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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 73 records · Page 4

Study of boundary-layer transition using transonic cone Preston tube data

Laminar layer Preston tube data on a sharp nose, ten degree cone obtained in the Ames 11 ft TWT and in flight tests are analyzed. During analyses of the laminar-boundary layer data, errors were discovered in both the wind tunnel and the flight data. A correction procedure for errors in the flight data is recommended which forces the flight data to exhibit some of the orderly characteristics of the wind tunnel data. From corrected wind tunnel data, a correlation is developed between Preston tube pressures and the corresponding values of theoretical laminar skin friction. Because of the uncertainty in correcting the flight data, a correlation for the unmodified data is developed, and, in addition, three other correlations are developed based on different correction procedures. Each of these correlations are used in conjunction with the wind tunnel correlation to define effective freestream unit Reynolds numbers for the 11 ft TWT over a Mach number range of 0.30 to 0.95. The maximum effective Reynolds numbers are approximately 6.5% higher than the normal values. These maximum values occur between freestream Mach numbers of 0.60 and 0.80. Smaller values are found outside this Mach number range. These results indicate wind tunnel noise affects the average laminar skin friction much less than it affects boundary layer transition. Data on the onset, extent, and end of boundary layer transition are summarized. Application of a procedure for studying the relative effects of varying nose radius on a ten degree cone at supercritical speeds indicates that increasing nose radius promotes boundary layer transition and separation of laminar boundary layers.

Reed, T. D.↗

Discovering Communicable Scientific Knowledge from Spatio-Temporal Data

This paper describes how we used regression rules to improve upon a result previously published in the Earth science literature. In such a scientific application of machine learning, it is crucially important for the learned models to be understandable and communicable. We recount how we selected a learning algorithm to maximize communicability, and then describe two visualization techniques that we developed to aid in understanding the model by exploiting the spatial nature of the data. We also report how evaluating the learned models across time let us discover an error in the data.

Schwabacher, Mark↗

Maps Suggest Transport and Source Processes of PM2.5 at 1 km x 1 km for the Whole San Joaquin Valley, Winter 2011 (Generalizations from DISCOVER-AQ)

We present interpreted data analysis using MAIAC (Multiangle implementation of Atmospheric Correction) retrievals and appropriate RAPid Update Cycle (RAP) meteorology to map respirable aerosol (PM2.5) for the period January and February, 2011. The San Joaquin Valley is one of the unhealthiest regions in the USA for PM2.5 and related morbidity. The methodology evaluated can be used for the entire moderate-resolution imaging spectrometer (MODIS, VIIRS) data record. Other difficult areas of the West: Riverside, CA, Salt Lake City, UT, and Doa Ana County, NM share similar difficulties and solutions. The maps of boundary layer depth for 1116 hr local time from RAP allows us to interpret aerosol optical thickness as a concentration of particles in a nearly well-mixed box capped by clean air. That mixing is demonstrated by DISCOVER-AQ data and afternoon samples from the airborne measurements, P3B (on-board) and B200 (HSRL2 lidar). This data and the PM2.5 gathered at the deployment sites allowed us to estimate and then evaluate consistency and daily variation of the AOT to PM2.5 relationship. Mixed-effects modeling allowed a refinement of that relation from day to day; RAP mixed layers explained the success of previous mixed-effects modeling. Compositional, size-distribution, and MODIS angle-of-regard effects seem to describe the need for residual daily correction beyond ML depth.We report on an extension method to the entire San Joaquin Valley for all days with MODIS imagery using the permanent PM2.5 stations, evaluated for representativeness. Resulting map movies show distinct sources, particularly Interstate-5 (at approx. 1km x 1km resolution) and the broader Bakersfield area. Accompanying winds suggest transport effects and variable pathways of pollution cleanout. Such estimates should allow morbiditymortality studies. They should be also useful for actual model assimilations, where composition and sources are uncertain. We conclude with a description of new work to extend these insights to similar regions, e.g. interior valleys of California, the Po Valley, the Mediterranean litoral, and the Ganges Plain.This work show generalizable use of remote sensing, a major goal of DISCOVER-AQ, Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality.

Chatfield, R.↗

XML Based Scientific Data Management Facility

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of HTML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

Mehrotra, Piyush↗

XML Based Scientific Data Management Facility

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of XML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management ,facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

Mehrotra, P.↗

MAGSAT data processing: A report for investigators

The in-flight attitude and vector magnetometer data bias recovery techniques and results are described. The attitude bias recoveries are based on comparisons with a magnetic field model and are thought to be accurate to 20 arcsec. The vector magnetometer bias recoveries are based on comparisons with the scalar magnetometer data and are thought to be accurate to 3 nT or better. The MAGSAT position accuracy goals of 60 m radially and 300 m horizontally were achieved for all but the last 3 weeks of Magsat lifetime. This claim is supported by ephemeris overlap statistics and by comparisons with ephemerides computed with an independent orbit program using data from an independent tracking network. MAGSAT time determination accuracy is estimated at 1 ms. Several errors in prelaunch assumptions regarding data time tags, which escaped detection in prelaunch data tests, and were discovered and corrected postlaunch are described. Data formats and products, especially the Investigator-B tapes, which contain auxiliary parameters in addition to the basic magnetometer and ephemeris data, are described.

Langel, R. A.↗

ESIP Information Quality Cluster (IQC)

The Information Quality Cluster (IQC) within the Federation of Earth Science Information Partners (ESIP) was initially formed in 2011 and has evolved significantly over time. The current objectives of the IQC are to: 1. Actively evaluate community data quality best practices and standards; 2. Improve capture, description, discovery, and usability of information about data quality in Earth science data products; 3. Ensure producers of data products are aware of standards and best practices for conveying data quality, and data providers distributors intermediaries establish, improve and evolve mechanisms to assist users in discovering and understanding data quality information; and 4. Consistently provide guidance to data managers and stewards on how best to implement data quality standards and best practices to ensure and improve maturity of their data products. The activities of the IQC include: 1. Identification of additional needs for consistently capturing, describing, and conveying quality information through use case studies with broad and diverse applications; 2. Establishing and providing community-wide guidance on roles and responsibilities of key players and stakeholders including users and management; 3. Prototyping of conveying quality information to users in a more consistent, transparent, and digestible manner; 4. Establishing a baseline of standards and best practices for data quality; 5. Evaluating recommendations from NASA's DQWG in a broader context and proposing possible implementations; and 6. Engaging data providers, data managers, and data user communities as resources to improve our standards and best practices. Following the principles of openness of the ESIP Federation, IQC invites all individuals interested in improving capture, description, discovery, and usability of information about data quality in Earth science data products to participate in its activities.

data products↗

The X-Ray Variable Sky

A novel approach to search for rapid time variability of every source, whether persistent or transient, within the entire ROSAT detector field has been developed. Semi-automated software statistically tests the photon arrival time event list for source variability and reports significant (greater than 5 sigma) variable enhancement in the photon count rate on time scales ranging from 5-500 seconds. The computational algorithms have been thoroughly tested, and are able to discriminate between false detections induced by instrumental effects, and real X-ray variable sources (XRVs); when carefully scrutinized by the PI. The analysis has proven to be successful, with both periodic and transient XRVs having been found. Some of these are entirely new discoveries, while others have been detected in previous X-ray missions, yet their nature remained elusive since source identification and analysis had yet to be performed. On average, one new (unidentified) XRV is found per ROSAT PSPC field analyzed. In some cases the XRVs show only a transient signature (a burst type event) with no persistent X-ray or other known (optical) counterpart. The ambitious goal of this project was to process as much of the ROSAT PSPC archive data as feasibly possible to discover XRVs and analyze this data.

Stringfellow, Guy↗

Monitoring of the tidal dynamics of the Dutch Waddensea by SIR-B

The potential of LANDSAT data, covering the entire tidal flats at a certain, known, tidal situation, was assessed. It was discovered that the data cannot be used for systematic survey because of the long interval between subsequent passes, weather conditions often interfere with recording, and of the lack of correlation between passes and the tidal situation. The objective is to overcome the problems by using: (1) the synoptic view obtained by SIR-B, which has the potential of surveying large areas of the flats simultaneously; (2) the all-weather capability of the microwave system; (3) the recording during consecutive days, which results in a straightforeward correlation with the tidal cycle and the picturing of different tidal stages; and (4) the multiangle incidence of SIR-B to analyze the bottom configuration of submerged parts of the flats. The use of a weather independent monitoring device, such as radar, an improvement in the monitoring technique of tidal coastal areas.

Koopmans, B. N.↗

MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region

MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

MODIS↗

Faults Discovery By Using Mined Data

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Lee, Charles↗

Lifetimes and Occurrence Rates of Dark Vortices on Neptune from 25 Years of Hubble Space Telescope Images

We scoured the full set of blue-wavelength Hubble Space Telescope images of Neptune, finding one additional dark spot in new Hubble data beyond those discovered in 1989, 1994, 1996, and 2015. We report the complete disappearance of the SDS-2015 dark spot, using new Hubble data taken on 2018 September 9–10, as part of the Outer Planet Atmospheres Legacy (OPAL) program. Overall, dark spots in the full Hubble data set have lifetimes of at least one to two years, and no more than six years. We modeled a set of dark spots randomly distributed in time over the latitude range on Neptune that is visible from Earth, finding that the cadence of archival Hubble images would have detected about 70% of these spots if their lifetimes are only one year, or about 85%–95% of simulated spots with lifetimes of two or more years. Based on the Hubble data set, we conclude that dark spots have average occurrence rates of one dark spot every four to six years. Many numerical models to date have simulated much shorter vortex lifetimes, so our findings provide constraints that may lead to improved understanding of Neptune’s wind field, stratification, and humidity.

Hsu, Andrew I.↗

MAGSAT anomaly profiles of the eastern Indian Ocean

Ground tracks from SEASAT were used in an effort to develop qualititative relationships between the gravity field and MAGSAT magnetic anomalies in the eastern Indian Ocean. Investigation of data quality led to analyses of the average value (over 80 vector data points, or approximately 36 km intervals) and of the standard deviation of this average, as a mean of identifying noisy portions of the data. It was discovered that the plots of the average value minus the individual (measured) point value are most useful for identifying noisy areas and data spikes. Spectrum analysis using edited (spikes removed) data show that the noise floor is less than 1 nT and the slope of the spectrum in the region of wavelengths between 1200 km and 250 km is approximately -3. Consequently the estimated resolution limit improved from approximately 360 km to approximately 250 km.

Sailor, R. V.↗

Parametric-Studies and Data-Plotting Modules for the SOAP

"Parametric Studies" and "Data Table Plot View" are the names of software modules in the Satellite Orbit Analysis Program (SOAP). Parametric Studies enables parameterization of as many as three satellite or ground-station attributes across a range of values and computes the average, minimum, and maximum of a specified metric, the revisit time, or 21 other functions at each point in the parameter space. This computation produces a one-, two-, or three-dimensional table of data representing statistical results across the parameter space. Inasmuch as the output of a parametric study in three dimensions can be a very large data set, visualization is a paramount means of discovering trends in the data (see figure). Data Table Plot View enables visualization of the data table created by Parametric Studies or by another data source: this module quickly generates a display of the data in the form of a rotatable three-dimensional-appearing plot, making it unnecessary to load the SOAP output data into a separate plotting program. The rotatable three-dimensionalappearing plot makes it easy to determine which points in the parameter space are most desirable. Both modules provide intuitive user interfaces for ease of use.

Source record↗

OMI/TROPOMI Data Support from GES DISC

The NASA GES DISC has been the official archive center for data from the Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission since 2004. In recent years, the GES DISC has been evolving and improving its data management and services in order to promote its data to be easily discovered and accessed, as well as to facilitate data "interoperability". This presentation will summarize metrics collected of OMI data usage and GES DISC data services. In order to support the recently released Sentinel-5P/TROPOMI data from ESA at the NASA GES DISC, a new End User License Agreement (EULA) has been implemented for users accessing these data from the GES DISC.

Johnson, J.↗

Finding Your TEMPO: An Introduction to the Mission, Products, and Data Services for Air Quality Observations over North America

NASA's Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission is the first space-based instrument to monitor major air pollutants across the North American continent every daylight hour at high spatial resolution. TEMPO is an ultraviolet and visible spectrometer that sits on a commercial satellite in a geostationary orbit about 22,000 miles above Earth's equator. This vantage point enables TEMPO to monitor daily variations in ozone, nitrogen dioxide, and other key elements of air pollution from the Atlantic to the Pacific, and from Mexico City and the Yucatan Peninsula to the Canadian oil sands. This webinar will provide an overview of the TEMPO mission and its data products and will show you how to discover and access TEMPO data products using NASA's Earthdata Search. This includes finding documentation, performing searches and filtering, using subsetting/concatenation services in Earthdata Search, and utilizing the Earthdata Forum.

Caroline Nowlan↗