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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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NASA NTRS2016

Wind-US Users Guide Version 4.0

Wind-US is a computational platform which may be used to numerically solve various sets of equations governing physical phenomena. Currently, the code supports the solution of the Euler and Navier-Stokes equations of fluid mechanics, along with supporting equation sets governing turbulent and chemically reacting flows. Wind-US is a product of the NPARC Alliance, a partnership between the NASA Glenn Research Center (GRC) and the Arnold Engineering Development Complex (AEDC) dedicated to the establishment of a national, applications-oriented flow simulation capability. The Boeing Company has also been closely associated with the Alliance since its inception, and represents the interests of the NPARC User's Association. The "Wind-US User's Guide" describes the operation and use of Wind-US, including: a basic tutorial; the physical and numerical models that are used; the boundary conditions; monitoring convergence; the files that are read and/or written; parallel execution; and a complete list of input keywords and test options. For current information about Wind-US and the NPARC Alliance, please see the Wind-US home page at http://www.grc.nasa.gov/WWW/winddocs/ and the NPARC Alliance home page at http://www.grc.nasa.gov/WWW/wind/.

fluid dynamics↗
NASA NTRS2016

Wildfires Dynamics in Siberian Larch Forests

Wildfire number and burned area temporal dynamics within all of Siberia and along a south-north transect in central Siberia (45deg-73degN) were studied based on NOAA/AVHRR (National Oceanic and Atmospheric Administration/ Advanced Very High Resolution Radiometer) and Terra/MODIS (Moderate Resolution Imaging Spectroradiometer) data and field measurements for the period 1996-2015. In addition, fire return interval (FRI) along the south-north transect was analyzed. Both the number of forest fires and the size of the burned area increased during recent decades (p < 0.05). Significant correlations were found between forest fires, burned areas and air temperature (r = 0.5) and drought index (The Standardized Precipitation Evapotranspiration Index, SPEI) (r = 0.43). Within larch stands along the transect, wildfire frequency was strongly correlated with incoming solar radiation (r = 0.91). Fire danger period length decreased linearly from south to north along the transect. Fire return interval increased from 80 years at 62 N to 200 years at the Arctic Circle (6633' N), and to about 300 years near the northern limit of closed forest stands (about 71+ N). That increase was negatively correlated with incoming solar radiation (r = 0.95). Keywords: wildfires; drought index; larch stands; fire return interval; fire frequency; burned area; climate-induced trends in Siberian wildfires

wildfires↗
NASA NTRS2017

New GES DISC Services Shortening the Path in Science Data Discovery

The Current GES DISC available services only allow user to select variables from a single dataset at a time and too many variables from a dataset are displayed, choice is hard. At American Geophysical Union (AGU) 2016 Fall Meeting, Goddard Earth Sciences Data Information Services Center (GES DISC) unveiled a new service: Datalist. A Datalist is a collection of predefined or user-defined data variables from one or more archived datasets. Our science support team curated predefined datalist and provided value to the user community. Imagine some novice user wants to study hurricane and typed in hurricane in the search box. The first item in the search result is GES DISC provided Hurricane Datalist. It contains scientists recommended variables from multiple datasets like TRMM, GPM, MERRA, etc. Datalist uses the same architecture as that of our new website, which also provides one-stop shopping for data, metadata, citation, documentation, visualization and other available services.We implemented Datalist with new GES DISC web architecture, one single web page that unified all user interfaces. From that webpage, users can find data by either type in keyword, or browse by category. It also provides user with a sophisticated integrated data and services package, including metadata, citation, documentation, visualization, and data-specific services, all available from one-stop shopping.

Datalist↗
NASA NTRS2010

Learning Design at White Sands Test Facility

During the Fall of 2010, I spent my time at NASA White Sands Test Facility in Las Cruces, NM as an Undergraduate Student Research Program (USRP) Intern. During that time, I was given three projects to work on: Large Altitude Simulation System (LASS) basket strainer, log books, and the design of a case for touch screen monitors used for simulations. I spent most of my time on the LASS basket strainer. The LASS system has a water feed line with a basket strainer that filters out rust. In 2009, there were three misfires which cost approximately $27,000 and about 8% of the allotted time. The strainer was getting a large change in pressure that would result in a shutdown of the system. I have designed a new basket that will eliminate the large pressure change and it can be used with the old basket strainer housing. The LASS system has three steam generators (modules). Documents pertaining to these modules are stored electronically, and the majority of the documents are not able to be searched with keywords, so they have to be gone through one by one. I have come up with an idea on how to organize these files so that the Propulsion Department may efficiently search through the documents needed. Propulsion also has a LASS simulator that incorporates two touch screen monitors. Currently these monitors are in six foot by two foot metal cabinet on wheels. During simulation these monitors are used in the block house and need to be taken out of the block house when not in use. I have designed different options for hand held cases for storing and transporting the monitors in and out of the block house. The three projects previously mentioned demonstrate my contributions to the Propulsion Department and have taught me real world experience that is essential in becoming a productive engineer.

Grotewiel, Shane↗
NASA NTRS2015

Aluminum Mirror Coatings for UVOIR Telescope Optics Including the Far UV

NASA Cosmic Origins (COR) Program identified the development of high reflectivity mirror coatings for large astronomical telescopes particularly for the far ultra violet (FUV) part of the spectrum as a key technology requiring significant materials research and process development. In this paper we describe the challenges and accomplishments in producing stable high reflectance aluminum mirror coatings with conventional evaporation and advanced Atomic Layer Deposition (ALD) techniques. We present the current status of process development with reflectance of approx. 55 to 80% in the FUV achieved with little or no degradation over a year. Keywords: Large telescope optics, Aluminum mirror, far UV astrophysics, ALD, coating technology development.

large telescope optics↗
NASA NTRS2017

Harvesting NASA's Common Metadata Repository (CMR)

As part of NASA's Earth Observing System Data and Information System (EOSDIS), the Common Metadata Repository (CMR) stores metadata for over 30,000 datasets from both NASA and international providers along with over 300M granules. This metadata enables sub-second discovery and facilitates data access. While the CMR offers a robust temporal, spatial and keyword search functionality to the general public and international community, it is sometimes more desirable for international partners to harvest the CMR metadata and merge the CMR metadata into a partner's existing metadata repository. This poster will focus on best practices to follow when harvesting CMR metadata to ensure that any changes made to the CMR can also be updated in a partner's own repository. Additionally, since each partner has distinct metadata formats they are able to consume, the best practices will also include guidance on retrieving the metadata in the desired metadata format using CMR's Unified Metadata Model translation software.

Earth Resources↗
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↗
NASA NTRS2018

WGISS-45 International Directory Network (IDN) Report

The objective of this presentation is to provide IDN (International Directory Network) updates on features and activities to the Committee on Earth Observation Satellites (CEOS) Working Group on Information Systems and Services (WGISS) and provider community. The following topics will be will be discussed during the presentation: Transition of Providers DIF-9 (Directory Interchange Format-9) to DIF-10 Metadata Records in the Common Metadata Repository (CMR); GCMD (Global Change Master Directory) Keyword Update; DIF-10 and UMM-C (Unified Metadata Model-Collections) Schema Changes; Metadata Validation of Provider Metadata; docBUILDER for Submitting IDN Metadata to the CMR (i.e. Registration); and Mapping WGClimate Essential Climate Variable (ECV) Inventory to IDN Records.

WGISS↗
NASA NTRS2018

State of the SOOS GCMD Portal

A brief status update on NASA’s latest Global Change Master Directory (GCMD) keyword update, description of the differences between DIF-9 and DIF-10 formats in advance of the deprecation of DIF-9 support in Earth Observing System Data and Information System (EOSDIS) with specifics on the DIF-10.3 schema, transition schedule, and some usage metrics for the GCMD Southern Ocean Observing System (SOOS) Portal.

SOOS Portal↗
NASA NTRS2018

Mission Configuration Tree for the James Webb Space Telescope (JWST)

The GSFC Mission Configuration web-based application is a means of documenting the structure of the many elements used in building each mission that NASA launches, as well as archiving the documents associated with each of these elements and keeping track of suppliers. This includes all available drawings, engineering orders, parts lists, block diagrams, and photos of each system, subsystem, and component. While the information for several of NASA's missions is being input into Mission Configuration, the ten weeks of this project focused on collecting information for the instrument systems of the James Webb Space Telescope. Documents were collected from a database called the Next Generation Integrated Network (NGIN) so that they can eventually be uploaded into the application. From these documents, including drawings and parts lists, a configuration tree was created in Microsoft Visio which showed the relationships between each system, subsystem, and component. When both these documents and the configuration tree are input into Mission Configuration, they will be place into a drill down tree structure, from which drawings and documents can be accessed directly. Mission Configuration also includes search functions that make all parts searchable by keywords such as vendor, part number, taxonomy, and alternate nomenclature. This application is an important resource for providing access to documents related to the components used on each mission. It has created a central repository for information which can be used to benefit Safety & Mission Assurance, but may also be useful across codes. The process of collecting the information and documents to put into Mission Configuration is also allowing for a concise breakdown of information from diverse formats, creating standardization which makes information more readily accessible, while retaining project-specific information that makes it more easily searchable.

Cain, Mary C.↗
NASA NTRS2018

Steps Toward Improved Integration, Search, and Analysis of Heterogeneous Data in the Astrobiology Habitable Environments Database

The Astrobiology Habitable Environments Database (AHED) is a new data system being developed as a long-term, open-access repository for astrobiology data. AHED is intended to store user-contributed results from NASA or externally-funded research in astrobiology, and to encourage sharing and synergy within the astrobiology community. However, the interdisciplinary nature of astrobiology presents some specific challenges to data management, integration, and analysis within AHED. In some disciplines (e.g., genomics), open databases thrive because the contributed products are fairly uniform and standardized (e.g., sequence data). In astrobiology, each investigation produces a unique set of data products; this makes it difficult to search across different datasets to find similar data, or to combine results from separate investigations. With AHED, we are taking steps to ensure there is adequate metadata - both at the dataset and record levels - to facilitate search, integration, and analysis. At the dataset level, we are developing a new metadata standard for describing astrobiology datasets, with detailed information about content, funding source, and scientific relevance, along with a set of topical keywords for characterizing datasets. At the record level, we are encouraging users to provide more structured content and finer-grained metadata. In many user-contributed science data repositories, few restrictions are placed on the uploaded data format, and minimal or no record-level metadata is required; thus users are unburdened when it comes to data preparation. The tradeoff is that deep integration and search across datasets is almost impossible without standardized structures and metadata. Although AHED users are free to upload minimally-described datasets, they will be encouraged to use database authoring tools (supplied by the underlying platform - Open Data Repository's Data Publisher) plus a set of customizable astrobiology-specific templates to help structure their data and provide standardized metadata. In reward for their extra effort, AHED will be able to deliver enhanced search, discovery, and analysis capabilities.

astrobiology↗
NASA NTRS2018

GeneLab: Omics Database for Spaceflight Experiments

Motivation - To curate and organize expensive spaceflight experiments conducted aboard space stations and maximize the scientific return of investment, while democratizing access to vast amounts of spaceflight related omics data generated from several model organisms. Results - The GeneLab Data System (GLDS) is an open access database containing fully coordinated and curated "omics" (genomics, transcriptomics, proteomics, metabolomics) data, detailed metadata and radiation dosimetry for a variety of model organisms. GLDS is supported by an integrated data system allowing federated search across several public bioinformatics repositories. Archived datasets can be queried using full-text search (e.g., keywords, Boolean and wildcards) and results can be sorted in multifactorial manner using assistive filters. GLDS also provides a collaborative platform built on GenomeSpace for sharing files and analyses with collaborators. It currently houses 172 datasets and supports standard guidelines for submission of datasets, MIAME (for microarray), ENCODE Consortium Guidelines (for RNA-seq) and MIAPE Guidelines (for proteomics).

omics↗
NASA NTRS2018

WGISS-46 ACCESS Section: IDN Report

The objective of this presentation is to provide IDN updates on features and activities to the Committee on Earth Observation Satellites (CEOS) Working Group on Information Systems and Services (WGISS) and provider community. The following topics will be will be discussed during the presentation: Overview of NASA's Vision of Services (UMM-S), Migration of IDN SERFs to UMM-S, Metadata Management Tool (MMT): Successor to DocBuilder, DocBuilder-10: Create/Update Dataset Records, Transition of DIF-9 to DIF-10, Schedule for UMM-C and GCMD/IDN Keywords, IDN's WGISS/WGCV Joint Session: Collaborative Actions.

Committee on Earth Observation Satellites↗
NASA NTRS2018

Enriching the Twitter Stream Increasing Data Mining Yield and Quality Using Machine Learning

Social media data streams are important sources of real-time and historical global information for science applications. At the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we are exploring the Twitter data stream for its potential in augmenting the validation program of NASA Earth science missions, specifically the Global Precipitation Measurement (GPM) mission. We have implemented a tweet processing infrastructure that outputs classified precipitation tweets. Inputs are "passive" tweets, along with a smaller number of tweets from "active" participants, i.e., those knowingly contributing to our effort. The "active" tweets, presumably of higher quality, enrich the Twitter stream. "Active" sources include data scraped from other social media (e.g., public Facebook posts) and data from existing crowdsourcing programs (e.g., mPING reports). In addition, there is likely relevant precipitation information in images and documents that are the end points of links often included in tweets. Information derived from these "active" sources could then be tweeted into the Twitter stream, thus enriching its quality. The objective of our current work is to mine these tweet­ linked images and documents, using neural networks, to increase the information content and quality related to precipitation. For images, we classified them as either precipitation-related or not. For training and validation, we used images obtained via the Google custom search API. We created two models: (1) by training a simple Convolutional Neural Network and (2) by using transfer learning principles to adapt a pre-trained object recognition model. For documents, both those linked to tweets and the tweet contents, we trained Hierarchical Attention Networks to determine precipitation occurrence, type, and intensity. For training and validation, we used a keyword-filtered tweet data set labelled with ground truth data from Dark Sky (an API to retrieve weather-related labels) and the National Severe Storms Laboratory's Multi­ Radar/Multi-Sensor (MRMS) system. Our results demonstrated the efficacy of our machine learning approaches for enriching the Twitter stream, to derive information potentially useful for validation of earth science satellite data.

Albayrak, Arif↗
NASA NTRS2019

A New Laser Beam Pointing Method Using Laser Arrays

A new method is described for optical data transmissions from satellites using laser arrays for laser beam pointing. It combines a lens system and a vertical-cavity surface-emitting laser (VCSEL)/Photodetector Array, both mature technologies, in a novel way. This system is applied to satellites in low-Earth orbit, (LEO). It can replace current architectures which use dynamical systems, (i.e., moving parts) to point the laser, and which may use vibration isolation platforms. Results of computer simulations show diffraction limited beam propagation. Possible additional applications are to planetary distances (deep space optical communications, (DSOC)), to optical multiple access, (OMA), to communication between a constellation of close satellites, and to satellites that use modulating retro-reflectors. Keywords: laser beam pointing, free-space optical communication, low-Earth orbit (LEO) data communications, integrated VCSEL/ photodetector arrays, deep space optical communications (DSOC), optical multiple access (OMA), constellation of close satellites, modulating retro-reflectors.

Goorjian, P. M.↗
NASA NTRS2019

Long Term Potential Evapotranspiration and Evapotranspiration Data and Services at NASA GES DISC

Recently, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has released global land 3-hourly Potential Evapotranspiration and Supporting Forcing Data Version-1 (PET_PU_3H025.001), at 0.25x0.25 degree spatial resolution, spanning the 23 year period from 1984 to 2006. The Version-2 will be released in the near future, covering longer time period. This dataset was generated by Professor Justin Sheffield through NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) project. Potential evapotranspiration (PET) is a representation of the environmental demand for evapotranspiration (ET). ET and PET are important part of the global water cycle estimation, and are also critical to advance our understanding of the climate system. NASA GES DISC archives and distributes various global and regional ET datasets from several projects, for example, Land Data Assimilation System (LDAS), Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), other MEaSUREs Projects, such as Land Surface Atmospheric Boundary Interaction Product by William Rossow; and SRB/GEWEX evapotranspiration (Penman-Monteith) by Eric F. Wood. In this presentation, we will overview all available PET and ET datasets and services at GES DISC. As examples, climatology and some seasonal characteristics of PET and selected ET will be shown. The data can be accessed from NASA GES DISC (https://disc.gsfc.nasa.gov/) by searching keyword "evapotranspiration".

Shen, Suhung↗
NASA NTRS2019

Integrated Analysis of Multiple User Metrics - A “Sequel”; and Introducing the Google Analytic

For decades, the Goddard Earth Sciences Data and Information Services Center (GES DISC) has archived and distributed enormous volumes of NASA Earth science data (accompanied with many developed tools and services) to various research/applications communities and the general public. Being “immersed” in the Big Data era, we have inevitably faced the challenges of our continually increasing archived data in both volume and variety, as well as enhanced user needs and demands. In recent years, we have actively analyzed different types of user metrics, such as operational distribution metrics (recording numbers of distinct users and downloaded data files, size of distributed data volume): user publication metrics (mining info from our Giovanni users’ publications): and Bugzilla metrics (collecting info from user questions or feedback from user assistance tickets). Such metrics have helped us achieve a better understanding of user needs, demands, characteristics, and behaviors, which has then helped us improve our user services. Now we will present a “Sequel” of integrated analysis of multiple metrics at the GES DISC by introducing and adding one new kind of metrics acquired via utilizing our recently implemented Google Analytic 360 suite. Several “newer” reports, e.g., “What web site features and links are the most popular (and least)?” and “What are the top 25 dataset Keyword searches?” retrieved from this new metrics set will be presented, along with the aforementioned “traditional” metrics results.

Shie, Chung-Lin↗
NASA NTRS2020

Near 40 Years MERRA-2 Data at NASA GES DISC -Opportunity and Challenge to Support Extremes Study

To the end of 2019, 40 years NASA climate reanalysis data sets from the Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) will be available at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 consists atmosphere, land, and ocean data, which may be used for the studies ranging from the short scale weather events to the large scale decadal vulnerabilities. The hourly products, such as precipitation, soil moisture, temperature, and aerosols etc., have been used widely to study extreme events.In supporting users from broad communities, GES DISC have developed various data access services, including subsetter for downloading only data of interest with preferred format; OPeNDAP - for machine-to-machine data access; and Giovanni- for online visualization and analysis, etc. A big challenge for extreme study is to downloading and processing long-term hourly or daily data. The data downloading performance is not very satisfied by many users with current services and the native archived data structure. Late June 2019, many people in Europe had experienced extreme heat waves. The temperatures in several countries exceeded 40°C (104°F). For example, MERRA-2 shows that the near surface daily maximum temperature of June 28 2019 over Marseille, a city in southern France, reached 41.1 °C (106°F), which is the record breaking temperature in the last 40 years. GES DISC is working together with domain science experts to improve the performance of long time series access, making analysis ready data sets in supporting application researches, such as extreme study. In this presentation, using Europe heat wave as an example, we will show prototype of the in developing service for finding extremes from near 40 years MERRA-2 data at a given location. MERRA-2 data can be accessed from NASA GES DISC(https://disc.gsfc.nasa.gov/ ) by search keyword "MERRA-2".

Shen, Suhung↗