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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Neurofilament protein is differentially distributed in subpopulations of corticocortical projection neurons in the macaque monkey visual pathways

Previous studies of the primate cerebral cortex have shown that neurofilament protein is present in pyramidal neuron subpopulations displaying specific regional and laminar distribution patterns. In order to characterize further the neurochemical phenotype of the neurons furnishing feedforward and feedback pathways in the visual cortex of the macaque monkey, we performed an analysis of the distribution of neurofilament protein in corticocortical projection neurons in areas V1, V2, V3, V3A, V4, and MT. Injections of the retrogradely transported dyes Fast Blue and Diamidino Yellow were placed within areas V4 and MT, or in areas V1 and V2, in 14 adult rhesus monkeys, and the brains of these animals were processed for immunohistochemistry with an antibody to nonphosphorylated epitopes of the medium and heavy molecular weight subunits of the neurofilament protein. Overall, there was a higher proportion of neurons projecting from areas V1, V2, V3, and V3A to area MT that were neurofilament protein-immunoreactive (57-100%), than to area V4 (25-36%). In contrast, feedback projections from areas MT, V4, and V3 exhibited a more consistent proportion of neurofilament protein-containing neurons (70-80%), regardless of their target areas (V1 or V2). In addition, the vast majority of feedback neurons projecting to areas V1 and V2 were located in layers V and VI in areas V4 and MT, while they were observed in both supragranular and infragranular layers in area V3. The laminar distribution of feedforward projecting neurons was heterogeneous. In area V1, Meynert and layer IVB cells were found to project to area MT, while neurons projecting to area V4 were particularly dense in layer III within the foveal representation. In area V2, almost all neurons projecting to areas MT or V4 were located in layer III, whereas they were found in both layers II-III and V-VI in areas V3 and V3A. These results suggest that neurofilament protein identifies particular subpopulations of corticocortically projecting neurons with distinct regional and laminar distribution in the monkey visual system. It is possible that the preferential distribution of neurofilament protein within feedforward connections to area MT and all feedback projections is related to other distinctive properties of these corticocortical projection neurons.

Non-NASA Center↗
NASA NTRS1995

Using Visual Programming to Simulate, Test, and Display a Telemetry Stream

Advantages of using visual programming to create, modify, test and display a telemetry stream are presented. Commercial visual programming software is being used to test new algorithms as part of the ground support for the Galileo spacecraft Test Bed.

visual programming real-time data display text-bas↗
NASA NTRS1994

Experience Report: Visual Programming in the Real World

This paper reports direct experience with two commercial, widely used visual programming environments. While neither of these systems is object oriented, the tools have transformed the development process and indicate a direction for visual object oriented tools to proceed.

visual programming↗
NASA NTRS2003

Visualization experiences and issues in Deep Space Exploration

The panelists will discuss their experiences in collecting data in deep space, transmitting it to Earth, processing and visualizing it here, and using the visualization to drive the continued mission. This closes the loop, making missions more responsive to their environment, particularly in-situ operations on planetary surfaces and within planetary atmospheres.

visualization↗
NASA NTRS2007

Visualization of Concurrent Program Executions

Various program analysis techniques are efficient at discovering failures and properties. However, it is often difficult to evaluate results, such as program traces. This calls for abstraction and visualization tools. We propose an approach based on UML sequence diagrams, addressing shortcomings of such diagrams for concurrency. The resulting visualization is expressive and provides all the necessary information at a glance.

concurrent programs↗
NASA NTRS2014

Three Dimensional Lightning Launch Commit Criteria Visualization Tool

Lightning occurrence too close to a NASA LSP or future SLS program launch vehicle in flight would have disastrous results. The sensitive electronics on the vehicle could be damaged to the point of causing an anomalous flight path and ultimate destruction of the vehicle and payload.According to 45th Weather Squadron (45 WS) Lightning Launch Commit Criteria (LLCC), a vehicle cannot launch if lightning is within 10 NM of its pre-determined flight path. The 45 WS Launch Weather Officers (LWOs) evaluate this LLCC for their launch customers to ensure the safety of the vehicle in flight. Currently, the LWOs conduct a subjective analysis of the distance between lightning and the flight path using data from different display systems. A 3-D display in which the lightning data and flight path are together would greatly reduce the ambiguity in evaluating this LLCC. It would give the LWOs and launch directors more confidence in whether a GO or NO GO for launch should be issued. When lightning appears close to the path, the LWOs likely err on the side of conservatism and deem the lightning to be within 10 NM. This would cause a costly delay or scrub. If the LWOs can determine with a strong level of certainty that the lightning is beyond 10 NM, launch availability would increase without compromising safety of the vehicle, payload or, in the future, astronauts.The AMU was tasked to conduct a market research of commercial, government, and open source software that might be able to ingest and display the 3-D lightning data from the KSC Lightning Mapping Array (LMA), the 45th Space Wing Weather Surveillance Radar (WSR), the National Weather Service in Melbourne Weather Surveillance Radar 1988 Doppler (WSR-88D), and the vehicle flight path data so that all can be visualized together. To accomplish this, the AMU conducted Internet searches for potential software candidates and interviewed software developers.None of the available off-the-shelf software had a 3-D capability that could display all of the data in a single visualization. The AMU determined there are two viable software packages that could satisfy the 45 WS requirement with further development and recommends the KSC Weather Office follow-up with both organizations to request development costs.

weather↗
NASA NTRS2014

Design Visualization Internship Overview

This is a report documenting the details of my work as a NASA KSC intern for the Summer Session from June 2nd to August 8th, 2014. This work was conducted within the Design Visualization Group, a Contractor staffed organization within the C1 division of the IT Directorate. The principle responsibilities of the KSC Design Visualization Group are the production of 3D simulations of NASA equipment and facilities for the purpose of planning complex operations such as hardware transportation and vehicle assembly. My role as an intern focused on aiding engineers in using 3D scanning equipment to obtain as-built measurements of NASA facilities, as well as using CATIA and DELMIA to process this data. My primary goals for this internship focused on expanding my CAD knowledge and capabilities, while also learning more about technologies I was previously unfamiliar with, such as 3D scanning. An additional goal of mine was to learn more about how NASA operates, and how the U.S. Space Program operates on a day-to-day basis. This opportunity provided me with a front-row seat to the daily maneuvers and operations of KSC and NASA as a whole. Each work day, I was able to witness, and even take part of, a small building block of the future systems that will take astronauts to other worlds. After my experiences this summer, not only can I say that my goals have been met, but also that this experience has been the highlight of my experience in higher education.

Telescience↗
NASA NTRS2015

Visualization and Quantification of Rotor Tip Vortices in Helicopter Flows

This paper presents an automated approach for effective extraction, visualization, and quantification of vortex core radii from the Navier-Stokes simulations of a UH-60A rotor in forward flight. We adopt a scaled Q-criterion to determine vortex regions and then perform vortex core profiling in these regions to calculate vortex core radii. This method provides an efficient way of visualizing and quantifying the blade tip vortices. Moreover, the vortices radii are displayed graphically in a plane.

Quantification↗
NASA NTRS2013

Ultrascale Visualization of Climate Data

Fueled by exponential increases in the computational and storage capabilities of high-performance computing platforms, climate simulations are evolving toward higher numerical fidelity, complexity, volume, and dimensionality. These technological breakthroughs are coming at a time of exponential growth in climate data, with estimates of hundreds of exabytes by 2020. To meet the challenges and exploit the opportunities that such explosive growth affords, a consortium of four national laboratories, two universities, a government agency, and two private companies formed to explore the next wave in climate science. Working in close collaboration with domain experts, the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) project aims to provide high-level solutions to a variety of climate data analysis and visualization problems.

analysis tools↗
NASA NTRS2015

Visual Stability of Objects and Environments Viewed through Head-Mounted Displays

Virtual Environments (aka Virtual Reality) is again catching the public imagination and a number of startups (e.g. Oculus) and even not-so-startup companies (e.g. Microsoft) are trying to develop display systems to capitalize on this renewed interest. All acknowledge that this time they will get it right by providing the required dynamic fidelity, visual quality, and interesting content for the concept of VR to take off and change the world in ways it failed to do so in past incarnations. Some of the surprisingly long historical background of the technology that the form of direct simulation that underlies virtual environment and augmented reality displays will be briefly reviewed. An example of a mid 1990's augmented reality display system with good dynamic performance from our lab will be used to illustrate some of the underlying phenomena and technology concerning visual stability of virtual environments and objects during movement. In conclusion some idealized performance characteristics for a reference system will be proposed. Interestingly, many systems more or less on the market now may actually meet many of these proposed technical requirements. This observation leads to the conclusion that the current success of the IT firms trying to commercialize the technology will depend on the hidden costs of using the systems as well as the development of interesting and compelling content.

virtual environment↗
NASA NTRS2017

Weather from 250 Miles Up: Visualizing Precipitation Satellite Data (and Other Weather Applications) Using CesiumJS

Geospatial weather visualization remains predominately a two-dimensional endeavor. Even popular advanced tools like the Nullschool Earth display 2-dimensional fields on a 3-dimensional globe. Yet much of the observational data and model output contains detailed three-dimensional fields. In 2014, NASA and JAXA (Japanese Space Agency) launched the Global Precipitation Measurement (GPM) satellite. Its two instruments, the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) observe much of the Earth's atmosphere between 65 degrees North Latitude and 65 degrees South Latitude. As part of the analysis and visualization tools developed by the Precipitation Processing System (PPS) Group at NASA Goddard, a series of CesiumJS [Using Cesium Markup Language (CZML), JavaScript (JS) and JavaScript Object Notation (JSON)] -based globe viewers have been developed to improve data acquisition decision making and to enhance scientific investigation of the satellite data. Other demos have also been built to illustrate the capabilities of CesiumJS in presenting atmospheric data, including model forecasts of hurricanes, observed surface radar data, and gridded analyses of global precipitation. This talk will present these websites and the various workflows used to convert binary satellite and model data into a form easily integrated with CesiumJS.

web applications↗
NASA NTRS2018

Live Aircraft Encounter Visualization at FutureFlight Central

Researchers at the National Aeronautics and Space Administration (NASA) have developed an aircraft data streaming capability that can be used to visualize live aircraft in near real-time. During a joint Federal Aviation Administration (FAA)/NASA Airborne Collision Avoidance System flight series, test sorties between unmanned aircraft and manned intruder aircraft were shown in real-time at NASA Ames' FutureFlight Central tower facility as a virtual representation of the encounter. This capability leveraged existing live surveillance, video, and audio data streams distributed through a Live, Virtual, Constructive test environment, then depicted the encounter from the point of view of any aircraft in the system showing the proximity of the other aircraft. For the demonstration, position report data were sent to the ground from on-board sensors on the unmanned aircraft. The point of view can be change dynamically, allowing encounters from all angles to be observed. Visualizing the encounters in real-time provides a safe and effective method for observation of live flight testing and a strong alternative to travel to the remote test range.

Video Streaming↗
NASA NTRS2019

A Qualitative Investigation of Selected Infrared Flow Visualization Image Processing Techniques

The deployment and integration of high-sensitivity infrared cameras in a transonic wind tunnel testenvironment 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 discussed 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 makes use of dynamic mode decomposition and discrete-time filtering to separate the background reflections that dominate low emissivity surfaces from the aerodynamic driven surface temperature gradients.This process will be shown to resolve the onset of boundary layer transition on a bare metal wing as well as identify and resolve hidden features in the image data. While the implementation of this technique is very preliminary it demonstrates the potential to extend the application of infrared flow-visualization within the wind tunnel test environment.

Image Processeing↗
NASA NTRS2015

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↗
NASA NTRS2019

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↗
NASA NTRS2020

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↗
NASA NTRS2021

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↗