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Results for “analysis and 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.

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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Long term storage test of titanium material with liquid fluorine propellant

The compatibility of 6AL-4V Ti with propellant grade GF2 and LF2 at 77 K for up to 3 years was investigated. Titanium double coupons, annealed or heat treated, with 16 or 64 RMS finishes, were immersed in F2 in individual Pyrex capsules and stored under LN2 for 29 and 39 months. Pre and post immersion tests were performed on the propellant and coupons. Chemical analysis of the propellant did not reveal any significant changes due to titanium corrosion. Gravimetric, visual, microscopic, and metallurgical examination with pitting analysis did not reveal gross corrosion of the titanium although pitting appears to be greater after 39 months exposure. The increase in pit size and number raises the possibility of unpredictable crack propagation instability. Fracture toughness tests are necessary to define this possibility.

Denson, J. R.↗
NASA NTRS2014

A Cloud-Based Global Flood Disaster Community Cyber-Infrastructure: Development and Demonstration

Flood disasters have significant impacts on the development of communities globally. This study describes a public cloud-based flood cyber-infrastructure (CyberFlood) that collects, organizes, visualizes, and manages several global flood databases for authorities and the public in real-time, providing location-based eventful visualization as well as statistical analysis and graphing capabilities. In order to expand and update the existing flood inventory, a crowdsourcing data collection methodology is employed for the public with smartphones or Internet to report new flood events, which is also intended to engage citizen-scientists so that they may become motivated and educated about the latest developments in satellite remote sensing and hydrologic modeling technologies. Our shared vision is to better serve the global water community with comprehensive flood information, aided by the state-of-the- art cloud computing and crowdsourcing technology. The CyberFlood presents an opportunity to eventually modernize the existing paradigm used to collect, manage, analyze, and visualize water-related disasters.

CyberFlood↗
NASA NTRS1995

elVis: An Interactive System For Visualization of Unsteady Fluid Flow

ElVis is a prototype system with allows for the interactive visualization of unsteady fluid flow. The increasing computational power applied to fluid dynamics simulations presents the enormous challenge to the visualization system designer to apply a wide range of technologies to the analysis process with ever increasing demands on performance. Visualization of the results of unsteady fluid flow simulations presents the challenge of exploring very large and complex data sets. Since exploration is a trial and error process, it is of utmost importance that the time required to execute a trial (i.e., create a visualization) be at a minimum in order to provide real time interaction.

Gerald-Yamasaki, Michael↗
DOE OSTI2023

FORCE Output Data Visualization

The Framework for Optimization of ResourCes and Economics (FORCE) is a collection of software tools, models, and datasets acquired and developed under the Integrated Energy Systems (IES) program to enable analysis of technical and economic viability of myriad IES configurations. Idaho National Laboratory is hosting a training session for FORCE users and developers, which is "Integrated Energy Systems Tools FORCE Overview and Training 2023." We will present data output visualization results with FORCE scenarios as examples and show how does the new design improve existing automated visualization for analysis results.

25 ENERGY STORAGE↗
NASA NTRS1995

Visualization of stratospheric ozone depletion and the polar vortex

Direct analysis of spacecraft observations of stratospheric ozone yields information about the morphology of annual austral depletion. Visual correlation of ozone with other atmospheric data illustrates the diurnal dynamics of the polar vortex and contributions from the upper troposphere, including the formation and breakup of the depletion region each spring. These data require care in their presentation to minimize the introduction of visualization artifacts that are erroneously interpreted as data features. Non geographically registered data of differing mesh structures can be visually correlated via cartographic warping of base geometries without interpolation. Because this approach is independent of the realization technique, it provides a framework for experimenting with many visualization strategies. This methodology preserves the fidelity of the original data sets in a coordinate system suitable for three-dimensional, dynamic examination of atmospheric phenomena.

Treinish, Lloyd A.↗
DOE OSTI2024

Direct evidence from STXM analysis of enhanced oxygen storage capacity in ceria through the addition of Cu and Mg: Correlation of HT-WGS reaction performance

Here, scanning transmission X-ray microscopy (STXM) analysis was utilized to directly present visual evidence of changes in oxygen storage capacity (OSC) when small amounts of an additive were incorporated into CeO2. Specifically, the chemical map measured by STXM analysis differentiated between Cu-rich and Ce-rich areas to derive the proportion of Ce3+. Additionally, we found that the dispersion of Cu significantly influenced the formation of OSC. The findings were applied to the high-temperature water–gas shift reaction for producing high-purity hydrogen from waste-derived syngas, establishing a correlation with catalyst performance. Consequently, the CCM75 (Ce/Mg = 75/25) catalyst demonstrated the highest Cu dispersion and OSC values (6.9 %, 800.3 μmolO/gcat), and it also showed the highest CO conversion (79 % at 450 °C) and stability (−7.7 % at 450 °C after 50 h), attributed to the significant presence of active Cu. This study confirms previously reported interactions between Cu and CeO2 and uncovers the significant roles of Cu and Mg in this catalysis system, providing new understanding of the mechanisms that facilitate OSC improvement.

Lee, Ru-Ri↗
DOE OSTI2021

Elucidating the Onset of Plasticity in Sliding Contacts Using Differential Computational Orientation Tomography

Abstract Depending on the mechanical and thermal energy introduced to a dry sliding interface, the near-surface regions of the mated bodies may undergo plastic deformation. In this work, we use large-scale molecular dynamics simulations to generate “differential computational orientation tomographs” (dCOT) and thus highlight changes to the microstructure near tribological FCC alloy surfaces, allowing us to detect subtle differences in lattice orientation and small distances in grain boundary migration. The analysis approach compares computationally generated orientation tomographs with their undeformed counterparts via a simple image analysis filter. We use our visualization method to discuss the acting microstructural mechanisms in a load- and time-resolved fashion, focusing on sliding conditions that lead to twinning, partial lattice rotation, and grain boundary-dominated processes. Extracting and laterally averaging the color saturation value of the generated tomographs allows us to produce quantitative time- and depth-resolved maps that give a good overview of the progress and severity of near-surface deformation. Corresponding maps of the lateral standard deviation in the color saturation show evidence of homogenization processes occurring in the tribologically loaded microstructure, frequently leading to the formation of a well-defined separation between deformed and undeformed regions. When integrated into a computational materials engineering framework, our approach could help optimize material design for tribological and other deformation problems. Graphic Abstract .

36 MATERIALS SCIENCE↗
NASA NTRS1996

Off-the-shelf real-time monitoring of satellite constellations in a visual 3-D environment

The multimission spacecraft analysis system (MSAS) data monitor is a generic software product for future real-time data monitoring and analysis. The system represents the status of a satellite constellation through the shape, color, motion and position of graphical objects floating in a three dimensional virtual reality environment. It may be used for the monitoring of large volumes of data, for viewing results in configurable displays, and for providing high level and detailed views of a constellation of monitored satellites. It is considered that the data monitor is an improvement on conventional graphic and text-based displays as it increases the amount of data that the operator can absorb in a given period, and can be installed and configured without the requirement for software development by the end user. The functionality of the system is described, including: the navigation abilities; the representation of alarms in the cybergrid; limit violation; real-time trend analysis, and alarm status indication.

Schwuttke, Ursula M.↗
DOE OSTI2021

Data processing pipeline for Tianlai experiment

The Tianlai project is a 21cm intensity mapping experiment for detecting dark energy by measuring the baryon acoustic oscillation (BAO) features in the large scale structure power spectrum. This experiment provides an opportunity to test the data processing methods for cosmological 21cm signal extraction, which is still a great challenge in current radio astronomy research. The 21cm signal is much weaker than the foregrounds and easily aected by the imperfections in the instrumental responses. Furthermore, processing the large volumes of interferometer data poses a practical challenge. We have developed a data processing pipeline called tlpipe to process the drift scan survey data from the Tianlai experiment. It performs oine data processing tasks such as radio frequency interference (RFI) agging, array calibration, binning, and map-making, etc. It also includes utility functions needed for the data analysis, such as data selection, transformation, visualization and others. A number of new algorithms are implemented, for example the eigenvector decomposition method for array calibration and the Tikhnov regularization for m-mode analysis. In this paper we describe the design and implementation of the pipeline and illustrate its functions with some analysis of real data. Finally, we outline directions for future development of this publicly code.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Using Earth Observations to Analyze Shoreline Changes and Understand the Effects of Sea Level Rise in Southern Puerto Rico

This summer, the Jobos Bay National Estuarine Research Reserve (JBNERR) partnered with NASA DEVELOP to evaluate water quality, mangrove forest extent, sea level rise, and land cover changes in Jobos Bay. DEVELOP is a national capacity building program that connects satellite data with early career scientists and decision makers. Through ten-week feasibility studies, DEVELOP partners with organizations that have the power to enact policy within their communities. Jobos Bay, in the southeast coast of Puerto Rico, has experienced intense hurricane seasons with increased seasonal storm surge, near-shore land use changes, and strong variations in precipitation and runoff. Through proposals, bi-weekly meetings, and frequent email communication, this cross-sector initiative provided valuable results for management decisions within the reserve. Using satellite observations to measure land use change, the team found that 17% of the reserve has shifted from land to water along the coast since 1997. Using Sentinel-2 the team was able to visualize turbidity, chlorophyll-a, and colored dissolved organic matter (CDOM) for Jobos Bay. While some large events such as Hurricane Maria were reflected in the turbidity analysis, chlorophyll-a and CDOM visualizations were limited by the influence of shallow-water bottom reflectance, particularly around reefs and within the Bay. The team also found that Jobos Bay lost 4.9 square kilometers of mangrove habitat over the past decade, calculated using Landsat 7 and 8 within Google Earth Engine. The results from this study will inform JBNERR and its community members on the regional impacts of sea level rise as well as serve as a baseline for future conservation efforts and research in the estuary.

Olivia Spencer↗
NASA NTRS1998

Effect of altered sensory conditions on multivariate descriptors of human postural sway

Multivariate descriptors of sway were used to test whether altered sensory conditions result not only in changes in amount of sway but also in postural coordination. Eigenvalues and directions of eigenvectors of the covariance of shnk and hip angles were used as a set of multivariate descriptors. These quantities were measured in 14 healthy adult subjects performing the Sensory Organization test, which disrupts visual and somatosensory information used for spatial orientation. Multivariate analysis of variance and discriminant analysis showed that resulting sway changes were at least bivariate in character, with visual and somatosensory conditions producing distinct changes in postural coordination. The most significant changes were found when somatosensory information was disrupted by sway-referencing of the support surface (P = 3.2 x 10(-10)). The resulting covariance measurements showed that subjects not only swayed more but also used increased hip motion analogous to the hip strategy. Disruption of vision, by either closing the eyes or sway-referencing the visual surround, also resulted in altered sway (P = 1.7 x 10(-10)), with proportionately more motion of the center of mass than with platform sway-referencing. As shown by discriminant analysis, an optimal univariate measure could explain at most 90% of the behavior due to altered sensory conditions. The remaining 10%, while smaller, are highly significant changes in posture control that depend on sensory conditions. The results imply that normal postural coordination of the trunk and legs requires both somatosensory and visual information and that each sensory modality makes a unique contribution to posture control. Descending postural commands are multivariate in nature, and the motion at each joint is affected uniquely by input from multiple sensors.

NASA Discipline Neuroscience↗
NASA NTRS2005

Radiation Mitigation and Power Optimization Design Tools for Reconfigurable Hardware in Orbit

The Reconfigurable Hardware in Orbit (RHinO)project is focused on creating a set of design tools that facilitate and automate design techniques for reconfigurable computing in space, using SRAM-based field-programmable-gate-array (FPGA) technology. In the second year of the project, design tools that leverage an established FPGA design environment have been created to visualize and analyze an FPGA circuit for radiation weaknesses and power inefficiencies. For radiation, a single event Upset (SEU) emulator, persistence analysis tool, and a half-latch removal tool for Xilinx/Virtex-II devices have been created. Research is underway on a persistence mitigation tool and multiple bit upsets (MBU) studies. For power, synthesis level dynamic power visualization and analysis tools have been completed. Power optimization tools are under development and preliminary test results are positive.

French, Matthew↗
DOE OSTI2023

ExaWind at NREL: Upping the Ante

The objective of the ExaWind component of the Exascale Computing Project is to deliver many-turbine blade-resolved simulations in complex terrain. These simulations bring new challenges to both compute and analysis of the resulting data. In this paper/video, we visually explore the impact of ExaWind on wind simulations through two studies of a small wind farm under two atmospheric conditions. We then turn to analysis and review tools that visualization researchers at NREL use to answer the challenges that ExaWind brings.

collaborative visualization↗
DOE OSTI2022

Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: Comparison with linear subspace techniques

Natural convection in porous media is a highly nonlinear multiphysical problem relevant to many engineering applications (e.g., the process of CO 2 sequestration). Here, we extend and present a non-intrusive reduced order model of natural convection in porous media employing deep convolutional autoencoders for the compression and reconstruction and either radial basis function (RBF) interpolation or artificial neural networks (ANNs) for mapping parameters of partial differential equations (PDEs) on the corresponding nonlinear manifolds. To benchmark our approach, we also describe linear compression and reconstruction processes relying on proper orthogonal decomposition (POD) and ANNs. Further, we present comprehensive comparisons among different models through three benchmark problems. The reduced order models, linear and nonlinear approaches, are much faster than the finite element model, obtaining a maximum speed-up of 7 × 10 6 because our framework is not bound by the Courant–Friedrichs–Lewy condition; hence, it could deliver quantities of interest at any given time contrary to the finite element model. Our model’s accuracy still lies within a relative error of 7% in the worst-case scenario. We illustrate that, in specific settings, the nonlinear approach outperforms its linear counterpart and vice versa. We hypothesize that a visual comparison between principal component analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) could indicate which method will perform better prior to employing any specific compression strategy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Inferring the shape of data: a probabilistic framework for analysing experiments in the natural sciences

A critical step in data analysis for many different types of experiments is the identification of features with theoretically defined shapes in N -dimensional datasets; examples of this process include finding peaks in multi-dimensional molecular spectra or emitters in fluorescence microscopy images. Identifying such features involves determining if the overall shape of the data is consistent with an expected shape; however, it is generally unclear how to quantitatively make this determination. In practice, many analysis methods employ subjective, heuristic approaches, which complicates the validation of any ensuing results—especially as the amount and dimensionality of the data increase. Here, we present a probabilistic solution to this problem by using Bayes’ rule to calculate the probability that the data have any one of several potential shapes. This probabilistic approach may be used to objectively compare how well different theories describe a dataset, identify changes between datasets and detect features within data using a corollary method called Bayesian Inference-based Template Search; several proof-of-principle examples are provided. Altogether, this mathematical framework serves as an automated ‘engine’ capable of computationally executing analysis decisions currently made by visual inspection across the sciences.

Science & Technology - Other Topics↗
DOE OSTI2022

LungMAP Portal Ecosystem: Systems-level Exploration of the Lung

An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging, and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a new gateway portal. This portal connects a broad spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development, and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease, and drug treatment. These atlases are provided as independent and integrated queryable datasets, with an emphasis on dynamic visualization, figure generation, re-analysis, cell-type curation, and automated reference-based classification of user-provided single-cell genomics datasets (Azimuth). Finally, as this resource grows, we intend to increase the breadth of available interactive interfaces, supported data types, data portals and datasets from LungMAP and external research efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

RETRO RX

RETRO Rx is an R&D 100 Gold Award-winning suite of tools that provides a new class of analytics in the space between traditional epidemiological models and unanalyzed spreadsheets of data. Unlike traditional models, these tools provide analysts, scientists, practitioners, and decision makers a way to easily and effectively do sophisticated analyses using a simple user interface. AIDO guides users at the early stages of a disease outbreak by comparing the current parameters to historic outbreaks. RED Alert constructs a broad historical picture of disease incidence (recent outbreak included) to detect disease reemergence at its earliest stages, locally and globally. RETRO Rx compiles data and presents analysis in a clear, concise visual format to support disease mitigation and prevention planning. Both are available currently as web-based apps. A prototype of the RED Alert mobile app with enhanced functionality is available for beta testing and AIDO mobile app development is planned.

59 BASIC BIOLOGICAL SCIENCES↗