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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 NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks and challenges associated with deep space missions and experiments (cis-Lunar, Mars transit/surface) require new knowledge discovery and development of novel ecosystems. Supporting distant and long-duration missions and experiments requires biological data (from yeast, microbes, fruit flies, C. elegans, plants, crops, rodents, humans) be findable, accessible, interoperable, reusable (FAIR), and maximally open-access. As data-intensive, bioinformatic, meta-analytical, and computer-assisted approaches continue to be a centerpiece of modern research, the NASA Biological and Physical Sciences division is expanding its Open Science capabilities beyond NASA GeneLab. The NASA Ames Life Sciences Data Archive (ALSDA) is a repository which is responsible for collecting and access to space biological imagery and video, alongside tabular and environmental data. In this presentation, we will discuss strategies dealing with archiving, curating, and accessibility of images from very distinct imaging modalities (e.g., micro-computed tomography, magnetic resonance imaging, photographic images of plants, fluorescence microscopy, behavioral videos, etc.). There are two main challenges: 1. Open-source data storage and 2. Metadata related to the imagery-video. Both have been solved by leveraging two existing open-source systems. For data storage, ALSDA is utilizing components through the Open Microscopy Environment (OME), which can read most imaging proprietary formats and display on a web interface complex multidimensional images (Z stack, multi-channel, temporal, spectral). Most technical metadata from imaging modalities are captured seamlessly. For metadata capturing experimental details, ALSDA (like GeneLab) uses the ISA-Tab specification which relies on the ISA data model to order and classify metadata. The ISA data model uses a tree structure with three files to capture the metadata: The top layer is the Investigations file, the second layer is the Study file(s), and the last layer is the Assay file(s). We believe such an approach may be useful for other types of image research data from other investigators in the AGU community.

imaging↗
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 NTRS1987

Anomalous dust in the open cluster Trumpler 37

New IUE data were obtained towards stars in the open cluster Trumpler 37. Extinction curves derived from these data show that the anomalous dust detected towards HD 204827 and HD 210072 is not unique to those lines of sight but occurs generally in that region of the sky. The dust is apparently associated with the Trumpler 37 cluster, which forms the center of Cepheus OB2. This is a complex region of star formation where the evolution of dust grains through shock waves could be considered likely. A supernova in a slightly older star-forming region of Cep OB2 located next to Trumpler 37 is a possible source of such a shock wave.

Clayton, Geoffrey C.↗
DOE OSTI2024

Protein data bank: From two epidemics to the global pandemic to mRNA vaccines and Paxlovid

Structural biologists and the open-access Protein Data Bank (PDB) played decisive roles in combating the COVID-19 pandemic. Global biostructure data were turned into global knowledge, allowing scientists and engineers to understand the inner workings of coronaviruses and develop effective countermeasures. Two mRNA vaccines, initially designed with guidance from PDB structures of the SARS-CoV-1 and MERS-CoV spike proteins, prevented infections entirely or reduced the likelihood of morbidity and mortality for more than five billion individual recipients worldwide. Structure-guided drug discovery by Pfizer, Inc (facilitated by PDB structures), initiated in the 2000s in response to SARS-CoV-1 and resumed in 2020, yielded nirmatrelvir (the active ingredient of Paxlovid) -- a potent, orally-bioavailable inhibitor of the SARS-CoV-2 main protease. You've got to love the Protein Data Bank!

Burley, Stephen K.↗
NASA NTRS1998

Mapping Northern Exposure With POLDER: Application for Circumpolar Methane Exchange

Three images types from POLDER airborne imagery, nadir looking multi-spectral bands, multiple view-angle images of the red band, and combined datasets, were used to classify land cover types at the NASA southern BOREAS study site in Saskatchewan, Canada. We found that combining multiple view-angle imagery with nadir viewing multi-spectral bands provided the greatest accuracy and discrimination of the largest number of inundated and non-inundated land cover classes. While the nadir looking multi-spectral band data correctly separated open water from other land cover classes it did not separate the inundated vegetated regions that define boreal wetlands. Multiple view-angle data could separate two upland vegetation types and open water but only one inundated vegetation type.

Ustin, Susan L.↗
NASA NTRS1998

The Aviation Performance Measuring System (APMS): An Integrated Suite of Tools for Measuring Performance and Safety

This is a report of work in progress. In it, I summarize the status of the research and development of the Aviation Performance Measuring System (APMS) for managing, processing, and analyzing digital flight-recorded data, The objectives of the NASA-FAA APMS research project are to establish a sound scientific and technological basis for flight-data analysis, to define an open and flexible architecture for flight-data analysis systems, and to articulate guidelines for a standardized database structure on which to continue to build future flight-data-analysis extensions. APMS offers to the air transport community an open, voluntary standard for flight-data-analysis software; a standard that will help to ensure suitable functionality and data interchangeability among competing software programs. APMS will develop and document the methodologies, algorithms, and procedures for data management and analyses to enable users to easily interpret the implications regarding safety and efficiency of operations. APMS does not entail the implementation of a nationwide flight-data-collection system. It is intended to provide technical tools to ease the large-scale implementation of flight-data analyses at both the air-carrier and the national-airspace levels in support of their Flight Operations and Quality Assurance (FOQA) Programs and Advanced Qualifications Programs (AQP). APMS cannot meet its objectives unless it develops tools that go substantially beyond the capabilities of the current commercially available software and supporting analytic methods that are mainly designed to count special events. These existing capabilities, while of proven value, were created primarily with the needs-of aircrews in mind. APMS tools must serve the needs of the government and air carriers, as well as aircrews, to fully support the FOQA and AQP programs. They must be able to derive knowledge not only through the analysis of single flights (special-event detection), but also through statistical evaluation of the performance of large groups of flights. This paper describes the integrated suite of tools that will assist analysts in evaluating the operational performance and safety of the national air transport system, the air carrier, and the aircrew.

Statler, Irving C.↗
NASA NTRS1996

APMS: An Integrated Set of Tools for Measuring Safety

This is a report of work in progress. In it, I summarize the status of the research and development of the Aviation Performance Measuring System (APMS) for managing, processing, and analyzing digital flight-recorded data. The objectives of the NASA-FAA APMS research project are to establish a sound scientific and technological basis for flight-data analysis, to define an open and flexible architecture for flight-data-analysis systems, and to articulate guidelines for a standardized database structure on which to continue to build future flight-data-analysis extensions. APMS will offer to the air transport community an open, voluntary standard for flight-data-analysis software, a standard that will help to ensure suitable functionality, and data interchangeability, among competing software programs. APMS will develop and document the methodologies, algorithms, and procedures for data management and analyses to enable users to easily interpret the implications regarding safety and efficiency of operations. APMS does not entail the implementation of a nationwide flight-data-collection system. It is intended to provide technical tools to ease the large-scale implementation of flight-data analyses at both the air-carrier and the national-airspace levels in support of their Flight Operations and Quality Assurance (FOQA) Programs and Advanced Qualifications Programs (AQP). APMS cannot meet its objectives unless it develops tools that go substantially beyond the capabilities of the current commercially available software and supporting analytic methods that are mainly designed to count special events. These existing capabilities, while of proven value, were created primarily with the needs of air crews in mind. APMS tools must serve the needs of the government and air carriers, as well as air crews, to fully support the FOQA and AQP programs. They must be able to derive knowledge not only through the analysis of single flights (special-event detection), but through statistical evaluation of the performance of large groups of flights. This paper describes the integrated suite of tools that will assist analysts in evaluating the operational performance and safety of the national air transport system, the air carrier, and the air crew.

Statler, Irving C.↗
NASA NTRS1997

APMS: An Integrated Suite of Tools for Measuring Performance and Safety

This is a report of work in progress. In it, I summarize the status of the research and development of the Aviation Performance Measuring System (APMS) for managing, processing, and analyzing digital flight-recorded data. The objectives of the NASA-FAA APMS research project are to establish a sound scientific and technological basis for flight-data analysis, to define an open and flexible architecture for flight-data-analysis systems, and to articulate guidelines for a standardized database structure on which to continue to build future flight-data-analysis extensions . APMS will offer to the air transport community an open, voluntary standard for flight-data-analysis software, a standard that will help to ensure suitable functionality, and data interchangeability, among competing software programs. APMS will develop and document the methodologies, algorithms, and procedures for data management and analyses to enable users to easily interpret the implications regarding safety and efficiency of operations. APMS does not entail the implementation of a nationwide flight-data-collection system. It is intended to provide technical tools to ease the large-scale implementation of flight-data analyses at both the air-carrier and the national-airspace levels in support of their Flight Operations and Quality Assurance (FOQA) Programs and Advanced Qualifications Programs (AQP). APMS cannot meet its objectives unless it develops tools that go substantially beyond the capabilities of the current commercially available software and supporting analytic methods that are mainly designed to count special events. These existing capabilities, while of proven value, were created primarily with the needs of air crews in mind. APMS tools must serve the needs of the government and air carriers, as well as air crews, to fully support the FOQA and AQP programs. They must be able to derive knowledge not only through the analysis of single flights (special-event detection), but through statistical evaluation of the performance of large groups of flights. This paper describes the integrated suite of tools that will assist analysts in evaluating the operational performance and safety of the national air transport system, the air carrier, and the air crew.

Statler, Irving C.↗
NASA NTRS1997

APMS: An Integrated Suite of Tools for Measuring Performance and Safety

This is a report of work in progress. In it, I summarize the status of the research and development of the Aviation Performance Measuring System (APMS) for managing, processing, and analyzing digital flight-recorded data. The objectives of the NASA-FAA APMS research project are to establish a sound scientific and technological basis for flight-data analysis, to define an open and flexible architecture for flight-data-analysis systems, and to articulate guidelines for a standardized database structure on which to continue to build future flight-data-analysis extensions. APMS will offer to the air transport community an open, voluntary standard for flight-data-analysis software, a standard that will help to ensure suitable functionality, and data interchangeability, among competing software programs. APMS will develop and document the methodologies, algorithms, and procedures for data management and analyses to enable users to easily interpret the implications regarding safety and efficiency of operations. APMS does not entail the implementation of a nationwide flight-data-collection system. It is intended to provide technical tools to ease the large-scale implementation of flight-data analyses at both the air-carrier and the national-airspace levels in support of their Flight Operations and Quality Assurance (FOQA) Programs and Advanced Qualifications Programs (AQP). APMS cannot meet its objectives unless it develops tools that go substantially beyond the capabilities of the current commercially available software and supporting analytic methods that are mainly designed to count special events. These existing capabilities, while of proven value, were created primarily with the needs of air crews in mind. APMS tools must serve the needs of the government and air carriers, as well as air crews, to fully support the FOQA and AQP programs. They must be able to derive knowledge not only through the analysis of single flights (special-event detection), but through statistical evaluation of the performance of large groups of flights. This paper describes the integrated suite of tools that will assist analysts in evaluating the operational performance and safety of the national air transport system, the air carrier, and the air crew.

Statler, Irving C.↗
NASA NTRS2016

Achieving Fast Operational Intelligence in NASA's Deep Space Network Through Complex Event Processing

NASA’s Deep Space Network (DSN) is a complex, global project, in which the expertise of human operators remain crucial for its successful operation. To find ways to save costs in operations and to improve its services, a number of modernization efforts are underway in the DSN. One such effort is a research and technology development task at the Jet Propulsion Laboratory that is investigating the use of complex event processing (CEP) for intelligent assessment of situations, trend analysis, and advanced automation. The technology leverages the significant business intelligence (BI) and data science advancements made in the enterprise industries over the last several years. The open source big data processing engine Apache SparkTM and the high-throughput, distributed messaging system Apache Kafka form the core of the DSN Complex Event Processing (DCEP) framework. This paper discusses the system engineering perspective of why achieving efficient, lower-cost operations in the DSN is a challenging problem, how the DCEP system handles the use cases that help realize intelligent operations, and how this solution fits into the overall model of the planned DSN Follow-the- Sun Operations (FtSO).

Choi, Joshua S.↗
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 NTRS2005

Aerosol and Cloud Observations and Data Products by the GLAS Polar Orbiting Lidar Instrument

The Geoscience Laser Altimeter System (GLAS) launched in 2003 is the first polar orbiting satellite lidar. The instrument was designed for high performance observations of the distribution and optical scattering cross sections of clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. Both receiver channels meet and exceed their design goals, and beginning with a two month period through October and November 2003, an excellent global lidar data set now exists. The data products for atmospheric observations include the calibrated, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data sets are now in open release through the NASA data distribution system. The initial results on global statistics for cloud and aerosol distribution has been produced and in some cases compared to other satellite observations. The sensitivity of the cloud measurements is such that the 70% global cloud coverage result should be the most accurate to date. Results on the global distribution of aerosol are the first that produce the true height distribution for model inter-comparison.

Spinhirne, J. D.↗
DOE OSTI2022

Enabling Data Exchange and Data Integration with the Common Information Model: An Introduction for Power Systems Engineers and Application Developers

The Common Information Model (CIM) is an open-source information model that is used to model an electrical network and the various equipment used on the network. CIM is widely used for data exchange of bulk transmission power systems and is finding increasing use for distribution systems. Use of a non-proprietary information model (such as CIM) that has been agreed upon and adopted by numerous utilities, vendors, and researchers allows significant reduction in the effort and cost of data integration. Likewise, adoption of open data platforms built around the CIM increases available functionalities for managing and optimizing the smart grid of the future. This report is intended as an introduction to CIM for utility engineers, power systems researchers, and application developers, providing a broad view of the CIM and how particular profiles can be adapted for various use cases. Unlike most other CIM introduction documents and the International Electrotechnical Commission (IEC) standards (which are mostly targeted to an audience of data scientists, enterprise database managers, and platform developers), this report is intended for users of traditional power systems analysis software and other readers without any prior experience with canonical information models, data profiles, or UML modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Performance Year 1 Technical Report - OPEN COG Grid: Extendable Coherent Models-Datasets for Cognitive Power Grids

The OPEN COG Grid project is a collaborative effort between LLNL, NREL, and Texas A&M University (TAMU) to develop synthetic power system datasets that (i) contain all technical information that would be available in a real system, allowing to conduct studies ranging from dynamic simulation to long term planning studies; ii) are accessible to researchers from the broader data sciences community, as oppossed to power system experts only; and (iii) This report summarizes the work conducted during the first 15 months of execution of the project. These activities encompassed: 1. Conduct a survey of existing open data sets and open source power systems simulators, their supported use cases, and accessibility (Chapter 1). 2. Define a new extensible specification for power system data, covering all parameters necessary for most computational use cases (Chapter 2). 3. Collecting real technical system data to complete missing parameters in existing open source datasets (Chapter 3). 4. Develop models that capture the behavior of emergent actors in power grids, neglected by existing datasets; aggregated residential demand response (Chapter 4) and demand response of cryptocurrency miners (Chapter 5). 5. Collect detailed spatial information on distributed energy resources, particular, solar photovoltaic facilities (Chapter 6). The following chapters provide detailed descriptions of these tasks, the assumptions taken, and their findings. In conducting these tasks, the project team produced: two (accepted) conference papers; one journal paper under submission; one draft journal paper pending submission; released one repository with the developed power system data specification, with documentation and examples; and one extended dataset for the Texas power grid under review for release. The team hopes these contributions will enhance access to power system data and remove barriers to the development of new computational techniques for power systems, particularly, those inspired by cognitive sciences.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Open Source Platform for Live Processing of High Data Rate Electron Microscopy (SBIR Phase I Award Topic 15, Subtopic B, Final Scientific / Technical Report)

4D scanning transmission electron microscopy (STEM) is experiencing a revolution both in terms of data size, and data veracity, as are many other areas of experimental data acquisition. This presents enormous opportunities to make new scientific discoveries, but is also hamstrung by aging software that is no longer fit for purpose. Experimental data acquisition platforms must make the same investments in software infrastructure that the simulation community made decades ago to take advantage of high-performance computing (HPC) if they hope to realize the full potential of the latest advances made in detector technology. This requires rethinking the design and deployment of hardware, moving away from small, fixed commodity computing capabilities with closed interfaces to open, modular, scalable systems designed for parallelism and throughput. The technical approach will leverage best-in-class open source technologies, and develop new approaches strategically to build an open source platform for experimental data acquisition targeting high data rate electron microscopy. The project will develop a software platform that uses the power and performance of modern HPC resources to ingest the large volume of data produced by electron microscopes using direct electron detectors. A set of configurable pipelines will be used to enable the processing to be tailored to the problem being investigated with builtin visualization of data at interactive rates. This project will leverage investments made by the DOE and other agencies to provide a powerful software platform for the experimental data community working with most powerful electron microscopes, such as 4D STEM detectors. It will create a platform that serves as a reference for the community. Permissive open source licensing will make the platform available to all, with a simple deployment strategy offering the ability to keep data close to where it is generated. This advanced software platform will require customization for each deployment, creating opportunities for software services that are typically offered to extend open source software platforms.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2024

Spring 2021 Sea Ice Transport in the Southern Beaufort Sea Occurred During Coastal Lead Opening Events

Winds blew a record large portion of the Arctic’s multiyear sea ice (MYI) into the southern Beaufort Sea (SBS) in winter 2021. From early March, a network of buoys from the Sea Ice Dynamic Experiment (SIDEx) tracked the MYI as it drifted across the SBS toward the Chukchi Sea. Transport was episodic as the consolidated ice pack interacted with coastal boundaries and repeatedly fractured. We investigated variability in 2021 MYI transport by relating in situ sea ice drift to remotely sensed coastal lead opening events, which have been associated with increased ice drift speeds in winter. Daily ice concentration data show ten opening events occurred throughout March and April 2021. Opening lasted 1-5 consecutive days as southeasterly winds pushed the SBS ice pack away from coastal boundaries. During opening, the ice pack abruptly accelerated and its response to wind forcing stabilized around free drift conditions, drifting at 2.1 % of wind speeds (median rate of 13.7 km d −1 ). With this efficient wind-to-ice momentum transfer, nearly all (94 %) alongshore MYI transport in March-April 2021 occurred during opening events, which comprised just half of March-April days. Only 6 % of transport occurred during the other half of days without observed opening. On these days, the ice was mostly stationary (median 1.7 km d −1 drift rate, 0.6 % of wind speeds) as northwesterly winds compressed the pack against the coast. Spatiotemporal discontinuities in ice-wind speed ratios were measured across several coastal leads that transected the SIDEx buoy network, providing direct observations of changes in ice drift regime as coastal leads opened. These results quantify the disproportionate contribution of offshore and alongshore winds in breaking the SBS ice pack away from the coast, opening leads, and driving SBS ice transport during spring 2021, highlighting the critical role these episodic events play in consolidation season sea ice drift.

Oceanography↗
DOE OSTI2026

Scalable GPS Data Logging To Support Advanced Fleet Analysis

This highlight details the key takeaways from a project that utilized NLR's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline. National Laboratory of the Rockies researchers developed and demonstrated low-cost, open-source Arduino data loggers with 3D-printed cases that are compatible with global navigational systems and built with components available ubiquitously worldwide, enabling cost-effective collection and analysis of fleet operational data. Validated on an overseas transit bus fleet, NLR analysis showed that, with sufficient charging opportunities, 90% of observed duty cycles could be accomplished by electric buses with no modifications to operations.

33 ADVANCED PROPULSION SYSTEMS↗