displays of solid-surface, contours, wire-frame, and transparency. By simultaneously rendering diverse data sets acquired from multiple sources, formats, and resolutions and by interacting with the data through an intuitive, direct-manipulation interface, ELVIS provides an interactive and responsive environment for exploratory data analysis.

Hansen, Elaine R.↗
DOE OSTI2021

Structural analyses of macromolecules by solution scattering (CRADA Final Report)

New innovative Small Angle X-ray Scattering (SAXS) methods to visualized macromolecules in solution at low resolution has led the SIBYLS group at Lawrence Berkeley Lab in being a world leader in biological SAXS. This research is particularly important now as LBNL establishes high-priority research topics including molecular to mesoscale analysis. This new expanding area of research relies on and ties in with our efforts towards developing a solution structure modeling tool for RNA structure prediction. Due to the pandemic our efforts focused on the SARS-CoV-2 proteins and RNA interactions. Specifically, we characterized SARS-CoC-2 proteins interaction with RNA (Wilanowski et al. 2021 -Hammel group) and Nucleoprotein interaction with RNA (Schneidman group).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1973

An experimental investigation of vortex stability, tip shapes, compressibility, and noise for hovering model rotors

Schlieren methods of flow visualization and hot-wire anemometry for velocity measurements were used to investigate the wakes generated by hovering model propellers and rotors. The research program was directed toward investigating (1) the stability of the tip vortex, (2) the effects produced by various tip shapes on performance and tip vortex characteristics, and (3) the shock formation and noise characteristics associated with various tip shapes. A free-wake analysis was also conducted for comparison with the vortex stability experimental results. Schlieren photographs showing wake asymmetry, interaction, and instability are presented along with a discussion of the effects produced by the number of blades, collective pitch, and tip speed. Two hot-wire anemometer techniques, used to measure the maximum circumferential velocity in the tip vortex, are discussed.

Tangler, J. L.↗
NASA NTRS2005

An Interoperable, Agricultural Information System Based on Satellite Remote Sensing Data

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of US. agricultural products and for global food security. The Goddard Space Flight Center Earth Sciences Data and Information Services Center Distributed Active Archive Center (GES DISC DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide satellite remote sensing data products (e.g., rainfall) and services. The data products will include crop condition and yield prediction maps, generated from a crop growth model with satellite data inputs, in collaboration with the USDA Agricultural Research Service. The AIS will enable the remote, interoperable access to distributed data, by using the GrADS-DODS Server (GDS) and by being compliant with Open GIS Consortium standards. Users will be able to download individual files, perform interactive online analysis, as well as receive operational data flows. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as those of the USDA Foreign Agricultural Service and the U.N. World Food Program.

Teng, William↗
NASA NTRS2017

Engine Icing Data - An Analytics Approach

Engine icing researchers at the NASA Glenn Research Center use the Escort data acquisition system in the Propulsion Systems Laboratory (PSL) to generate and collect a tremendous amount of data every day. Currently these researchers spend countless hours processing and formatting their data, selecting important variables, and plotting relationships between variables, all by hand, generally analyzing data in a spreadsheet-style program (such as Microsoft Excel). Though spreadsheet-style analysis is familiar and intuitive to many, processing data in spreadsheets is often unreproducible and small mistakes are easily overlooked. Spreadsheet-style analysis is also time inefficient. The same formatting, processing, and plotting procedure has to be repeated for every dataset, which leads to researchers performing the same tedious data munging process over and over instead of making discoveries within their data. This paper documents a data analysis tool written in Python hosted in a Jupyter notebook that vastly simplifies the analysis process. From the file path of any folder containing time series datasets, this tool batch loads every dataset in the folder, processes the datasets in parallel, and ingests them into a widget where users can search for and interactively plot subsets of columns in a number of ways with a click of a button, easily and intuitively comparing their data and discovering interesting dynamics. Furthermore, comparing variables across data sets and integrating video data (while extremely difficult with spreadsheet-style programs) is quite simplified in this tool. This tool has also gathered interest outside the engine icing branch, and will be used by researchers across NASA Glenn Research Center. This project exemplifies the enormous benefit of automating data processing, analysis, and visualization, and will help researchers move from raw data to insight in a much smaller time frame.

Engine Icing↗
DOE OSTI2022

Toward Human-Centric Transportation and Energy Metrics: Influence of Mode, Vehicle Occupancy, Trip Distance, and Fuel Economy

Traditional metrics measuring transportation and energy outcomes can be augmented to better represent impacts on people's lives and systems-level performance. In this context, this study introduces two novel metrics: road capacity (as number of people traveling and accessing services) and energy intensity (as energy use for people traveling and accessing services). Current national-level distributions of available data in the United States for factors contributing to the two new integrated metrics are used as context to evaluate potential outcomes. These factors include vehicle occupancy, mode share, fuel economy, and trip distance. Variations in input values provide insights on how these factors shape efficiencies in road capacity and energy intensity. Parametric sensitivity analysis indicates that the impact of each input depends upon the metric being evaluated. For the human-centered road capacity mobility metric, increasing vehicle occupancy has the largest effect – twice that of increasing mode share for bike, walk, and transit. For the energy intensity mobility metric, the effect of improving fuel economy is the largest. However, when the focus is on accessibility (instead of mobility), for both metrics the effect of lowering average trip distance is the largest. Additionally, a novel interactive tool to visualize the results for various parameter combinations makes the metrics practitioner ready. The findings suggest that the diffusion of new human-centric metrics that benchmark outcomes associated with road capacity and energy may be significant in motivating new sustainable transportation investments and efficient utilization of infrastructure, mobility assets, and services.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Visualization Techniques in Space and Atmospheric Sciences

Unprecedented volumes of data will be generated by research programs that investigate the Earth as a system and the origin of the universe, which will in turn require analysis and interpretation that will lead to meaningful scientific insight. Providing a widely distributed research community with the ability to access, manipulate, analyze, and visualize these complex, multidimensional data sets depends on a wide range of computer science and technology topics. Data storage and compression, data base management, computational methods and algorithms, artificial intelligence, telecommunications, and high-resolution display are just a few of the topics addressed. A unifying theme throughout the papers with regards to advanced data handling and visualization is the need for interactivity, speed, user-friendliness, and extensibility.

Szuszczewicz, E. P.↗
NASA NTRSDate not supplied

Constructing a Knowledge Graph & Applying Graph Algorithms to Draw Insights about GES-DISC Jira Tickets

In order to assess the complexities of Jira tickets created by NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC), it was beneficial to create a knowledge graph. The knowledge graph receives ticket data through the Jira API. The creation of a knowledge graph will help to answer high-level questions about internal structure, knowledge gaps, and team organization within GES-DISC. To work towards this goal, the knowledge graph was constructed in adockerizedNeo4j graph database. Once the graph had been created, graph algorithms were applied to answer high-level questions, such as exploring the role of staff in relation to projects, which qualities of a ticket contribute to the formation of communities within the graph, etc. To answer these questions, centrality and community detection algorithms were applied using Cypher querying language. The analysis of the results of the algorithms indicated that, as expected, certain individuals were more connected to some projects, while others were serving as hub nodes between two or more projects. Similarly, specific keywords are more likely to increase a Jira ticket’s centrality in the graph. In terms of community detection, when tickets in a community have certain qualities, it is more probable for them to be grouped together. To best visualize which nodes had higher centrality scores or were grouped into certain communities, interactive graphs were created in Python using Plotly and Matplotlib. Ultimately, the project was successful in creating and deploying a knowledge graph to better understand the relationships between data in GES-DISC Jira tickets

Rebecca Lipton↗
DOE OSTI2022

Optical properties of Peaked Spectrum radio sources

ABSTRACT In this work, we study the optical properties of compact radio sources selected from the literature in order to determine the impact of the radio-jet in their circumnuclear environment. Our sample includes 58 Compact Steep Spectrum (CSS) and GigaHertz Peaked Spectrum (GPS) and 14 Megahertz-Peaked spectrum (MPS) radio sources located at z ≤ 1. The radio luminosity (LR) of the sample varies between Log LR ∼ 23.2 and 27.7 W Hz−1. We obtained optical spectra for all sources from SDSS-DR12 and performed a stellar population synthesis using the starlight code. We derived stellar masses (M⋆), ages 〈t⋆〉, star formation rates (SFR), metallicities 〈Z⋆〉 and internal reddening AV for all young AGNs of our sample. A visual inspection of the SDSS images was made to assign a morphological class for each source. Our results indicate that the sample is dominated by intermediate to old stellar populations and there is no strong correlation between optical and radio properties of these sources. Also, we found that young AGNs can be hosted by elliptical, spiral and interacting galaxies, confirming recent findings. When comparing the optical properties of CSS/GPS and MPS sources, we do not find any significant difference. Finally, the Mid-Infrared WISE colours analysis suggests that the compact radio sources defined as powerful AGNs are, in general, gas-rich systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Diagnostic diagrams for ram pressure stripped candidates

ABSTRACT This paper presents a method for finding ram pressure stripped (RPS) galaxy candidates by performing a morphological analysis of galaxy images obtained from the Legacy survey. We consider a sample of about 600 galaxies located in different environments such as groups and clusters, tidally interacting pairs and the field. The sample includes 160 RPS previously classified in the literature into classes from J1 to J5, based on the increasing level of disturbances. Our morphological analysis was done using the astromorphlib software followed by the inspection of diagnostic diagrams involving combinations of different parameters like the asymmetry (A), concentration (C), Sérsic index (n), and bulge strength parameters $F(G,\, M_{20})$. We found that some of those diagrams display a distinct region in which galaxies classified as J3, J4, and J5 decouples from isolated galaxies. We call this region as the morphological transition zone and we also found that tidally interacting galaxies in pairs are predominant within this zone. Nevertheless, after visually inspecting the objects in the morphological transition zone to discard obvious contaminants, we ended up with 33 bona fide new RPS candidates in the studied nearby groups and clusters (Hydra, Fornax, and CLoGS sample), of which one-third show clear evidence of unwinding arms. Future works may potentially further increase significantly the samples of known RPS using such method.

Astronomy & Astrophysics↗
NASA NTRS1989

Scientific visualization in computational aerodynamics at NASA Ames Research Center

The visualization methods used in computational fluid dynamics research at the NASA-Ames Numerical Aerodynamic Simulation facility are examined, including postprocessing, tracking, and steering methods. The visualization requirements of the facility's three-dimensional graphical workstation are outlined and the types hardware and software used to meet these requirements are discussed. The main features of the facility's current and next-generation workstations are listed. Emphasis is given to postprocessing techniques, such as dynamic interactive viewing on the workstation and recording and playback on videodisk, tape, and 16-mm film. Postprocessing software packages are described, including a three-dimensional plotter, a surface modeler, a graphical animation system, a flow analysis software toolkit, and a real-time interactive particle-tracer.

Bancroft, Gordon V.↗
NASA NTRS2001

Overview of ICE Project: Integration of Computational Fluid Dynamics and Experiments

Researchers at the NASA Glenn Research Center have developed a prototype integrated environment for interactively exploring, analyzing, and validating information from computational fluid dynamics (CFD) computations and experiments. The Integrated CFD and Experiments (ICE) project is a first attempt at providing a researcher with a common user interface for control, manipulation, analysis, and data storage for both experiments and simulation. ICE can be used as a live, on-tine system that displays and archives data as they are gathered; as a postprocessing system for dataset manipulation and analysis; and as a control interface or "steering mechanism" for simulation codes while visualizing the results. Although the full capabilities of ICE have not been completely demonstrated, this report documents the current system. Various applications of ICE are discussed: a low-speed compressor, a supersonic inlet, real-time data visualization, and a parallel-processing simulation code interface. A detailed data model for the compressor application is included in the appendix.

Stegeman, James D.↗
NASA NTRS2012

JPL Genesis and Rapid Intensification Processes (GRIP) Portal

Satellite observations can play a very important role in airborne field campaigns, since they provide a comprehensive description of the environment that is essential for the experiment design, flight planning, and post-experiment scientific data analysis. In the past, it has been difficult to fully utilize data from multiple NASA satellites due to the large data volume, the complexity of accessing NASA s data in near-real-time (NRT), as well as the lack of software tools to interact with multi-sensor information. The JPL GRIP Portal is a Web portal that serves a comprehensive set of NRT observation data sets from NASA and NOAA satellites describing the atmospheric and oceanic environments related to the genesis and intensification of the tropical storms in the North Atlantic Ocean. Together with the model forecast data from four major global atmospheric models, this portal provides a useful tool for the scientists and forecasters in planning and monitoring the NASA GRIP field campaign during the 2010 Atlantic Ocean hurricane season. This portal uses the Google Earth plug-in to visualize various types of data sets, such as 2D maps, wind vectors, streamlines, 3D data sets presented at series of vertical cross-sections or pointwise vertical profiles, and hurricane best tracks and forecast tracks. Additionally, it allows users to overlap multiple data sets, change the opacity of each image layer, generate animations on the fly with selected data sets, and compare the observation data with the model forecast using two independent calendars. The portal also provides the capability to identify the geographic location of any point of interest. In addition to supporting the airborne mission planning, the NRT data and portal will serve as a very rich source of information during the post-field campaign analysis stage of the airborne experiment. By including a diverse set of satellite observations and model forecasts, it provides a good spatial and temporal context for the high-resolution, but limited in space and time, airborne observations.

Knosp, Brian W.↗
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 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↗