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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 1,171 records · Page 65

Visualization and Quantification of Rotor Tip Vortices in Helicopter Flows

Helicopter aeromechanics encompasses a highly vortical flow field. The vortices generated at each blade tip contain unsteady, complex, three-dimensional structures, which interact with each other, other blades, the fuselage and various components of the helicopter. It is crucial to understand vortex kinematics and their subsequent dynamic evolution. Much research has been devoted to the understanding of helicopter vortex dynamics, including a number of experimental studies.1-6 In May 2010 Particle Image Velocimetry (PIV) measurements of a full-scale UH-60A rotor were acquired in the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel.1 These measurements were taken at a plane just downstream of the advancing blade in the vicinity of the blade tip—the so-called PIV plane. The resulting PIV data were then processed using an ensemble-average approach to create graphical representations of the vortical wake velocity and vorticity fields, which, in turn, have enhanced the understanding of rotorcraft vortical wake flow field physics and have provided a more detailed validation of vortical wake computer simulations.7 A common approach used to analyze flow field features is to compute and plot color contour maps of various scalar quantities such as pressure, velocity magnitude and vorticity magnitude. For example, the color map of the vorticity magnitude is typically used to determine vortical flow structure. With this approach the vortex core may appear larger or smaller, depending on the contour levels that are selected. Thus, the resulting visualization is sensitive to user-specified contour levels. For vortex core radius measurements, it is more accurate to calculate the vortex core radius using the cross-flow velocity profile across the vortex core. The task of extracting the cross-flow velocity profile can be time consuming with existing tools since the user needs to manually select the core center then specify sampling points along the profile axis. The task becomes even more challenging when the associated grid system uses AMR (Adaptive Mesh Refinement) where the profile axis could span multiple grid blocks. There are a number of existing techniques for profiling of vortex core attributes;8-9 however, these techniques are not fully automatic in that the user still needs to select the vortex core center to compute the cross-flow velocity profile. The present study introduces a new color map scheme that is based on the vortex core radius, which is fully automatic and does not require user intervention. Analysis and visualization of blade tip vortices on the PIV plane using the proposed new color map scheme are described in Section II. The new approach is evaluated using two case studies, which are described in Section III. The paper ends with a summary in Section IV.

Quantification↗

A Qualitative Review of Selected Infrared Flow Visualization Processing Techniques: Contrast Enhancement and Frequency Domain Analysis

The deployment and integration of high-sensitivity infrared cameras in a transonic wind tunnel test environment has resulted in a unique capability to image aerodynamic phenomena in real-time. Multi-camera infrared flow visualization data systems are now routinely utilized at the NASA Ames Unitary Plan Wind Tunnel. The small flow-induced temperature gradients on the surface of the wind tunnel test article coupled with the high bit-depth of the infrared camera sensor makes the processing of the image data critically important. An image processing routine must enhance features of interest with minimal artifacts. Additionally, the production wind tunnel test environment demands that these processed images are made available in a real-time, automatic fashion. Therefore, any image processing routine must be computationally economical and enhance the image data with minimal input from a human operator. The following seeks to qualitatively explore selected image processing techniques by assessing their effectiveness to resolve flow features on a wind tunnel test article. A multi-scale contrast enhancement technique is introduced as well as a new implementation of a multi-scale, non-interpolated adaptive histogram equalization. Finally, a novel method is introduced that demonstrates the ability to resolve flow features imaged on bare-steel test articles possessing low emissivity. This method merges frequency domain analysis with contrast enhancement and has the potential to extend the application of infrared flow-visualization within the wind tunnel test environment.

Infrared Imaging↗

LaRC SmartLab Apps For Instrument Control And Data Processing: Optical Micrometer Data Visualizer

The LaRC Smart Lab applications are a series of software tools to greatly enhance researcher efficiency by streamlining and automating workflows. Python scripts and applications are increasingly being used in scientific workflows, including for instrument control and data processing. Interactive Python scripting environments such as Jupyter Lab provide powerful tools for using Python. In some use cases, the development of standalone applications with dedicated graphical user interfaces (GUIs) can enhance the utility of the code and open it up to more users, including non-programmers. Here, we describe a GUI based optical micrometer data visualization application developed as part of the LaRC SmartLab project. We highlight its use in visualizing experimental data and briefly discuss its implementation to give pointers to programmers who wish develop work based on this application's or similar co de.

LaRC SmartLab↗

Visualization of Upcoming ISS Changes - Featuring MLM Install

The MAGIK Robotic analysis team provides kinematic feasibility assessments and robotic visualizations for the ISS. The latest visualization displays ISS planned operations in increments 65 and 66 as of the 7/6/21 flight plan. Featured events include the arrival of the Multipurpose Laboratory Module (MLM) and surrounding visiting vehicle actions. The complete list of actions shown include: Repeated ISS attitude adjustment maneuvers from: starting position with positive X Velocity Vector (+XVV), yaw to -XVV, and pitch to final position with -ZVV. Then subsequent return to -XVV and nominal position +XVV. Crew-2 relocation from Node 2 Forward (N2F) to Node 2 Zenith (N2Z). 77 Progress with Docking Compartment 1 (DC1) undock and departure. MLM install. Boe-OFT2 arrival and departure at N2F. NG-16 arrival and berth at Node 1 Nadir (N1N). SpX-23 arrival at N2F. 64 Soyuz relocation and fly-around. SpX-23 departure from N2F. 65 Soyuz approach and dock to MRM-1. 64 Soyuz undock and departure. 78 Progress relocation.

ISS↗

Experiment Design and Visualization Techniques for an X-59 Low-boom Variability Study

This presentation outlines the design of experiments approach and data visualization techniques for a simulation study of sonic booms from NASA’s X-59 supersonic aircraft. The X-59 will soon be flown over communities across the contiguous USA as it produces a low-loudness sonic boom, or low-boom. Survey data on human perception of low-booms will be collected to support development of potential future commercial supersonic aircraft noise regulatory standards. The macroscopic atmosphere plays a critical role in the loudness of sonic booms. The extensive sonic boom simulation study presented herein was completed to assess climatological, geographical, and seasonal effects on the variability of the X-59’s low-boom loudness and noise exposure region size in order to inform X-59 community test planning. The loudness and extent of the noise exposure region make up the “sonic boom carpet.” Two spatial and temporal resolutions of atmospheric input data to the simulation were investigated. A Fast Flexible Space-Filling Design was used to select the locations across the USA for the two spatial resolutions. Analysis of simulated X-59 low-boom loudness data within a regional subset of the northeast USA was completed using a bootstrap forest to determine the final spatial and temporal resolution of the countrywide simulation study. Atmospheric profiles from NOAA’s Climate Forecast System Version 2 database were used to generate over one million simulated X-59 carpets at the final selected 138 locations across the USA. Effects of aircraft heading, season, geography, and climate zone on low-boom levels and noise exposure region size were analyzed. Models were developed to estimate loudness metrics throughout the USA for X-59 supersonic cruise overflight, and results were visualized on maps to show geographical and seasonal trends. These results inform regulators and mission planners on expected variations in boom levels and carpet extent from atmospheric variations. Understanding potential carpet variability is important when planning community noise surveys using the X-59.

X-59↗

Experience in Visualizing Satellite Data With AR/VR Technologies at NASA's GES-DISC

The Goddard Earth Sciences Data and Information Services Center (GES-DISC) at NASA plays a crucial role in archiving and disseminating vital Earth science data. In this project, we leverage immersive visualization technologies to reshape engagement with and comprehension of the intricate datasets of our planet. Through the adoption of immersive technologies, we are enhancing established methods, offering novel, intuitive experiences in visualizing and interacting with Earth science data. Our goal is to contribute to the ongoing evolution of data interaction, pushing the boundaries of what's possible in data interpretation and education.

Visualization↗

Improvements to GCAS Visualization Functionality

Analysis of communication systems is crucial to NASA objectives, whether located here on Earth or on a cosmic scale. The Glenn Research Center Communication Analysis Suite (GCAS) is software designed for analysis of communication systems throughout the solar system. This suite includes web-based visualization software that is used to simulate the data generated from the GCAS MATLAB® (The MathWorks, Inc.) capability. This report focuses on recent additions to the visualization portion of GCAS, including the motivation and methodology behind them. Notable additions include improved camera controls, such as novel first- and third-person settings, methods for displaying pertinent analysis information, finer control over timing mechanisms, and automated features designed to improve efficiency and memory usage.

Visualization↗

Full Lunar Surface Visualization and Simulation Platform

This paper reports the results of the innovative work completed to facilitate the creation of a lunar surface visualization and simulation platform for the entire surface of the moon as a design, test, training, verification, and mission support environment. The mathematical approach to the visualization of the data sets utilizes fractal mathematics to generate not only the highest possible detail that the Lunar Reconnaissance Orbiter (LRO) data can provide, but it also additionally supplies an estimation of surface reflectivity and lighting based upon location on the lunar surface. This level of detail and accuracy is required to conduct accurate integrated crew / vehicle risk assessment throughout the design-to-disposal life cycle of vehicles and their supporting procedures and mission priorities. This process starts with safety assessments of integrated hardware / software / crew/ and support environments. Unlike the Apollo Program, the Artemis Program is not risk tolerant.

Simulation↗

NASA Giovanni: Analyze, Compare, and Visualize 2000+ Earth Satellite and Model Variables Without Downloading Data and Software

Over vast oceans and remote continents, observations are often scarce and discontinuous. Satellite and model data play a critical role in research and applications. However, finding and accessing satellite and model data can be a daunting task for many, especially those outside the community. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA Science Mission Directorate Data Centers, provides Earth science data, information, and services to everyone such as researchers, application users, educators, and students. GES DISC archives and supports datasets applicable to several NASA Earth Science Focus Areas including Atmospheric Composition, Water & Energy Cycles, Carbon Cycle & Ecosystem, and Climate Variability. To facilitate data discovery, evaluation, and exploration, GES DISC has developed the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni), an online tool to analyze and visualize NASA remote sensing and model data without downloading data and software. As of this writing, over 2000 Earth satellite and model variables are available in Giovanni, including several wellknown NASA satellite missions (e.g., TRMM, GPM) and projects (e.g., MERRA-2, GPCP). Giovanni provides twenty-two plots that can be used to analyze, compare, and explore Earth data across different disciplines. Results can be shared with colleagues and downloaded for further analysis. Over the years, Giovanni has helped publish over 3000 referral papers. In this presentation, we will showcase key variables and plot types in Giovanni with examples. In particular, we will present several popular precipitation products from GPM and CPCP for evaluation and comparison.

data analysis↗

Quantification and Visualization of Variation in Anatomical Trees

This paper presents two approaches to quantifying and visualizing variation in datasets of trees. The first approach localizes subtrees in which significant population differences are found through hypothesis testing and sparse classifiers on subtree features. The second approach visualizes the global metric structure of datasets through low-distortion embedding into hyperbolic planes in the style of multidimensional scaling. A case study is made on a dataset of airway trees in relation to Chronic Obstructive Pulmonary Disease.

dataset, tree, quantification, visualization↗

Coupling Visualization, Simulation, and Deep Learning for Ensemble Steering of Complex Energy Models: Preprint

We have developed a framework for the exploration, design, and planning of energy systems that combines interactive visualization with machine-learning based approximations of simulations through a general purpose dataflow API. Our system provides a visual inter- face allowing users to explore an ensemble of energy simulations representing a subset of the complex input parameter space, and spawn new simulations to 'fill in' input regions corresponding to new enegery system scenarios. Unfortunately, many energy simula- tions are far too slow to provide interactive responses. To support interactive feedback, we are developing reduced-form models via machine learning techniques, which provide statistically sound esti- mates of the full simulations at a fraction of the computational cost and which are used as proxies for the full-form models. Fast com- putation and an agile dataflow enhance the engagement with energy simulations, and allow researchers to better allocate computational resources to capture informative relationships within the system and provide a low-cost method for validating and quality-checking large-scale modeling efforts.

97 MATHEMATICS AND COMPUTING↗

Storyline Visualization: A Compelling Way to Understand Patterns over Time and Space

Storyline visualization is a compelling way to understand patterns over time and space. Much effort has been spent developing efficient and aesthetically pleasing layout optimization algorithms. But what if those algorithms are optimizing the wrong things? To answer this question, we conducted a design study with different storyline layout algorithms. We found that users with our new design principles for storyline visualization outperform existing methods.

97 MATHEMATICS AND COMPUTING↗

An Interactive Visualization Tool for Large-Scale Building Stock Modeling

Recent advancements in data science and high-performance computing are making it easier to run millions of building simulations, but meaningful visualization of such large datasets remains a challenge. This paper presents a new tool developed to view the results of large-scale OpenStudio simulations of national, regional, or local building stocks. The tool processes millions of simulations to calculate measure savings, utility bills, carbon emissions, primary energy, and cost-effectiveness metrics at a high geographic resolution. Interactive visualizations of the building characteristics, consumption, and measure savings data include proportional symbol maps and histogram plots and can be filtered by any building characteristic.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Can You Verifi This? Studying Uncertainty and Decision-Making About Misinformation using Visual Analytics

We describe a novel study of decision-making processes around misinformation on social media. Using a custom-built visual analytic system, we presented users with news content from social media accounts from a variety of news outlets, including outlets engaged in distributing misinformation. We conducted controlled experiments to study decision-making regarding the veracity of these news outlets and tested the role of confirmation bias (the tendency to ignore contradicting information) and uncertainty of information on human decision-making processes. Our findings reveal that the presence of conflicting information, presented to users in the form of cues, impacts the ability to judge the veracity of news in systematic ways. We also find that instructing participants even to explicitly disconfirm given hypotheses does not significantly impact their decision-making regarding misinformation when compared to a control condition. Our findings have the potential to inform the design of visual analytics systems so that they may be used to mitigate the effects of cognitive biases and stymie the spread of misinformation on social media.

misinformation, decision making, social media, vis↗

Visualization of Jet Impingement and Ignition in a Piston-Cylinder Chamber

The transportation sector accounts for almost a third of the United States energy consumption. We are developing predictive simulations of the complex in-cylinder processes of internal combustion engines to improve performance and decrease pollutant emissions. Using volume rendering, we provide a first look at the jet impingement and ignition inside a piston-cylinder chamber. Through the visualization, we were able to construct a complete 3D picture of the jet impingement on the piston-bowl walls leading to the formation of pockets of auto-ignition of fuel-air mixture. These auto-ignition pockets subsequently lead to flame stabilization releasing the chemical energy for conversion to useful work. A detailed physical picture of flame stabilization as provided by the visualization techniques presented in this study help in the design next-generation internal combustion engines.

91 SC - Advanced Scientific Computing Reseach (ASC↗

An Interactive Visualization Tool for Large-Scale Building Stock Modeling: Preprint

Recent advancements in data science and high-performance computing are making it easier to run millions of building simulations, but meaningful visualization of such large datasets remains a challenge. This paper presents a new tool developed to view the results of large-scale OpenStudio simulations of national, regional, or local building stocks. The tool processes millions of simulations to calculate measure savings, utility bills, carbon emissions, primary energy, and cost-effectiveness metrics at a high geographic resolution. Interactive visualizations of the building characteristics, consumption, and measure savings data include proportional symbol maps and histogram plots and can be filtered by any building characteristic.

big data↗

Alternatives to Contour Visualizations for Power Systems Data

Electrical grids are geographical and topological structures whose voltage states are challenging to represent accurately and efficiently for visual analysis. The current common practice is to use colored contour maps, yet these can misrepresent the data. We examine the suitability of four alternative visualization methods for depicting voltage data in a geographically dense distribution system-Voronoi polygons, H3 tessellations, S2 tessellations, and a network-weighted contour map. We find that Voronoi tessellations and network-weighted contour maps more accurately represent the statistical distribution of the data than regular contour maps.

MATHEMATICS AND COMPUTING↗

Visualization of flow interaction in a channel flow produced by a pair of helically coiled rods

Helically coiled tubes have been considered in the design of steam generators or heat exchangers of next generation nuclear power plants. Its compactness, efficiency, and the capability to absorb thermal expansion are desirable for nuclear reactor designs. However, the complex flow generated by the helically coiled geometry can result in flow induced vibration (FIV). In order to predict the FIV, there have been efforts using Computational Fluid dynamics (CFD)4, 5 to be coupled with multi-mechanics simulations. However, it is required to validate CFD to have confidence in capturing the flow structure characteristics of the transient complex flow behavior and fluctuation. In the present study, a simplified helically coiled steam generator (HCSG) design experiment was built acquiring data for CFD validation purpose. It is not perfect representation of the multiple rods, however, the current test facility produced transient data of the flow interaction between the rods and flow fluctuations near the rods. Particle Image Velocimetry (PIV) was applied to visualize the turbulent flow in a channel with slant rods. The two dimensional turbulent flow fields were analyzed. The velocity components were defined as below. u = U + u' (1) v = V + v' (2) where u is the lateral velocity on x-axis, v is the vertical velocity on y-axis, U and V are the mean velocities, and u' and v' are the fluctuation. Reynolds number, Re, was calculated using the rod diameter, d = 15.9 mm, and the upstream approach velocity, V{sub 0} = 0.5 m/s. Re = V{sub 0} d/η (3) where η is the kinematic viscosity of water. The experiment was conducted at Re ≅ 9,000 considering the currently reasonable computing power. Flow visualization in a flow channel produced by helically coiled rods was performed using PIV. The mean velocity field and streamlines were presented in this paper. The vortical flow structures in the cavity between rods were observed. Because of the asymmetric geometry, the flow profile was skewed. Additional measurements and transient analysis will be conducted to produce benchmark data for FIV study using CFD. Also, a test facility with a 5-rod heat exchanger design is operating to produce more data as a further work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗