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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 NTRS2005

Analysis of Piezoelectric Structural Sensors with Emergent Computing Techniques

The purpose of this project was to try to interpret the results of some tests that were performed earlier this year and to demonstrate a possible use of emergence in computing to solve IVHM problems. The test data used was collected with piezoelectric sensors to detect mechanical changes in structures. This project team was included of Dr. Doug Ramers and Dr. Abdul Jallob of the Summer Faculty Fellowship Program, Arnaldo Colon-Lopez - a student intern from the University of Puerto Rico of Turabo, and John Lassister and Bob Engberg of the Structural and Dynamics Test Group. The tests were performed by Bob Engberg to compare the performance two types of piezoelectric (piezo) sensors, Pb(Zr(sub 1-1)Ti(sub x))O3, which we will label PZT, and Pb(Zn(sub 1/3)Nb(sub 2/3))O3-PbTiO, which we will label SCP. The tests were conducted under varying temperature and pressure conditions. One set of tests was done by varying water pressure inside an aluminum liner covered with carbon-fiber composite layers (a cylindrical "bottle" with domed ends) and the other by varying temperatures down to cryogenic levels on some specially prepared composite panels. This report discusses the data from the pressure study. The study of the temperature results was not completed in time for this report. The particular sensing done with these piezo sensors is accomplished by the sensor generating an controlled vibration that is transmitted into the structure to which the sensor is attached, and the same sensor then responding to the induced vibration of the structure. There is a relationship between the mechanical impedance of the structure and the resulting electrical impedance produced in the in the piezo sensor. The impedance is also a function of the excitation frequency. Changes in the real part of impendance signature relative to an original reference signature indicate a change in the coupled structure that could be the results of damage or strain. The water pressure tests were conducted by pressurizing the bottle on a test stand, and running sweeps of excitations frequencies for each of the piezo sensors and recording the resulting impedance. The sweeps were limited to 401 points by the available analyzer, and it was decided to perform individual sweeps at five different excitation frequency ranges. The frequency ranges used for the PZTs were different in two of the five ranges from the ranges used for the SCP. The bottles were pressurized to empty (no water), 0psig, 77 psig, 155 psig, 227 psig in nearly uniform increments of about 77psi. One of each of the two types of piezo sensors was fastened on to the bottle surface at two locations: about midway between the ends on cylindrical portion of the bottle and at the very edge of one of the end domes. The data was collected in files by sensor type (2 cases), by location (2 cases), by frequency range (5 cases), and pressure (5cases) to produce 100 data sets of 401 impedances. After familiarization with the piezo sensing technology and obtaining the data, the team developed a set of questions to try to answer regarding the data and made assignments of responsibilities. The next section lists the questions, and the remainder of the report describes the data analysis work performed by Dr. Ramers. This includes a discussion of the data, the approach to answering the question using statistical techniques, the use of an emergent system to investigate the data where statistical techniques were not usable, conclusions regarding the data, and recommendations.

Ramers, Douglas L.↗
NASA NTRS2011

Restoration of Apollo Data by the NSSDC and the PDS Lunar Data Node

The Lunar Data Node (LDN), under the auspices of the Geosciences Node of the Planetary Data System (PDS), is restoring Apollo data archived at the National Space Science Data Center. The Apollo data were arch ived on older media (7 -track tapes. microfilm, microfiche) and in ob solete digital formats, which limits use of the data. The LDN is maki ng these data accessible by restoring them to standard formats and archiving them through PDS. The restoration involves reading the older m edia, collecting supporting data (metadata), deciphering and understa nding the data, and organizing into a data set. The data undergo a pe er review before archive at PDS. We will give an update on last year' s work. We have scanned notebooks from Otto Berg, P.1. for the Lunar Ejecta and Meteorites Experiment. These notebooks contain information on the data and calibration coefficients which we hope to be able to use to restore the raw data into a usable archive. We have scanned Ap ollo 14 and 15 Dust Detector data from microfilm and are in the proce ss of archiving thc scans with PDS. We are also restoring raw dust de tector data from magnetic tape supplied by Yosio Nakamura (UT Austin) . Seiichi Nagihara (Texas Tech Univ.) and others in cooperation with NSSDC are recovering ARCSAV tapes (tapes containing raw data streams from all the ALSEP instruments). We will be preparing these data for archive with PDS. We are also in the process of recovering and archivi ng data not previously archived, from the Apollo 16 Gamma Ray Spectro meter and the Apollo 17 Infrared Spectrometer.

Williams, David R.↗
NASA NTRS2018

FAIRness and Usability for Open-Access Omics Data Systems

Omics data sharing is especially crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. 14 metrics. The range of Pass ratings was 29-79% of the 14 metrics, Partial Pass 0-21%, and Fail 7-50%. The range of overall FAIRness scores was 5-12 (out of 14). The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. We propose two new principles that Big Data systems, in particular, should consider for increasing data accessibility. We relate our experiences implementing semantic integration of omics data from several systems for the federated querying and retrieval functions of the GLDS, given the shortcomings in data interoperability of these systems.

Berrios, Daniel C.↗
NASA NTRS2018

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Berrios, Daniel C.↗
NASA NTRS2018

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the “FAIRness” of NASA’s GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Berrios, Daniel C.↗
NASA NTRS2005

Fatigue Crack Growth Database for Damage Tolerance Analysis

The objective of this project was to begin the process of developing a fatigue crack growth database (FCGD) of metallic materials for use in damage tolerance analysis of aircraft structure. For this initial effort, crack growth rate data in the NASGRO (Registered trademark) database, the United States Air Force Damage Tolerant Design Handbook, and other publicly available sources were examined and used to develop a database that characterizes crack growth behavior for specific applications (materials). The focus of this effort was on materials for general commercial aircraft applications, including large transport airplanes, small transport commuter airplanes, general aviation airplanes, and rotorcraft. The end products of this project are the FCGD software and this report. The specific goal of this effort was to present fatigue crack growth data in three usable formats: (1) NASGRO equation parameters, (2) Walker equation parameters, and (3) tabular data points. The development of this FCGD will begin the process of developing a consistent set of standard fatigue crack growth material properties. It is envisioned that the end product of the process will be a general repository for credible and well-documented fracture properties that may be used as a default standard in damage tolerance analyses.

Metallic materials↗
NASA NTRS2016

Wearable Biosensor Monitor to Support Autonomous Crew Health and Performance

During future human exploration missions, spaceflight crews will encounter adverse health outcomes and decrements in performance during the missions and for long term health. The Psychophysiological Research Lab is currently conducting a technology demonstration of a prototype wearable biosensor system (Astroskin) on astronaut surrogates during 30 day missions within NASAs Human Exploration Research Analog (HERA). HERA, located at Johnson Spaceflight Center, represents a flight analog for simulation of isolation, confinement and remote conditions of mission exploration scenarios. Astroskin, an autonomous medical monitoring system, consists of an intelligent garment for the upper body and a headband fitted with sensors, and associated software and hardware that can measure, transmit and store vital signs (ECG, respiration, blood pressure, etc.), sleep quality and activity level of the wearer. One of the main goals of the technology demonstration is to evaluate the performance of the Astroskin system (i.e., data quality), crew usability and comfort. To validate the Astroskin as a viable option for use during future spaceflight missions, crew data from HERA are sent to Ames researchers for processing and analyses. Crew surveys on usability and comfort will also be evaluated. This work supports the Exploration Medical Capabilities element within NASAs Human Research Program.

space analog↗
NASA NTRS2003

Data Access Tools And Services At The Goddard Distributed Active Archive Center (GDAAC)

As one of the largest providers of Earth Science data from the Earth Observing System, GDAAC provides the latest data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Solar Radiation and Climate Experiment (SORCE) data products via GDAAC's data pool (50TB of disk cache). In order to make this huge volume of data more accessible to the public and science communities, the GDAAC offers multiple data access tools and services: Open Source Project for Network Data Access Protocol (OPeNDAP), Grid Analysis and Display System (GrADS/DODS) (GDS), Live Access Server (LAS), OpenGlS Web Map Server (WMS) and Near Archive Data Mining (NADM). The objective is to assist users in retrieving electronically a smaller, usable portion of data for further analysis. The OPeNDAP server, formerly known as the Distributed Oceanographic Data System (DODS), allows the user to retrieve data without worrying about the data format. OPeNDAP is capable of server-side subsetting of HDF, HDF-EOS, netCDF, JGOFS, ASCII, DSP, FITS and binary data formats. The GrADS/DODS server is capable of serving the same data formats as OPeNDAP. GDS has an additional feature of server-side analysis. Users can analyze the data on the server there by decreasing the computational load on their client's system. The LAS is a flexible server that allows user to graphically visualize data on the fly, to request different file formats and to compare variables from distributed locations. Users of LAS have options to use other available graphics viewers such as IDL, Matlab or GrADS. WMS is based on the OPeNDAP for serving geospatial information. WMS supports OpenGlS protocol to provide data in GIs-friendly formats for analysis and visualization. NADM is another access to the GDAAC's data pool. NADM gives users the capability to use a browser to upload their C, FORTRAN or IDL algorithms, test the algorithms, and mine data in the data pool. With NADM, the GDAAC provides an environment physically close to the data source. NADM will benefit users with mining or offer data reduction algorithms by reducing large volumes of data before transmission over the network to the user.

Pham, Long↗
NASA NTRS2011

Capturing, Harmonizing and Delivering Data and Quality Provenance

Satellite remote sensing data have proven to be vital for various scientific and applications needs. However, the usability of these data depends not only on the data values but also on the ability of data users to assess and understand the quality of these data for various applications and for comparison or inter-usage of data from different sensors and models. In this paper, we describe some aspects of capturing, harmonizing and delivering this information to users in the framework of distributed web-based data tools.

Leptoukh, Gregory↗
NASA NTRS2017

GES DISC Greenhouse Gas Data Sets and Associated Services

NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) archives and distributes rich collections of data on atmospheric greenhouse gases from multiple missions. Hosted data include those from the Atmospheric Infrared Sounder (AIRS) mission (which has observed CO2, CH4, ozone, and water vapor since 2002); legacy water vapor and ozone retrievals from TIROS Operational Vertical Sounder (TOVS); and Upper Atmosphere Research Satellite (UARS) going back to the early 1980s. GES DISC also archives and supports data from seven projects of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) program that have ozone and water vapor records. Greenhouse gases data from the A-Train satellite constellation is also available: (1) Aura-Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) ozone, nitrous oxide, and water vapor since 2004; (2) Greenhouse Gases Observing Satellite (GOSAT) CO2 observations since 2009 from the Atmospheric CO2 Observations from Space (ACOS) task; and (3) Orbiting Carbon Observatory-2 (OCO-2) CO2 data since 2014. The most recent related data set that the GES DISC archives is methane flux for North America, as part of NASAs Carbon Monitoring System (CMS) project. This dataset contains estimates of methane emission in North America based on an inversion of the GEOS-Chem chemical transport model constrained by GOSAT observations (Turner et al., 2015). Along with data stewardship, an important focus area of the GES DISC is to enhance the usability of its data and broaden its user base. Users have unrestricted access to a new user-friendly search interface, which includes many services such as variable subsetting, format conversion, quality screening, and quick browse. The majority of the GES DISC data sets are also accessible through Open-source Project for a Network Data Access Protocol (OPeNDAP) and Web Coverage Service (WCS). The latter two services provide more options for specialized subsetting, format conversion, and image viewing. Additional data exploration, data preview, and preliminary analysis capabilities are available via NASA Giovanni, which obviates the need forusers to download the data (Acker and Leptoukh, 2007). Giovanni provides a bridge between the data and science and has been very successful in extending GES DISC data to educational users and to users with limited resources.

data ordering↗
NASA NTRS2016

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↗
NASA NTRS2018

End-to-End Solution for Data Customization with NASA's Earthdata Search

The goal of NASA's Earthdata Search End-to-End Services workflow is to take the pain and headache out of searching for data and getting that data back in a format that is usable with only that data that is relevant for you. For too long scientists have had to jump through endless hoops, use tools that only offer specific data or specific services, and perform any number of other non-science tasks just to get started on their actual project. Earthdata Search leverages the Common Metadata Repository's (CMR) newly implemented Unified Metadata Models for Services and Variables as well as a new service broker to expose and seamlessly integrate a collection's service capabilities and variables into an intuitive user interface. Using the new End-to-End Services workflow, scientists will be able to quickly see what data is available to be customized, what customization options are available, and actually perform those customizations on the data all within Earthdata Search, regardless of who the data provider is. This talk will demonstrate the simple workflow that will be available to end users and also give an overview covering how the workflow is enabled by the metadata stored within the CMR. (https://search.earthdata.nasa.gov/)

Reese, Mark↗
NASA NTRS2020

NASA ESDS Citizen Science Data Working Group

This document provides guidelines for legal, policy, and ethical issues; standards for citizen science data collection and management; information on ensuring usability of citizen science data and communication regarding its use; and best practices for long-term archival of citizen science data.Section1 contains a detailed discussion of policy, ethical, and legal considerations influencing citizen science data collection. Section 2 considers standards for documentation, including documentation of instrumentation, procedures, and the data itself. It concludes with a discussion of how citizen science data should be attributed. Section 3 provides guidance about how to ensure citizen science data are collected and stored in a useable way. It also considers how NASA and data producers should notify the scientific community, including citizen scientists and the public, about citizen science datasets and the scientific conclusions reached using them. Finally, Section 4 provides detailed information regarding what should be archived from projects using a citizen science approach, including data and code. It provides guidance about archive location, process, and timeframe, as well as information about data access and distribution services provided by NASA that may be relevant to data producers working with citizen scientists.

Citizen Science↗
NASA NTRS2010

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Liu, Zhong↗
NASA NTRS2002

NASA planetary data: applying planetary satellite remote sensing data in the classroom

NASA supports several data archiving and distribution mechanisms that provide a means whereby scientists can participate in education and outreach through the use of technology for data and information dissemination. The Planetary Data System (PDS) is sponsored by NASA's Office of Space Science. Its purpose is to ensure the long-term usability of NASA data and to stimulate advanced research. In addition, the NASA Regional Planetary Image Facility (RPIF), an international system of planetary image libraries, maintains photographic and digital data as well as mission documentation and cartographic data.

Regional Plaentary Image Facility RPIF Planetary D↗
NASA NTRS2009

Evolution of Information Management at the GSFC Earth Sciences (GES) Data and Information Services Center (DISC): 2006-2007

Increasingly sophisticated National Aeronautics and Space Administration (NASA) Earth science missions have driven their associated data and data management systems from providing simple point-to-point archiving and retrieval to performing user-responsive distributed multisensor information extraction. To fully maximize the use of remote-sensor-generated Earth science data, NASA recognized the need for data systems that provide data access and manipulation capabilities responsive to research brought forth by advancing scientific analysis and the need to maximize the use and usability of the data. The decision by NASA to purposely evolve the Earth Observing System Data and Information System (EOSDIS) at the Goddard Space Flight Center (GSFC) Earth Sciences (GES) Data and Information Services Center (DISC) and other information management facilities was timely and appropriate. The GES DISC evolution was focused on replacing the EOSDIS Core System (ECS) by reusing the In-house developed disk-based Simple, Scalable, Script-based Science Product Archive (S4PA) data management system and migrating data to the disk archives. Transition was completed in December 2007

Kempler, Steven↗
NASA NTRSDate not supplied

Open-Source Science-Driven Development of the Science Data System (SDS) for Earth System Observatory (ESO) Atmospheric Missions

The NASA Earth System Observatory (ESO) atmospheric missions will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The Science Data System (SDS) will deploy the adaptive processing system (APS) developed within the Cloud to manage the research and operational processing of ESO atmospheric mission orbital and suborbital sensors and curate these data for near real-time and collection reprocessing and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage and distribution. Further, the SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The SDS follows NASA’s commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the SDS system components will be developed with open-source concepts including components of APS itself as well as ESO atmospheric mission algorithms. This presentation describes the framework of the SDS and its integral part in facilitating OSS within the ESO atmospheric missions.

David M. Giles↗
NASA NTRS2015

Exploring NASA GES DISC Data with Interoperable Services

Overview of NASA GES DISC (NASA Goddard Earth Science Data and Information Services Center) data with interoperable services: Open-standard and Interoperable Services Improve data discoverability, accessibility, and usability with metadata, catalogue and portal standards Achieve data, information and knowledge sharing across applications with standardized interfaces and protocols Open Geospatial Consortium (OGC) Data Services and Specifications Web Coverage Service (WCS) -- data Web Map Service (WMS) -- pictures of data Web Map Tile Service (WMTS) --- pictures of data tiles Styled Layer Descriptors (SLD) --- rendered styles.

Giovanni↗