Search NASA⌕ Search

SEARCH · Search NASA

Results for “visual analytics”

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.

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

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

International Space Station Future Correlation Analysis Improvements

Ongoing modal analyses and model correlation are performed on different configurations of the International Space Station (ISS). These analyses utilize on-orbit dynamic measurements collected using four main ISS instrumentation systems: External Wireless Instrumentation System (EWIS), Internal Wireless Instrumentation System (IWIS), Space Acceleration Measurement System (SAMS), and Structural Dynamic Measurement System (SDMS). Remote Sensor Units (RSUs) are network relay stations that acquire flight data from sensors. Measured data is stored in the Remote Sensor Unit (RSU) until it receives a command to download data via RF to the Network Control Unit (NCU). Since each RSU has its own clock, it is necessary to synchronize measurements before analysis. Imprecise synchronization impacts analysis results. A study was performed to evaluate three different synchronization techniques: (i) measurements visually aligned to analytical time-response data using model comparison, (ii) Frequency Domain Decomposition (FDD), and (iii) lag from cross-correlation to align measurements. This paper presents the results of this study.

time synchronization↗
NASA NTRS2019

VISAGE - A Visualization and Exploration Framework for Environmental Data

Diverse airborne and ground-based environmental observations are important technologies for disaster assessment and response, as well as for the validation of environmental satellite observations and atmospheric models which can improve forecasts. The VISAGE (Visualization for Integrated Satellite, Airborne and Ground-based data Exploration) project is working to provide three-dimensional visualization and basic analytics capabilities for such datasets in an interactive user interface. The use of cloud-native, server less technologies for analysis optimized data storage will position VISAGE for integration with other technologies into a Data Analytic Center Framework.

Conover, Helen↗
NASA NTRS2021

Crop-CASMA - A Web GIS Tool for Cropland Soil Moisture Monitoring and Assessment Based on SMAP Data

Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA- a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.

Zhengwei Yang↗
NASA NTRS2021

Crop-CASMA - A Web GIS Tool for Cropland soil moisture Monitoring and Assessment Based on SMAP Data

Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA - a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.

Reichle, Rolf H.↗
DOE OSTI2026

Visualization for Insight and Data Analysis in Energy Research

This talk explores how advanced visualization technologies are transforming analytical reasoning and knowledge discovery in energy research, drawing on recent work at the National Laboratory of the Rockies' Computational Science Center. Through a series of scientific case studies, we demonstrate how immersive and high-resolution visualization environments enable scientists and engineers to identify previously unseen patterns and features - insights that often remain hidden in traditional desktop-based analysis. By embedding richer information into interactive analytics tools, these approaches support the exploration of complex, multivariate parameter spaces, where interaction itself catalyzes understanding. Beyond capability, we emphasize the critical role of visualization design grounded in perception and cognition, showing how visual encodings directly influence analytical outcomes. Spanning applications from materials science to integrated energy systems, these visualization approaches accelerate innovation and improve decision-making by enabling deeper, more reliable insight into increasingly complex energy data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Unified results of several analytical and experimental studies of helicopter handling qualities in visual terrain flight

The studies were undertaken to investigate the effects of rotor design parameters, interaxis coupling, and various levels of stability and control augmentation on the flying qualities of helicopters performing low-level, terrain-flying tasks in visual meteorological conditions. Some unified results are presented, and the validity and limitations of the flying-qualities data obtained are interpreted. Selected results, related to various design parameters, provide guidelines for the preliminary design of rotor systems and aircraft augmentation systems.

Chen, R. T. N.↗
NASA NTRS1990

Experimental and analytical study of close-coupled ventral nozzles for ASTOVL aircraft

Flow in a generic ventral nozzle system was studied experimentally and analytically with a block version of the PARC3D computational fluid dynamics program (a full Navier-Stokes equation solver) in order to evaluate the program's ability to predict system performance and internal flow patterns. For the experimental work a one-third-size model tailpipe with a single large rectangular ventral nozzle mounted normal to the tailpipe axis was tested with unheated air at steady-state pressure ratios up to 4.0. The end of the tailpipe was closed to simulate a blocked exhaust nozzle. Measurements showed about 5 1/2 percent flow-turning loss, reasonable nozzle performance coefficients, and a significant aftward axial component of thrust due to flow turning loss, reasonable nozzle performance coefficients, and a significant aftward axial component of thrust due to flow turning more than 90 deg. Flow behavior into and through the ventral duct is discussed and illustrated with paint streak flow visualization photographs. For the analytical work the same ventral system configuration was modeled with two computational grids to evaluate the effect of grid density. Both grids gave good results. The finer-grid solution produced more detailed flow patterns and predicted performance parameters, such as thrust and discharge coefficient, within 1 percent of the measured values. PARC3D flow visualization images are shown for comparison with the paint streak photographs. Modeling and computational issues encountered in the analytical work are discussed.

Mcardle, Jack G.↗
DOE OSTI2025

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Infectious diseases (IDs) have a significant detrimental impact on global health. Timely and accurate ID forecasting can result in more informed implementation of control measures and prevention policies. To meet the operational decision-making needs of real-world circumstances, we aimed to build a standardized, reliable, and trustworthy ID forecasting pipeline and visualization dashboard that is generalizable across a wide range of modeling techniques, IDs, and global locations. We forecasted 6 diverse, zoonotic diseases (brucellosis, campylobacteriosis, Middle East respiratory syndrome, Q fever, tick-borne encephalitis, and tularemia) across 4 continents and 8 countries. We included a wide range of statistical, machine learning, and deep learning models (n=9) and trained them on a multitude of features (average n=2326) within the One Health landscape, including demography, landscape, climate, and socioeconomic factors. The pipeline and dashboard were created in consideration of crucial operational metrics—prediction accuracy, computational efficiency, spatiotemporal generalizability, uncertainty quantification, and interpretability—which are essential to strategic data-driven decisions. While no single best model was suitable for all disease, region, and country combinations, our ensemble technique selects the best-performing model for each given scenario to achieve the closest prediction. For new or emerging diseases in a region, the ensemble model can predict how the disease may behave in the new region using a pretrained model from a similar region with a history of that disease. The data visualization dashboard provides a clean interface of important analytical metrics, such as ID temporal patterns, forecasts, prediction uncertainties, and model feature importance across all geographic locations and disease combinations. As the need for real-time, operational ID forecasting capabilities increases, this standardized and automated platform for data collection, analysis, and reporting is a major step forward in enabling evidence-based public health decisions and policies for the prevention and mitigation of future ID outbreaks.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1981

Holographic flow visualization of time-varying shock waves

Rapid-double-exposure, diffuse-illumination holography is evaluated analytically and experimentally as a flow visualization method for time-varying shock waves. Conditions are determined that minimize the distance (localization error) between the surface or curve of interference-fringe localization and the shock surface. Treated specifically are the cases of shock waves in a transonic compressor rotor for which there is laser anemometer data for comparison and shock waves in a flutter cascade.

Decker, A. J.↗
NASA NTRSDate not supplied

An Introduction to Data Visualization

Data visualization can be used to present findings, explore data, and use the human eye to find patterns that a computer would struggle to locate. Borrowing tools from art, storytelling, data analytics and software development, data visualization is an indispensable part of the analysis process. While data visualization usage spans across multiple disciplines and sectors, most never receive formal training in the subject. As such, this tutorial will introduce key data visualization building blocks and how to best use those building blocks for different scenarios and audiences. We will also go over tips on accessibility, design and interactive elements. While this will by no means be a complete overview of the data visualization field, by building a foundation and introducing some rules of thumb, attendees will be better equipped for communicating their findings to their audience.

data visualization↗
DOE OSTI2026

Grid Operator Analytics and Assessment Tools for Inverter- Based Resources Dominated Grid (GOAAT-IBR) Project Update

This presentation provides an update on the OPTIMA GOAAT project, with emphasis on the cloud-native data platform developed in-house to ingest, manage, and operationalize high-resolution power system data. Since our last NASPI presentation, accessible via OSTI ID #2671437, the project team advanced the design and deployment of a scalable architecture capable of handling both synchronized and non-synchronized streams, including PMU, point-on-wave (POW), COMTRADE, and SCADA data. These materials review the project status, recent progress, and key lessons learned. The core of the presentation examines the architecture and engineering of our cloud-native ingestion and data management platform. We then explain how pipelines were designed to collect, normalize, time-align, store, and serve heterogeneous data at scale. We will discuss design choices such as data models, streaming versus batch ingestion, storage tiers, and interoperability with analytics applications. Practical experiences with cloud-native technologies were shared during the event, including benefits, limitations, and integration challenges in a utility environment, along with methods used to improve performance, reduce latency, and optimize resource usage. The presentation also showcases user interface designs and visualization tools that convert raw measurements and analytics results into intuitive, actionable insights for operators and engineers. During the presentation examples were provided demonstrating how visualization, event views, and summarized analytics enhance situational awareness and support operational decision-making. These use cases illustrate how a well-designed data infrastructure can bridge the gap between high-volume measurements and practical grid operations.

Aminifar, Farrokh↗
NASA NTRS1972

A method for increasing thrust reverser utilization on STOL aircraft.

A technique for increasing the utilization of thrust reversers on STOL aircraft is described. The technique involves asymmetric orientation of the reversed exhaust in such a manner as to avoid the problems of self-ingestion, even in the presence of a cross wind, and cross ingestion between adjacent engines. Experimental results of ingestion in a single nacelle inlet are discussed and flow visualization pictures are presented. An analytical model of ingestion is described and sample results are shown.

Tatom, J. W.↗
NASA NTRS1992

Electroencephalographic monitoring of complex mental tasks

Outlined here is the development of neurophysiological procedures to monitor operators during the performance of cognitive tasks. Our approach included the use of electroencepalographic (EEG) and rheoencephalographic (REG) techniques to determine changes in cortical function associated with cognition in the operator's state. A two channel tetrapolar REG, a single channel forearm impedance plethysmograph, a Lead I electrocardiogram (ECG) and a 21 channel EEG were used to measure subject responses to various visual-motor cognitive tasks. Testing, analytical, and display procedures for EEG and REG monitoring were developed that extend the state of the art and provide a valuable tool for the study of cerebral circulatory and neural activity during cognition.

Guisado, Raul↗
NASA NTRS1997

Graphic Three-Axes Presentation of Residual Gas Analyzer Data

Residual gas analyzers (RGA) are commonly used to measure the composition of residual gases in thermal-vacuum test chambers. Measurements from RGA's are often used to identify and quantify outgassing contaminants from a test article during thermal-vacuum testing. RGA data is typically displayed as snapshots in time, showing instantaneous concentrations of ions from ionized residual gas molecules at different atomic masses. This ion concentration information can be interpreted to be representative of the composition of the residual gas in the chamber at the instant of analysis. Typically, test personnel are most interested in tracking the time history of changes in the composition of chamber residual gas to determine the relative cleanliness and the clean-up rate of the test article under vacuum. However, displays of instantaneous RGA data cannot provide test personnel with the preferred time history information. In order to gain an understanding of gas composition trends, a series of plots of individual data snapshots must be analyzed. This analysis is cumbersome and still does not provide a very satisfactory view of residual gas composition trends. A method was devised by the authors to present RCA data in a three-axis format, plotting Atomic Mass Unit (AMU), the Ionization Signal Response (ISR) as amps/torr as a function of AMU, and Time, to provide a clear graphic visualization of trends of changes in ISR with respect to time and AMU (representative of residual gas composition). This graphic visualization method provides a valuable analytical tool to interpret test article outgassing rates during thermal vacuum tests. Raw RGA data was extracted from a series of delimited ASCII files and then converted to a data array in a spreadsheet. Consequently, using the 3-D plotting functionality provided by the spreadsheet program, 3-D plots were produced. After devising the data format conversion process, the authors began developing a program to provide real-time 3-D plotting of RGA data. The intent of this program is to automate the RGA data acquisition process and to generate up-to-the-minute time history 3-D displays of stored RGA data (development of this program was not complete at the time of this writing). This paper provides a brief description of the data format conversion process and presents results from a recent test to illustrate the usefulness of this 3-D RGA data plotting technique.

Johnson, Kenneth R.↗
NASA NTRSDate not supplied

Machine Learning for NASA Advanced Information Systems

NASA's Advanced Information Systems Technology (AIST) Program is one of several Technology programs managed by the Earth Science Technology Office (ESTO) in the Earth Science Division (ESD). The AIST Program focuses on advanced information systems and novel computer science technologies that will be needed by NASA Earth Science in the next 5 to 10 years. The three main thrusts of the AIST Program deal with Novel Observing Strategies (NOS), Analytic Collaborative Frameworks (ACF) and Earth System Digital Twins (ESDT). For all these thrusts, Machine Learning (ML) is increasingly being used in multiple aspects of Earth science systems, e.g., for onboard autonomy and decision making, for the analysis of massive and diverse datasets as well as more recently for developing surrogate models that will represent one of the main components of future Digital Twins of the Earth. Particularly, ESDT technologies developed by the AIST Program will allow to develop integrated Earth Science frameworks that will mirror the Earth with state-of-the-art models (Earth system models and others), timely and relevant observations, and analytic tools. These information systems will be used for supporting near- and long-term science and policy decisions. ESDT frameworks will build on previously developed AIST capabilities and technologies to integrate interconnected models with continuous streams of observations, data analytics, data assimilation, simulations, advanced visualizations and the ability to conduct "what-if" scenarios. This talk will describe the three thrusts of the AIST Program with a special focus on Machine Learning and how it is being used at all steps of the Earth Science data lifecycle.

Mathematical and Computer Sciences (General)↗
NASA NTRSDate not supplied

Upcoming Lunar Mission Landing Sites: Viewing and Analysis with Celestial Mapping System

The Celestial Mapping System (CMS) is a powerful software platform designed to create virtual 3D globes for celestial bodies within our solar system, with a specific focus on lunar mapping. CMS offers a rich array of functionalities, including high-resolution imagery visualization, precise measurement tools, and analytical capabilities that cater to the needs of planetary scientists and mission planners. This abstract explores how CMS has been leveraged to conduct in-depth analyses of 12 lunar missions to the South Pole, including missions like Chandraayan 3, Russian Space Agency's Luna 25, Xelene 1, and Intuitive Machines Nova-C lander I. Moreover, the integration of HORUS (Hyper-effective nOise Removal Unit Software) into CMS enhances its capabilities, allowing for the rendering of images in a 3D globe format and providing visibility into permanently shadowed regions. CMS represents a cutting-edge tool for lunar surface awareness, equipment placement planning, and traverse path optimization

Moon↗
NASA NTRS1979

Analytic modeling of aerosol size distributions

Mathematical functions commonly used for representing aerosol size distributions are studied parametrically. Methods for obtaining best fit estimates of the parameters are described. A catalog of graphical plots depicting the parametric behavior of the functions is presented along with procedures for obtaining analytical representations of size distribution data by visual matching of the data with one of the plots. Examples of fitting the same data with equal accuracy by more than one analytic model are also given.

Deepack, A.↗