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NASA NTRS1996

Wind Tunnel Measured Effects on a Twin-Engine Short-Haul Transport Caused by Simulated Ice Accretions

A series of wind tunnel tests were conducted to assess the effects of leading edge ice contamination upon the performance of a short-haul transport. The wind tunnel test was conducted in the NASA Langley 14 by 22 foot facility. The test article was a 1/8 scale twin-engine short-haul jet transport model. Two separate leading edge ice contamination configurations were tested in addition to the uncontaminated baseline configuration. Several aircraft configurations were examined including various flap and slat deflections, with and without landing gear. Data gathered included force measurements via an internal six-component force balance, pressure measurements through 700 electronically scanned wing pressure ports, and wing surface flow visualization measurements. The artificial ice contamination caused significant performance degradation and caused visible changes demonstrated by the flow visualization. The data presented here is just a portion of the data gathered. A more complete data report is planned for publication as a NASA Technical Memorandum and data supplement.

Reehorst, Andrew↗

NASA NTRS1987

An experimental study of the aerodynamic characteristics of planar and non-planar outboard wing planforms

A series of wind tunnel experiments have been conducted to investigate the aerodynamic characteristics of several planar and nonplanar wingtip planforms. Seven different configurations: base-line rectangular, elliptical, swept and tapered, swept and tapered with dihedral, swept and tapered with anhedral, rising arc, and drooping arc, were investigated for two different spans. The data are available in terms of coefficient plots of force data, flow visualization photographs, and velocity and pressure flowfield surveys. All planforms, particularly the nonplanar, have some advantages over the baseline rectangular planform. Span efficiencies up to 20-percent greater than baseline are a possibility. However, it is suggested that the span efficiency concept might need refinement for nonplanar wings. Flow survey data show the change in effective span with vortex roll-up. The flow visualization shows the occurrence of mushroom-cell-separation flow patterns at angles of attack corresponding to stall. These grow with an increase in post-stall angle of attack. For the larger aspect ratios, the cells are observed to split into sub-cells at the higher angles of attack. For all angles of attack, some amount of secondary vortex flow is observed for the planar and nonplanar out-board planforms with sweep and taper.

Naik, D. A.↗

NASA NTRS2012

Giovanni: The Bridge between Data and Science

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a web-based remote sensing and model data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional data sets, covering atmospheric dynamics, atmospheric chemistry, hydrology, oceanographic, and land surface. Data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. Visualization options enable comparisons of multiple variables and easier refinement. Recently, new features have been developed, such as interactive scatter plots and maps. The performance is also being improved, in some cases by an order of magnitude for certain analysis functions with optimized software. We are working toward merging current Giovanni portals into a single omnibus portal with all variables in one (virtual) location to help users find a variable easily and enhance the intercomparison capability

Shen, Suhung↗

NASA NTRS2004

Real Data and Rapid Results: Ocean Color Data Analysis with Giovanni (GES DISC Interactive Online Visualization and ANalysis Infrastructure)

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step addressing the challenge of using archived Earth Observing System (EOS) data for regional or global studies by developing an infrastructure with a World Wide Web interface which allows online, interactive, data analysis: the GES DISC Interactive Online Visualization and ANalysis Infrastructure, or "Giovanni." Giovanni provides a data analysis environment that is largely independent of underlying data file format. The Ocean Color Time-Series Project has created an initial implementation of Giovanni using monthly Standard Mapped Image (SMI) data products from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission. Giovanni users select geophysical parameters, and the geographical region and time period of interest. The system rapidly generates a graphical or ASCII numerical data output. Currently available output options are: Area plot (averaged or accumulated over any available data period for any rectangular area); Time plot (time series averaged over any rectangular area); Hovmeller plots (image view of any longitude-time and latitude-time cross sections); ASCII output for all plot types; and area plot animations. Future plans include correlation plots, output formats compatible with Geographical Information Systems (GIs), and higher temporal resolution data. The Ocean Color Time-Series Project will produce sensor-independent ocean color data beginning with the Coastal Zone Color Scanner (CZCS) mission and extending through SeaWiFS and Moderate Resolution Imaging Spectroradiometer (MODIS) data sets, and will enable incorporation of Visible/lnfrared Imaging Radiometer Suite (VIIRS) data, which will be added to Giovanni. The first phase of Giovanni will also include tutorials demonstrating the use of Giovanni and collaborative assistance in the development of research projects using the SeaWiFS and Ocean Color Time-Series Project data in the online Laboratory for Ocean Color Users (LOCUS). The synergy of Giovanni with high-quality ocean color data provides users with the ability to investigate a variety of important oceanic phenomena, such as coastal primary productivity related to pelagic fisheries, seasonal patterns and interannual variability, interdependence of atmospheric dust aerosols and harmful algal blooms, and the potential effects of climate change on oceanic productivity.

Acker, J. G.↗

NASA NTRS1998

Demonstrations at Supercomputing 1998

Contents of the papers include: Visualization techniques- The next generation, Small-machine visualizing very big data sets, Public display of Lunar Prospector data, Steering molecules via Feel, High-dimensional data browser, Multi-source visualization, Interactive surface flow visualization, and the Virtual Windtunnel.

Bryson, Steve↗

NASA NTRS2015

Message Brokering Evaluation for Live Spacecraft Telemetry Monitoring, Recorded Playback, and Analysis

Live monitoring and post-flight analysis of telemetry data play a vital role in the development, diagnosis, and deployment of components of a space flight mission. Requirements for such a system include low end-to-end latency between data producers and visualizers, preserved ordering of messages, data stream archiving with random access playback, and real-time creation of derived data streams. We evaluate the RabbitMQ and Kafka message brokering systems, on how well they can enable a real-time, scalable, and robust telemetry framework that delivers telemetry data to multiple clients across heterogeneous platforms and flight projects. In our experiments using an actively developed robotic arm testbed, Kafka yielded a much higher message throughput rate and a consistent publishing rate across the number of topics and consumers. Consumer message rates were consistent across the number of topics but can exhibit bursty behavior with an increase in the contention for a single topic partition with increasing number of consumers.

Lee, Daren↗

NASA NTRS2018

Studying Diurnal Variations of Aerosols with NASA MERRA-2 Reanalysis Data

Aerosols play an important role in atmospheric dynamics, climate variations, and Earth's energy cycle by altering the radiation balance in the atmosphere through interaction with clouds, providing fertilizer for forests and canopy, and as a supply of iron to the ocean over long time periods. Studies suggest that much of the feedback between dust aerosols and dynamics is associated with diurnal and synoptic scale variability. However, the lack of sub-daily resolution of aerosols from satellite observations makes it difficult to study the diurnal characteristics, especially over tropical and subtropical regions. Investigation of this topic utilizes over 37 years of simulated global aerosol products from NASA atmospheric reanalysis, in the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data set, available from NASA Goddard Earth Science Data and Information Services Center (GES DISC). MERRA-2 covers the period 1980-present, and is continuing as an ongoing climate analysis. Aerosol assimilation is included throughout the period, using data from MODIS, MISR, AERONET, and AVHRR (in the pre-EOS period). The aerosols are assimilated using the MERRA-2 aerosol model, which interacts directly with radiation parameterization, and is radiatively coupled with atmospheric model dynamics in the Goddard Earth Observing System Model, Version 5 (GEOS-5). Hourly, monthly, and monthly diurnal data are available at spatial resolution of 0.5o x 0.625o (latitude x longitude). By using MERRA-2 hourly and monthly diurnal products, different aerosol diurnal variabilities are observed over North America, Africa, Asia, and Australia, that may be due to different meteorological conditions and aerosol sources. The presentation will also provide an overview of MERRA-2 data services at GES DISC, such as how to find and download data, and how to quickly visualize and analyze data online with Giovanni.

aerosol↗

NASA NTRS1983

Identification and estimation of the area planted with irrigated rice based on the visual interpretation of LANDSAT MSS data

The objective was to test the feasibility of the application of MSS-LANDSAT data to irrigated rice crop identification and area evaluation, within four rice growing regions of the Rio Grande do Sul state, in order to extend the methodology for the whole state. The applied methodology was visual interpretation of the following LANDSAT products: channels 5 and 7 black and white imageries and color infrared composite imageries all at the scale of 1:250.000. For crop identification and evaluation, the multispectral criterion and the seasonal variation were utilized. Based on the results it was possible to conclude that: (1) the satellite data were efficient for crop area identification and evaluation; (2) the utilization of the multispectral criterion, allied to the seasonal variation of the rice crop areas from the other crops and, (3) the large cloud cover percentage found in the satellite data made it impossible to realize a rice crop spectral monitoring and, therefore, to define the best dates for such data acquisition for rice crop assessment.

Parada, N. D. J.↗

NASA NTRS1985

Workshop on Dust on Mars

A workshop was organized to stimulate and coordinate research on the properties of Martian dust, its distribution on the planet, and the processes affecting its yearly deposition, erosion, and transport. A great deal of research was carried out to understand local, regional, and global aspects of the Martian dust transport cycle, with the goal being definition of the currently active processes and their relation to those operating over the long term. To date, however, most individual research projects have centered around interpretation of single data sets (visual images, IRTM, radar, etc.), and these many efforts were not coordinated. Many of the details of short and long term dust-related processes, as inferred from the various single data sets, are still not agreed upon. It was the intent of this workshop to encourage the informal exchange of ideas among several researchers currently investigating various aspects of the problem and to investigate cooperative efforts to synthesize the individual approaches into a unified understanding of the present seasonal and yearly Martian sediment transport cycles.

Lee, S.↗

NASA NTRS2013

Datacasting V3.0

Datacasting V3.0 provides an RSSbased feed mechanism for publishing the availability of Earth science data records in real time. It also provides a utility for subscribing to these feeds and sifting through all the items in an automatic manner to identify and download the data records that are required for a specific application. Datacasting is a method by which multiple data providers can publish the availability of new Earth science data and users download those files that meet a predefined need; for example, to only download data files related to a specific earthquake or region on the globe. Datacasting is a server-client architecture. The server-side software is used by data providers to create and publish the metadata about recently available data according to the Datacasting RSS (Really Simple Syndication) specification. The client software subscribes to the Datacasting RSS and other RSS-based feeds. By configuring filters associated with feeds, data consumers can use the client to identify and automatically download files that meet a specific need. On the client side, a Datacasting feed reader monitors the server for new feeds. The feed reader will be tuned by the user, via a graphical user interface (GUI), to examine the content of the feeds and initiate a data pull after some criteria are satisfied. The criteria might be, for example, to download sea surface temperature data for a particular region that has cloud cover less than 50% and during daylight hours. After the granule is downloaded to the client, the user will have the ability to visualize the data in the GUI. Based on the popular concept of podcasting, which gives listeners the capability to download only those MP3 files that match their preference, Earth science Datacasting will give users a method to download only the Earth science data files that are required for a particular application.

Bingham, Andrew W.↗

NASA NTRS2014

Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-user Resources, Answers to Faqs, and Common Mistakes to Avoid

Satellite data of atmospheric pollutants are becoming more widely used in the decision-making and environmental management activities of public, private sector and non-profit organizations. They are employed for estimating emissions, tracking pollutant plumes, supporting air quality forecasting activities, providing evidence for "exceptional event" declarations, monitoring regional long-term trends, and evaluating air quality model output. However, many air quality managers are not taking full advantage of the data for these applications nor has the full potential of satellite data for air quality applications been realized. A key barrier is the inherent difficulties associated with accessing, processing, and properly interpreting observational data. A degree of technical skill is required on the part of the data end-user, which is often problematic for air quality agencies with limited resources. Therefore, we 1) review the primary uses of satellite data for air quality applications, 2) provide some background information on satellite capabilities for measuring pollutants, 3) discuss the many resources available to the end-user for accessing, processing, and visualizing the data, and 4) provide answers to common questions in plain language.

remote sensing↗

NASA NTRS2014

Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-User Resources, Answers to FAQs, and Common Mistakes to Avoid

Duncan, Bryan↗

NASA NTRSDate not supplied

Exploring Innovative Methods for Earth Science Communication Through NASA’s Earth Information Center

Environmental challenges stemming from unprecedented changes in our planet have increased the need to communicate our understanding of Earth as a connected system. In June 2023, NASA unveiled the Earth Information Center (EIC), part of NASA’s Earth Action Strategy aimed at amplifying NASA’s Earth science impact by engaging decision-makers beyond the scientific community. Existing in both physical and virtual space, the EIC provides critical information on how the planet is changing and affecting livelihoods across the globe. For over fifty years, NASA has utilized the unique vantage point space offers to monitor Earth in collaboration with Federal partners. Through an expanding fleet of Earth observing satellites and sensors, NASA informs local to global decision making within nine thematic areas: agriculture, biodiversity, disasters, greenhouse gases, health and air quality, sea level rise and coastal impacts, sustainable energy, water resources, and wildfires. Visitors to the inaugural location of the EIC at NASA Headquarters in Washington D.C., can interact with Earth observation data and models through innovative exhibits and storytelling. Designed by an interdisciplinary team, the EIC is designed for multiple modality learning to reach a wide base of end-users. Data driven visualizations, near real-time information, and curated stories highlight the applications of Earth observations to address environmental challenges. Complementary exhibits and immersive storytelling allow visitors to physically step inside environmental data and connect with information on an emotional level. Taken together, the collective EIC provides scientists and non-scientists alike with the ability to see our home planet as NASA sees it, as a system of systems, while delivering easily accessible information to those who need it most.

Earth Information Center↗

NASA NTRS2018

A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classification

A self-organizing map (SOM) is a type of competitive artificial neural network, which projects the high dimensional input space of the training samples into a low dimensional space with the topology relations preserved. This makes SOMs supportive of organizing and visualizing complex data sets and have been pervasively used among numerous disciplines with different applications. Notwithstanding its wide applications, the self-organizing map is perplexed by its inherent randomness, which produces dissimilar SOM patterns even when being trained on identical training samples with the same parameters every time, and thus causes usability concerns for other domain practitioners and precludes more potential users from exploring SOM based applications in a broader spectrum. Motivated by this practical concern, we propose a deterministic approach as a supplement to the standard self-organizing map. In accordance with the theoretical design, the experimental results with satellite cloud data demonstrate the effective and efficient organization as well as simplification capabilities of the proposed approach.

Initialization method↗

NASA NTRS2024

A Distributed Simulation Framework Applied to Artemis Analysis, Studies, Integration, and Test

The National Aeronautics and Space Administration (NASA) established the Artemis Program, a series of missions to return humans to the Moon and explore further than before. To execute the Artemis missions, NASA is collaborating with commercial and international partners to create the necessary infrastructure and logistics plan that will establish a long term presence on the Moon ahead of exploring Mars. NASA and its partners are developing a collection of space and surface systems to support crewed missions to the lunar surface that will provide the mobility, habitation, logistics, and exploration support necessary for Artemis mission successes which includes robust scientific investigations. This paper details the design, capabilities, and uses of the Artemis Distributed Simulation (ADS) being developed by the NASA Exploration Systems Simulations (NExSyS) Team to support Artemis architecture studies. ADS utilizes international interoperability standards to connect a collection of independent vehicle and service simulations; these include but are not limited to elements such as rovers, landers, and habitation elements along with services like communications, environment, visualization, and data logging. ADS’s distributed nature allows for the complex aggregation of constituent Artemis elements; this includes efficient scenario modification with the addition or removal of individual simulations representing Artemis elements or services. This capability provides support for the rapid performance of various Artemis mission trade studies exploring alternate configurations. Currently, ADS uses NASA developed simulations for development and testing; however, through the use of international simulation interoperability standards, ADS provides an integration framework to incorporate dissimilar authoritative vendor simulations as Artemis systems mature and vendor simulations become available. Vendor simulations will be able to join ADS and interact with other Artemis elements and vehicles while limiting the exposure of proprietary data. This paper describes the expansion of an existing distributed simulation infrastructure to accommodate a collaborative and dynamic framework for the Artemis Program. This work includes updated federation designs, integration into existing NASA facilities, advancements in visualizations, and advancements in human driven inputs. This paper will also outline recently completed and ongoing support and collaboration with NASA studies and testing, namely results from energetics and Human-In-The-Loop (HITL) studies. The paper concludes with a plan for future developments and facility integration to enable enhanced studies in preparation for a return of humans to the lunar surface.

Artemis↗

NASA NTRSDate not supplied

Effects of Simulated Microgravity and LINC-Complex on Chromosome 8 of Human Mammary Cells

Previously, human breast epithelial cells were studied under simulated microgravity to determine the role of the LINC-complex in maintaining nuclear morphology and gene expression. Data from that study was used in this project to understand how the LINC-complex influences gene expression at chromosome 8 under simulated microgravity. Differentially expressed genes found in clusters typically indicate a molecular relationship amongst them. Visual and data analyses (GO, pathways) identified 51 genes within clusters on chromosome 8 across various simulated microgravity conditions that did not share any molecular relationship. Additional results also determined that cells with a disrupted LINC-complex experienced more differential gene expression than the control, and that extended periods of simulated microgravity exacerbated differential gene expression in chromosome 8 of LINC-disrupted cells. These results suggest that the stressful simulated microgravity environment coupled with disrupted biological processes, such as in the case of the LINC-complex, can increase differential gene expression in chromosomes. Future studies where additional analyses are performed to further analyze gene expression of clusters under simulated microgravity could potentially elucidate the molecular relationship amongst affected genes.

Simulated microgravity↗

NASA NTRS1995

A versatile system for processing geostationary satellite data with run-time visualization capability

To better predict global climate change, scientists are developing climate models that require interdisciplinary and collaborative efforts in their building. We are currently involved in several such projects but will briefly discuss activities in support of two such complementary projects: the Atmospheric Radiation Measurement (ARM) program of the Department of Energy and Sequoia 2000, a joint venture of the University of California, the private sector, and government agencies. Our contribution to the ARM program is to investigate the role of clouds on the top of the atmosphere and on surface radiance fields through the data analysis of surface and satellite observations and complex modeling of the interaction of radiation with clouds. One of our first ARM research activities involves the computation of the broadband shortwave surface irradiance from satellite observations. Geostationary satellite images centered over the first ARM observation site are received hourly over the Internet network and processed in real time to compute hourly and daily composite shortwave irradiance fields. The images and the results are transferred via a high-speed network to the Sequoia 2000 storage facility in Berkeley, where they are archived These satellite-derived results are compared with the surface observations to evaluate the accuracy of the satellite estimate and the spatial representation of the surface observations. In developing the software involved in calculating the surface shortwave irradiance, we have produced an environment whereby we can easily modify and monitor the data processing as required. Through the principles of modular programming, we have developed software that is easily modified as new algorithms for computation are developed or input data availability changes. In addition, the software was designed so that it could be run from an interactive, icon-driven, graphical interface, TCL-TK, developed by Sequoia 2000 participants. In this way, the data flow can be interactively assessed and altered as needed. In this environment, the intermediate data processing 'images' can be viewed, enabling the investigator to easily monitor the various data processing steps as they progress. Additionally, this environment allows the rapid testing of new processing modules and allows their effects to be visually compared with previous results.

Landsfeld, M.↗

NASA NTRS2019

Using Science Operations Tools and Methods from NASA for Remote Presence Ocean Exploration on Earth: E/V Nautilus Cruise NA108

NASA Ames' Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade.In the last two years, we have participated in SUBSEA, a multi-institution collaborative project. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC). In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule.The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team's ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA's Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island's Graduate School of Oceanography (GSO). ISC is GSO's telepresence operations facility.

Lees, David S.↗