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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Scientific Visualization of Large Scale Unsteady Fluid Flow

In a numerical flow simulation. it is common to generate several thousand time steps of unsteady (time-dependent) flow data. Each time step may require tens to hundreds of megabytes for disk storage, and the total disk requirement for storing the unsteady flow data may be hundreds of gigabytes. Interactive visualization of unsteady flow data of this magnitude is presently impossible with the current hardware technology. This chapter describes the current approaches for unsteady flow visualization. An effective particle tracing technique for unsteady flow is also described. First, the life cycle of a typical numerical flow simulation is outlined. Several unsteady flow data sets from real-world problems are then given. The current approaches for visualizing unsteady flow are then described. There are many existing systems for flow visualization, and some of them are discussed. Streaklines depict time-varying phenomena that are sometimes difficult or impossible to see with other visualization techniques. The algorithms for computing streaklines are described. Several unsteady flow data sets have been visualized using streaklines, and the results are presented. Finally, some current issues in unsteady flow visualization are discussed.

Lane, David A.↗
NASA NTRS2014

Analyzing a 35-Year Hourly Data Record: Why So Difficult?

At the Goddard Distributed Active Archive Center, we have recently added a 35-Year record of output data from the North American Land Assimilation System (NLDAS) to the Giovanni web-based analysis and visualization tool. Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) offers a variety of data summarization and visualization to users that operate at the data center, obviating the need for users to download and read the data themselves for exploratory data analysis. However, the NLDAS data has proven surprisingly resistant to application of the summarization algorithms. Algorithms that were perfectly happy analyzing 15 years of daily satellite data encountered limitations both at the algorithm and system level for 35 years of hourly data. Failures arose, sometimes unexpectedly, from command line overflows, memory overflows, internal buffer overflows, and time-outs, among others. These serve as an early warning sign for the problems likely to be encountered by the general user community as they try to scale up to Big Data analytics. Indeed, it is likely that more users will seek to perform remote web-based analysis precisely to avoid the issues, or the need to reprogram around them. We will discuss approaches to mitigating the limitations and the implications for data systems serving the user communities that try to scale up their current techniques to analyze Big Data.

computational performance↗
NASA NTRS2012

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗
NASA NTRS1994

A Space and Atmospheric Visualization Science System

SAVS (a Space and Atmospheric Visualization Science system) is an integrated system with user-friendly functionality that employs a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, analysis, and visualization. All of this is accomplished without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. This report describes SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the earth's thermospheric, ionospheric, and mesospheric domains (TIMED). The final chapters provide a user-oriented description of interface functionalities, hands-on operations, and customized modules, with details of the primary modules presented in the appendices. The overall intent of the report is to reflect the accomplishments of the three-year development effort and to introduce potential users to the power and utility of the integrated data acquisition, analysis, and visualization system.

Szuszczewicz, E. P.↗
NASA NTRS2006

Using Dissimilarity Metrics to Identify Interesting Designs

A computer program helps to blend the power of automated-search software, which is able to generate large numbers of design solutions, with the insight of expert designers, who are able to identify preferred designs but do not have time to examine all the solutions. From among the many automated solutions to a given design problem, the program selects a smaller number of solutions that are worthy of scrutiny by the experts in the sense that they are sufficiently dissimilar from each other. The program makes the selection in an interactive process that involves a sequence of data-mining steps interspersed with visual displays of results of these steps to the experts. At crucial points between steps, the experts provide directives to guide the process. The program uses heuristic search techniques to identify nearly optimal design solutions and uses dissimilarity metrics defined by the experts to characterize the degree to which solutions are interestingly different. The search, data-mining, and visualization features of the program were derived from previously developed risk-management software used to support a risk-centric design methodology

Feather, Martin↗
NASA NTRS2009

SDBI 1904: Human Factors Assessment of Vibration Effects on Visual Performance during Launch

The primary objective of the of Human Factors Short Duration Bioastronautics Investigation (SDBI) 1904 is to determine visual performance limits during operational vibration and g-loads, specifically through the determination of minimal usable font sizes using Orion-type display formats. Currently there is little to no data available to quantify human visual performance under these extreme conditions. Existing data on shuttle vibration magnitude and frequency is incomplete, does not address seat and crew vibration in the current configuration, and does not address human visual performance. There have been anecdotal reports of performance decrements from shuttle crews, but no structured data has been collected. The SDBI is a companion effort to the Detailed Test Objective (DTO) 695, which will measure shuttle seat accelerations (vibration) during ascent. Data from the SDBI will serve an important role in interpreting the DTO vibration data. This data will be collected during the ascent phase of three shuttle missions (STS-119, 127, and 128). Both SDBI1904 and DTO 695 are low impact with respect to flight resources, and combined they represent an efficient and focused problem solving approach. The SDBI and DTO data will be correlated to determine the nature of perceived visual performance under varying vibrations and g-loads. This project will provide: * Immediate data for developing preliminary human performance vibration requirements * Flight validated inputs for ongoing and future ground-based research * Information of functional needs that will drive Orion display format design decisions

Shelby G Thompson↗
NASA NTRSDate not supplied

Fluid for Thought: SLS Rocket Aerodynamics featuring Pressure Sensitive Paint

Combining computer vision algorithms, state-of-the-art high-speed cameras, pressure sensitive paint (PSP) and transonic wind tunnel facilities, teams at NASA and Boeing study unsteady pressure over the Space Launch System (SLS) rocket model with unprecedented temporal and spatial data resolution. Post-processing visualizes pressure fluctuations over a 3D model by converting intensity data from videos of the wind tunnel test. Additionally, data analysis creates predictions of buffet forcing and aeroacoustic activity over the rocket body with the accuracy of a CFD model! The development of the technique will revolutionize aerodynamics research and reveal uncharted insights into fluid behavior and vehicle performance, enhancing aerospace technology and design as they advance. The talk will focus on the impact of the PSP technique on the SLS design and other potential aerospace applications, as well as lay out the experimental process, from wind tunnel test to insights from the data analysis.

Lucy Zhonghui Tang↗
NASA NTRS1999

Visualization Co-Processing of a CFD Simulation

OVERFLOW, a widely used CFD simulation code, is combined with a visualization system, pV3, to experiment with an environment for simulation/visualization co-processing on a SGI Origin 2000 computer(O2K) system. The shared memory version of the solver is used with the O2K 'pfa' preprocessor invoked to automatically discover parallelism in the source code. No other explicit parallelism is enabled. In order to study the scaling and performance of the visualization co-processing system, sample runs are made with different processor groups in the range of 1 to 254 processors. The data exchange between the visualization system and the simulation system is rapid enough for user interactivity when the problem size is small. This shared memory version of OVERFLOW, with minimal parallelization, does not scale well to an increasing number of available processors. The visualization task takes about 18 to 30% of the total processing time and does not appear to be a major contributor to the poor scaling. Improper load balancing and inter-processor communication overhead are contributors to this poor performance. Work is in progress which is aimed at obtaining improved parallel performance of the solver and removing the limitations of serial data transfer to pV3 by examining various parallelization/communication strategies, including the use of the explicit message passing.

Vaziri, Arsi↗
NASA NTRS2016

Geocam Space: Enhancing Handheld Digital Camera Imagery from the International Space Station for Research and Applications

Handheld astronaut photography of the Earth has been collected from the International Space Station (ISS) since 2000, making it the most temporally extensive remotely sensed dataset from this unique Low Earth orbital platform. Exclusive use of digital handheld cameras to perform Earth observations from the ISS began in 2004. Nadir viewing imagery is constrained by the inclined equatorial orbit of the ISS to between 51.6 degrees North and South latitude, however numerous oblique images of land surfaces above these latitudes are included in the dataset. While unmodified commercial off-the-shelf digital cameras provide only visible wavelength, three-band spectral information of limited quality current cameras used with long (400+ mm) lenses can obtain high quality spatial information approaching 2 meters/ground pixel resolution. The dataset is freely available online at the Gateway to Astronaut Photography of Earth site (http://eol.jsc.nasa.gov), and now comprises over 2 million images. Despite this extensive image catalog, use of the data for scientific research, disaster response, commercial applications and visualizations is minimal in comparison to other data collected from free-flying satellite platforms such as Landsat, Worldview, etc. This is due primarily to the lack of fully-georeferenced data products - while current digital cameras typically have integrated GPS, this does not function in the Low Earth Orbit environment. The Earth Science and Remote Sensing (ESRS) Unit at NASA Johnson Space Center provides training in Earth Science topics to ISS crews, performs daily operations and Earth observation target delivery to crews through the Crew Earth Observations (CEO) Facility on board ISS, and also catalogs digital handheld imagery acquired from orbit by manually adding descriptive metadata and determining an image geographic centerpoint using visual feature matching with other georeferenced data, e.g. Landsat, Google Earth, etc. The lack of full geolocation information native to the data makes it difficult to integrate astronaut photographs with other georeferenced data to facilitate quantitative analysis such as urban land cover/land use classification, change detection, or geologic mapping. The manual determination of image centerpoints is both time and labor-intensive, leading to delays in releasing geolocated and cataloged data to the public, such as the timely use of data for disaster response. The GeoCam Space project was funded by the ISS Program in 2015 to develop an on-orbit hardware and ground-based software system for increasing the efficiency of geolocating astronaut photographs from the ISS (Fig. 1). The Intelligent Robotics Group at NASA Ames Research Center leads the development of both the ground and on-orbit systems in collaboration with the ESRS Unit. The hardware component consists of modified smartphone elements including cameras, central processing unit, wireless Ethernet, and an inertial measurement unit (gyroscopes/accelerometers/magnetometers) reconfigured into a compact unit that attaches to the base of the current Nikon D4 camera - and its replacement, the Nikon D5 - and connects using the standard Nikon peripheral connector or USB port. This provides secondary, side and downward facing cameras perpendicular to the primary camera pointing direction. The secondary cameras observe calibration targets with known internal X, Y, and Z position affixed to the interior of the ISS to determine the camera pose corresponding to each image frame. This information is recorded by the GeoCam Space unit and indexed for correlation to the camera time recorded for each image frame. Data - image, EXIF header, and camera pose information - is transmitted to the ground software system (GeoRef) using the established Ku-band USOS downlink system. Following integration on the ground, the camera pose information provides an initial geolocation estimate for the individual film frame. This new capability represents a significant advance in geolocation from the manual feature-matching approach for both nadir and off-nadir viewing imagery. With the initial geolocation estimate, full georeferencing of an image is completed using the rapid tie-pointing interface in GeoRef, and the resulting data is added to the Gateway to Astronaut Photography of Earth online database in both Geotiff and Keyhole Markup Language (kml) formats. The integration of the GeoRef software component of Geocam Space into the CEO image cataloging workflow is complete, and disaster response imagery acquired by the ISS crew is now fully georeferenced as a standard data product. The on-orbit hardware component (GeoSens) is in final prototyping phase, and is on-schedule for launch to the ISS in late 2016. Installation and routine use of the Geocam Space system for handheld digital camera photography from the ISS is expected to significantly improve the usefulness of this unique dataset for a variety of public- and private-sector applications.

Stefanov, William L.↗
NASA NTRS2012

Graphics Processing Unit Assisted Thermographic Compositing

Objective Develop a software application utilizing high performance computing techniques, including general purpose graphics processing units (GPGPUs), for the analysis and visualization of large thermographic data sets. Over the past several years, an increasing effort among scientists and engineers to utilize graphics processing units (GPUs) in a more general purpose fashion is allowing for previously unobtainable levels of computation by individual workstations. As data sets grow, the methods to work them grow at an equal, and often greater, pace. Certain common computations can take advantage of the massively parallel and optimized hardware constructs of the GPU which yield significant increases in performance. These common computations have high degrees of data parallelism, that is, they are the same computation applied to a large set of data where the result does not depend on other data elements. Image processing is one area were GPUs are being used to greatly increase the performance of certain analysis and visualization techniques.

Ragasa, Scott↗
NASA NTRS2015

[Determine and Implement Updates to Be Made to MODEAR (Mission Operations Data Enterprise Architecture Repository)]

My main project was to determine and implement updates to be made to MODEAR (Mission Operations Data Enterprise Architecture Repository) process definitions to be used for CST-100 (Crew Space Transportation-100) related missions. Emphasis was placed on the scheduling aspect of the processes. In addition, I was to complete other tasks as given. Some of the additional tasks were: to create pass-through command look-up tables for the flight controllers, finish one of the MDT (Mission Operations Directorate Display Tool) displays, gather data on what is included in the CST-100 public data, develop a VBA (Visual Basic for Applications) script to create a csv (Comma-Separated Values) file with specific information from spreadsheets containing command data, create a command script for the November MCC-ASIL (Mission Control Center-Avionics System Integration Laboratory) testing, and take notes for one of the TCVB (Terminal Configured Vehicle B-737) meetings. In order to make progress in my main project I scheduled meetings with the appropriate subject matter experts, prepared material for the meetings, and assisted in the discussions in order to understand the process or processes at hand. After such discussions I made updates to various MODEAR processes and process graphics. These meetings have resulted in significant updates to the processes that were discussed. In addition, the discussions have helped the departments responsible for these processes better understand the work ahead and provided material to help document how their products are created. I completed my other tasks utilizing resources available to me and, when necessary, consulting with the subject matter experts. Outputs resulting from my other tasks were: two completed and one partially completed pass through command look-up tables for the fight controllers, significant updates to one of the MDT displays, a spreadsheet containing data on what is included in the CST-100 public data, a tool to create a csv file with specific information from spreadsheets containing command data, a command script for the November MCC-ASIL testing which resulted in a successful test day identifying several potential issues, and notes from one of the TCVB meetings that was used to keep the teams up to date on what was discussed and decided. I have learned a great deal working at NASA these last four months. I was able to meet and work with amazing individuals, further develop my technical knowledge, expand my knowledge base regarding human spaceflight, and contribute to the CST-100 missions. My work at NASA has strengthened my desire to continue my education in order to make further contributions to the field, and has given me the opportunity to see the advantages of a career at NASA.

Fanourakis, Sofia↗
NASA NTRS2017

Guided Tour of Pythonian Museum

At http:hdfeos.orgzoo, we have a large collection of Python examples of dealing with NASA HDF (Hierarchical Data Format) products. During this hands-on Python tutorial session, we'll present a few common hacks to access and visualize local NASA HDF data. We'll also cover how to access remote data served by OPeNDAP (Open-source Project for a Network Data Access Protocol). As a glue language, we will demonstrate how you can use Python for your data workflow - from searching data to analyzing data with machine learning.

hdf↗
NASA NTRS2024

Experimental Results for Mars Rotorcraft Airfoils (roamx-0201 and clf5605) at Low Reynolds Number and Compressible Flow in a Mars Wind Tunnel

Experimental results are obtained for a roamx-0201 type airfoil and the clf5605 airfoil at highsubsonic, low Reynolds number conditions using the Tohoku University Mars Wind Tunnel, Japan. The tests are conducted at a Mach number of M = 0.60, and a Reynolds number of Re = 20,000 to reflect representative aerodynamics of a rotor blade for Mars exploration. The angle of attack is varied between α = −2.0 deg and α = 6.0 deg. The roamx-0201 type airfoil is an unconventional airfoil optimized for the chosen tunnel operating conditions using the Evolutionary aLgorithm for Iterative Studies of Aeromechanics (ELISA), developed under the Rotor Optimization for the Advancement of Mars eXploration (ROAMX) project. ELISA is utilized here to optimize aerodynamic airfoil performance using a Genetic Algorithm and two-dimensional high-fidelity CFD simulations, ultimately resulting in a Pareto-optimal airfoil set. The clf5605 airfoil is the outboard airfoil used on the Ingenuity Mars Helicopter and provides a baseline against which the roamx-0201, as well as possible future airfoil profiles for the compressible low Reynolds number regime, can be compared against. Lift and drag data are recorded using a balance, pressure distributions are obtained using Pressure Sensitive Paint (PSP) application, and Schlieren images are obtained to visualize the flowfield. The data is tabulated to aid future research.

Roamx↗
NASA NTRS1979

Plotting max/min data envelopes

Study of maximum and minimum load distributions along structural section is aided by visual display of load distribution data. Maximum/minimum envelope plot program plots these envelopes of the stresses and shear loads at selected points in beam modeled by series of finite elements. Digital output for engineers and management is presented for quick analysis and understanding.

Furuike, T.↗
NASA NTRS2003

Modeling and Visualizing Uncertainty in Continuous Variables Predicted using Remotely Sensed Data

The use of remotely sensed images to map continuous biophysical variables, such as those related to terrestrial vegetation amount, sea surface temperature, and many other targets of NASA s Earth Observing System (EOS), includes variable, parametric, positional, spatial support and structural sources of uncertainty. A complete description of uncertainty will lead to a probability distribution at each location, allowing the exploration of the spatial dimension of uncertainty, that is, where the field is not well quantified. To achieve this purpose, convenient visualization tools are required. We have produced such a tool, called PDFVis, that facilitates the display of probability density functions (pdfs) on a per-grid-cell basis. The density estimate from Monte-Carlo generated realizations is interactively displayed as well as parametric and non-parametric summaries of the pdf field (such as mean, median, quartiles, standard deviation, number of modes, and locations of modes). Shaded surface renderings of pdfs along a transect can also be projected onto a plane. This tool will become more useful as richer descriptions of spatial uncertainty become available.

Dungan, Jennifer L.↗
NASA NTRS2007

Candidate Landing Site for the Mars Science Laboratory: Vernal Crater, S.W. ARabia Terra

In the fall of 2009, the Mars Science Laboratory (MSL) will be launched to Mars. The purpose of this mission is to assess biologic potential and geology and to investigate planetary processes of relevance to past habitability. MSL will be able to provide visual, chemical, radiation, and environmental data with its suite of instruments [1]. In order to be selected for the MSL landing site, certain engineering requirements must be met [1] and the area should contain geologic features suggestive of past habitability, so that the overriding science goal of the mission will be attained. There are a total of 33 proposed landing sites as of the first MSL Landing Site Workshop held in Pasadena, CA from May 31st to June 2nd, 2006 [1]. There will be an opportunity to gather high resolution visual and hyperspectral data on all proposed landing sites from the now-orbiting Mars Reconnaissance Orbiter (MRO) which entered martian orbit and began its main science phase in November of 2006 [2]. The data being gathered are from: the high resolution imaging science experiment (HiRISE), the context (CTX) camera and the compact reconnaissance imaging spectrometer (CRISM) onboard the spacecraft. The footprints of these instruments are centered on a single point, and each proposer must submit these coordinates, along with the coordinates of the proposed landing ellipse. Data from these instruments, along with new MOC images and THEMIS mosaics, will be used to enhance our understanding of the geologic and engineering parameters of each site.

Paris, K. N.↗
NASA NTRS1968

The Use of Large Lithium-Drifted, Germanium Diodes for Gamma-Ray Spectral Measurements at Balloon Altitudes

A series of balloon-borne experiments has been initiated at the Oak Ridge National Laboratory (ORNL) in cooperation with the Space Sciences Laboratory of the NASA G. C. Marshall Space Flight Center to determine the feasibility of using large (greater than 20 cc) lithium-drifted, germanium diodes to investigate the spectrum of atmospheric gamma rays (60 keV < E < 1.5 MeV) at altitudes corresponding to a few grams per cm (sup 2) residual atmosphere. The results of these measurements will also provide a basis for designing an appropriate shield for a multi-diode, highly directional gamma-ray spectrometer for use in astrophysical measurements. Two flights were accomplished during 1967 using the same two diodes and basic instrument package. Both flights were launched at the NCAR Scientific Balloon Flight Base, Palestine, Texas, and attained a float altitude of 117, 000 ft. The measured atmospheric gamma-ray spectrum shows at least one distinct line at 511 keV (annihilation radiation) superimposed on a continuous distribution of gamma rays attributable to both energy-degraded gamma rays and brems-strahlung photons. A second diode, encased in a passive shield of plastic and lead, shows the expected lines resulting from both neutron inelastic scattering and capture in the germanium. Data acquisition was accomplished on an event-by-event basis through the use of 512-channel, on-board ADC and word-generator circuits and a ground-based, on-line telemetry decoder. The decoder makes it possible to store the data in the memory of a modified pulse-height analyzer simultaneously with storage on magnetic tape. This provides a real-time visual observation of the data as it is accumulated and greatly facilitates preflight calibrations.

Chapman, G. T.↗
NASA NTRS2017

GES DISC Datalist Improves Earth Science Data Discoverability

At American Geophysical Union(AGU) 2016 Fall Meeting, Goddard Earth Sciences Data Information Services Center (GES DISC) unveiled a novel way to access data: Datalist. Currently, datalist is a collection of predefined data variables from one or more archived datasets, curated by our subject matter expert (SME). Our science support team has curated a predefined Hurricane Datalist and received very positive feedback from the user community. Datalist uses the same architecture our new website uses and have the same look and feel as other datasets on our web site. and also provides a one-stop shopping for data, metadata, citation, documentation, visualization and other available services. Since the last AGU Meeting, we have further developed a few new datalists corresponding to the Big Earth Data Initiative (BEDI) Societal Benefit Areas and A-Train data. We now have four datalists: Hurricane, Wind Energy, Greenhouse Gas and A-Train. We have also started working with our User Working Group members to create their favorite datalists and working with other DAAC to explore the possibility to include their products in our datalists that may also lead to a future of potential federated (cross-DAAC) datalists. Since our datalist prototype effort was a success, we are planning to make datalist operational. It's extremely important to have a common metadata model to support datalist, this will also be the foundation of federated datalist. We mapped our datalist metadata model to the unpublished UMM(Universal Metadata Model)-Var (Variable) (June version) and found that the UMM-var together with UMM-C (Collection) and possible UMM-S (Service) will meet our basic requirements. For example: Dataset shortname, and version are already specified in UMM-C, variable name, long name, units, dimensions are all specified in UMM-Var. UMM-Var also facilitates Science Keywords to allow tagging at variable level and Characteristics for optional variable characteristics. Measurements is useful for grouping of the variables and Set is promising to define datalist. And finally, the UMM-Service model to specify the available services for the variable will be very beneficial. In summary, UMM-Var, UMM-C and UMM-S are the basis of federated datalist and the development and deployment of datalist will contribute to the evolution of the UMM.

datalist↗