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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Flight, Wind-Tunnel, and Computational Fluid Dynamics Comparison for Cranked Arrow Wing (F-16XL-1) at Subsonic and Transonic Speeds

Geometrical, flight, computational fluid dynamics (CFD), and wind-tunnel studies for the F-16XL-1 airplane are summarized over a wide range of test conditions. Details are as follows: (1) For geometry, the upper surface of the airplane and the numerical surface description compare reasonably well. (2) For flight, CFD, and wind-tunnel surface pressures, the comparisons are generally good at low angles of attack at both subsonic and transonic speeds, however, local differences are present. In addition, the shock location at transonic speeds from wind-tunnel pressure contours is near the aileron hinge line and generally is in correlative agreement with flight results. (3) For boundary layers, flight profiles were predicted reasonably well for attached flow and underneath the primary vortex but not for the secondary vortex. Flight data indicate the presence of an interaction of the secondary vortex system and the boundary layer and the boundary-layer measurements show the secondary vortex located more outboard than predicted. (4) Predicted and measured skin friction distributions showed qualitative agreement for a two vortex system. (5) Web-based data-extraction and computational-graphical tools have proven useful in expediting the preceding comparisons. (6) Data fusion has produced insightful results for a variety of visualization-based data sets.

John E Lamar↗
NASA NTRS2014

Modernization of the Cassini Ground System

The Cassini Spacecraft and its ground system have been operational for over 16 years. Modernization presents several challenges due to the personnel, processes, and tools already invested and embedded into the current ground system structure. Every mission's ground system has its own unique complexities and challenges, involving various organizational units. As any mission from its inception to its execution, schedules are always tight. This forces GDS engineers to implement a working ground system that is not necessarily fully optimized. Ground system challenges increase as technology evolves and cyber threats become more sophisticated. Cassini's main challenges were due to its ground system existing before many security requirements were levied on the multi-mission tools and networks. This caused a domino effect on Cassini GDS tools that relied on outdated technological features. In the aerospace industry reliable and established technology is preferred over innovative yet less proven technology. Loss of data for a spacecraft mission can be catastrophic; therefore, there is a reluctance to make changes and updates to the ground system. Nevertheless, all missions and associated teams face the need to modernize their processes and tools. Systems development methods from well-known system analysis and design principles can be applied to many missions' ground systems. Modernization should always be considered, but should be done in such a way that it does not affect flexibility nor interfere with established practices. Cassini has accomplished a secure and efficient ground data system through periodic updates. The obstacles faced while performing the modernization of the Cassini ground system will be outlined, as well as the advantages and challenges that were encountered.

Razo, Gus↗
NASA NTRS2014

Modernization of the Cassini Ground System

The Cassini Spacecraft and its ground system have been operational for over 16 years. Modernization presents several challenges due to the personnel, processes, and tools already invested and embedded into the current ground system structure. Every mission's ground system has its own unique complexities and challenges, involving various organizational units. As any mission from its inception to its execution, schedules are always tight. This forces GDS engineers to implement a working ground system that is not necessarily fully optimized. Ground system challenges increase as technology evolves and cyber threats become more sophisticated. Cassini's main challenges were due to its ground system existing before many security requirements were levied on the multi-mission tools and networks. This caused a domino effect on Cassini GDS tools that relied on outdated technological features. In the aerospace industry reliable and established technology is preferred over innovative yet less proven technology. Loss of data for a spacecraft mission can be catastrophic; therefore, there is a reluctance to make changes and updates to the ground system. Nevertheless, all missions and associated teams face the need to modernize their processes and tools. Systems development methods from well-known system analysis and design principles can be applied to many missions' ground systems. Modernization should always be considered, but should be done in such a way that it does not affect flexibility nor interfere with established practices. Cassini has accomplished a secure and efficient ground data system through periodic updates. The obstacles faced while performing the modernization of the Cassini ground system will be outlined, as well as the advantages and challenges that were encountered.

Razo, Gus↗
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 NTRS1981

Applications systems verification and transfer project. Volume 1: Operational applications of satellite snow cover observations: Executive summary

Both LANDSAT and NOAA satellite data were used in improving snowmelt runoff forecasts. When the satellite snow cover data were tested in both empirical seasonal runoff estimation and short term modeling approaches, a definite potential for reducing forecast error was evident. A cost benefit analysis run in conjunction with the snow mapping indicated a $36.5 million annual benefit accruing from a one percent improvement in forecast accuracy using the snow cover data for the western United States. The annual cost of employing the system would be $505,000. The snow mapping has proven that satellite snow cover data can be used to reduce snowmelt runoff forecast error in a cost effective manner once all operational satellite data are available within 72 hours after acquisition. Executive summaries of the individual snow mapping projects are presented.

Rango, A.↗
NASA NTRS2018

Developing a Standard for Earth Observation Data Preservation Content - A Path to Future Usability

For datasets to be usable, many pieces of information in addition to the data themselves are essential. During the active parts of the lifecycle of dataset generating projects, the needed information is usually accessible through individuals familiar with the various aspects of the projects. However, the utility of datasets tends to outlive the lives of projects, by several decades in many cases. Thus it is essential to capture all the relevant information about the datasets, data, metadata and associate knowledge that is sufficient to read, understand, interpret and reuse the datasets, while the projects are still active. The capture and preservation should be such that the data are usable when no consultation is available from the original project participants. Identification of specific categories of content through an international standard is beneficial to the user communities of the future, so that projects involving Earth observations and generating data products can consistently plan for preservation and future usability of the project outcomes. While there are existing standards that address archival and preservation in general, there are no existing international standards or specifications today to address what content should be preserved. The standard, ISO 19165-1, titled "Geographic Information - Preservation of digital data and metadata Part 1: Fundamentals" considers geographic information preservation in general. It acknowledges that "specific content items needed to preserve the full provenance and context of the data and associated metadata depend on the needs of the designated community and types of datasets (e.g., maps, remotely sensed data from satellites and airborne instruments, physical samples). Follow-up parts to this standard may be developed detailing content items appropriate to individual disciplines." NASA proposed an extension to this standard, titled "Geographic information -- Preservation of digital data and metadata -- Part 2: Content specifications for Earth observation data and derived digital products." The development of this extension is in progress with participation by an international team representing nine countries. The purpose of this paper is to introduce this standard and report on its status.

Remote Sensing; Data Systems; Open Data;↗
DOE OSTI2025

PDF Entity Annotation Tool (PEAT)

While different text mining approaches – including the use of Artificial Intelligence (AI) and other machine based methods - continue to expand at a rapid pace, the tools used by researchers to create the labeled datasets required for training, modeling, and evaluation remain rudimentary. Labeled datasets contain the target attributes the machine is going to learn; for example, training an algorithm to delineate between images of a car or truck would generally require a set of images with a quantitative description of the underlying features of each vehicle type. Development of labeled textual data that can be used to build natural language machine learning models for scientific literature is not currently integrated into existing manual workflows used by domain experts. Published literature is rich with important information, such as different types of embedded text, plots, and tables that can all be used as inputs to train ML/natural language processing (NLP) models, when extracted and prepared in machine readable formats. Currently, both normalized data extraction of use to domain experts and extraction to support development of ML/NLP models are labor intensive and cumbersome manual processes. Automatic extraction of data and information from formats such as PDFs that are optimized for layout and human readability, not machine readability. The PDF (Portable Document Format) Entity Annotation Tool (PEAT) was developed with the goal of allowing users to annotate publications within their current print format, while also allowing those annotations to be captured in a machine-readable format. One of the main issues with traditional annotation tools is that they require transforming the PDF into plain text to facilitate the annotation process. While doing so lessens the technical challenges of annotating data, the user loses all structure and provenance that was inherent in the underlying PDF. Also, textual data extraction from PDFs can be an error prone process. Challenges include identifying sequential blocks of text and a multitude of document formats (multiple columns, font encodings, etc.). As a result of these challenges, using existing tools for development of NLP/ML models directly from PDFs is difficult because the generated outputs are not interoperable. We created a system that allows annotations to be completed on the original PDF document structure, with no plain text extraction. The result is an application that allows for easier and more accurate annotations. In addition, by including a feature that grants the user the ability to easily create a schema, we have developed a system that can be used to annotate text for different domain-centric schemas of relevance to subject matter experts. Different knowledge domains require distinct schemas and annotation tags to support machine learning.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

NASA information systems commonality and convergence

Efforts to identify high payback functions performed by the Office of Space Science Applications (OSSA) data systems package existing operationally proven implementations as system building blocks and foster their use in the OSSA environment. An overview is given of the current state of OSSA data systems and the major challenges facing system developers over the next five years. Current trends in system commonality are discussed, and development is examined in the context of system design. Central system engineering approaches to solving the commonality and interoperability challenges are described. Efforts to package three diverse building blocks and to foster their reuse are documented.

Handley, Thomas H., Jr.↗
NASA NTRSDate not supplied

Open-Source Science-led Development of the Atmosphere Observing System (AOS) Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission 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 AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS 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 AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David Giles↗
NASA NTRSDate not supplied

Open-Source Science-led Development of the AOS Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission 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 AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS 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 AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David M. Giles↗
DOE OSTI2025

Active multi-mode data analysis to improve fault diagnosis in AHUs

Faults in heating, ventilation and air conditioning systems can lead to increased energy consumption, occupant comfort issues, and reduced equipment lifetime. Commercial fault detection and diagnosis (FDD) tools has been increasingly deployed in U.S. commercial buildings. While they are helping to achieve energy efficiency and operational reliability, there remain gaps in their fault diagnostic capabilities. The diagnostic results often contain multiple distinct candidate root causes (CRCs) or offer no insight into CRCs. This study developed a novel active rule-based multi-mode data analysis method to enhance diagnostic resolution by applying proven rule sets and additional new rules to data from multiple known operational modes. The proposed method was demonstrated using enhanced air handling unit performance assessment rule sets and validated with the simulated data of two air handling units. New metrics, namely, reduced number of CRCs and improvement ratio, were developed to quantify the improvement of fault diagnostic resolution. The validation results showed that the proposed method effectively reduced the number of CRCs in contrast to analyzing data solely for a single mode of operation. It achieved a median improvement ratio of 80% in 19 test cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1983

Spaceborne SAR and sea ice

A number of remote sensing systems deployed in satellites to view the Earth which are successful in gathering data on the behavior of the world's snow and ice covers are described. Considering sea ice which covers over 10% of the world ocean, systems that have proven capable to collect useful data include those operating in the visible, near-infrared, infrared, and microwave frequency ranges. The microwave systems have the essential advantage in observing the ice under all weather and lighting conditions. Without this capability data are lost during the long polar night and during times of storm passage, periods when ice activity can be intense. The margins of the ice pack, a region of particular interest, is shrouded in cloud between 80 and 90% of the time.

Weeks, W. F.↗
NASA NTRS2023

Constructing a Raman Spectroscopy System

The project aims to understand how Raman spectroscopy works by constructing a system based on existing concepts of the technique and utilizing NASA’s available tools and software to analyze the collected data. Once the data is successfully interpreted and proven, other improvements to the assembled system will then be explored. Part of the paper goes through several phases of construction of the system and improvements made. Nevertheless, the data obtained and the results were unsatisfactory as they need to be further analyzed for accuracy. The ultimate ambition was to be able to assist NASA with its objective of implementing a remote and compact Raman spectroscopy system on a rover for future planetary surface characterization such as Mars and lunar surfaces via a Raman spectroscopy system that the agency’s Senior Engineer, Dr. M. Nurul Abedin, has been working on since the early 2000s [2,3,4].

Jake Nguyen↗
NASA NTRS2008

Transformation of OODT CAS to Perform Larger Tasks

A computer program denoted OODT CAS has been transformed to enable performance of larger tasks that involve greatly increased data volumes and increasingly intensive processing of data on heterogeneous, geographically dispersed computers. Prior to the transformation, OODT CAS (also alternatively denoted, simply, 'CAS') [wherein 'OODT' signifies 'Object-Oriented Data Technology' and 'CAS' signifies 'Catalog and Archive Service'] was a proven software component used to manage scientific data from spaceflight missions. In the transformation, CAS was split into two separate components representing its canonical capabilities: file management and workflow management. In addition, CAS was augmented by addition of a resource-management component. This third component enables CAS to manage heterogeneous computing by use of diverse resources, including high-performance clusters of computers, commodity computing hardware, and grid computing infrastructures. CAS is now more easily maintainable, evolvable, and reusable. These components can be used separately or, taking advantage of synergies, can be used together. Other elements of the transformation included addition of a separate Web presentation layer that supports distribution of data products via Really Simple Syndication (RSS) feeds, and provision for full Resource Description Framework (RDF) exports of metadata.

Mattmann, Chris↗
NASA NTRS2002

The Design and Use of Calorimeters For Characterization of High-Enthalpy Flows in Arc-Heated Test Facilities

High-enthalpy, arc-heated flows used for aerothermal testing present a challenging environment for flow characterization. This paper describes the design and use of cooled dwell probes used for heat-transfer and pressure characterization of the NASA and United States Department of Defense (DoD) arc facilities located at Moffett Field, CA, and Arnold Air Force Base, TN. Dwell calorimeters designed, fabricated, and tested by Thermal Technologies, Inc. (TTI) in the NASA IHF and the USAF H1 and H2 arc test facilities provide heat flux and pressure data with excellent repeatability. These calorimeters use standard Gardon calorimeter gages and pressure ports with unique cooling systems enabling them to withstand the severe arc-heated environments for durations sufficient for acquisition of steady-state data. The TTI probes have proven very robust in the extreme aerothermal environments of these facilities. This paper provides an overview of calorimeter instruments typically used in arc facilities, discusses design features of the TTI dwell probes, presents selected data acquired by the TTI calorimeters, and provides comparisons with data acquired from using measurement techniques.

D Mark Smith↗
NASA NTRS1998

A Modeling Approach to Global Land Surface Monitoring with Low Resolution Satellite Imaging

The effects of changing land use/land cover on global climate and ecosystems due to greenhouse gas emissions and changing energy and nutrient exchange rates are being addressed by federal programs such as NASA's Mission to Planet Earth (MTPE) and by international efforts such as the International Geosphere-Biosphere Program (IGBP). The quantification of these effects depends on accurate estimates of the global extent of critical land cover types such as fire scars in tropical savannas and ponds in Arctic tundra. To address the requirement for accurate areal estimates, methods for producing regional to global maps with satellite imagery are being developed. The only practical way to produce maps over large regions of the globe is with data of coarse spatial resolution, such as Advanced Very High Resolution Radiometer (AVHRR) weather satellite imagery at 1.1 km resolution or European Remote-Sensing Satellite (ERS) radar imagery at 100 m resolution. The accuracy of pixel counts as areal estimates is in doubt, especially for highly fragmented cover types such as fire scars and ponds. Efforts to improve areal estimates from coarse resolution maps have involved regression of apparent area from coarse data versus that from fine resolution in sample areas, but it has proven difficult to acquire sufficient fine scale data to develop the regression. A method for computing accurate estimates from coarse resolution maps using little or no fine data is therefore needed.

Hlavka, Christine A.↗