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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 NTRS2020

Accretion-Driven Sources in Spatially Resolved Lyα Emitters

Lyα emission is a standard tracer of starburst galaxies at high redshift. However, a number of local Lyα emitters (LAEs) are X-ray sources, suggesting a possible origin of Lyα photons other than young, hot stars, and which may be active at much later ages relative to the parent starburst. Resolved, nearby LAEs offer the opportunity to discriminate between diffuse X-ray emission arising from supernova-heated gas, high-mass X-ray binaries (HMXBs), or low-luminosity active galactic nuclei (LLAGN). We examine archival X-ray imaging from Chandra and XMM-Newton for 11 galaxies with spatially resolved Lyα imaging to determine the luminosity, morphology, and spectral hardness of the X-ray sources. The data are consistent with 9 of the 12, bright Lyα sources being driven by luminous, >1040 erg s-1 X-ray sources. Half of the eight Chandra sources are unresolved. The data suggest that nuclear activity, whether from LLAGN or nuclear starbursts, may play an important role in Lyα emission. Our results also suggest a significant link between Lyα emission and HMXBs, ultraluminous X-ray sources, and/or LLAGN, which would imply that Lyα may be generated over timescales 1–2 orders of magnitude longer than produced by photoionization from OB stars. This highlights a critical need to quantify the relative contributions of different sources across cosmic time, to interpret Lyα observations and the resulting properties of distant galaxies.

Benjamin Dittenber↗
NASA NTRS2001

EGIS - An Environmental GIS Developed for NASA Field Center Applications

As the principal center for Environmental Geographic Information Systems (EGIS), the John C. Stennis Space Center (SSC), located in Hancock County, Mississippi, has been assigned technical support requirements to design and to implement a basic EGIS data base for all NASA Field Centers. The intent of this Phase I effort is to produce a baseline EGIS data base incorporating newly available remotely sensed data as well as existing environmental data. A example application of the use of the data base at Stennis Space Center will be to illustrate baseline environmental conditions for consideration with proposed propulsion test stand development and operation. To effectively answer questions related to environmental issues at each center, organization of the data layers and sources will include the following categories: Cadastral/Geodetic; Geopolitical; Hydrography; Infrastructure; Physical Geography; Socioeconomic; Remote Sensing Imagery; Associated Metadata. As part of a Phase II effort, site-specific data and applications will be implemented and added to the data base at each Field Center. This poster illustrates the framework of the design and implementation of a basic EGIS data base. Shown are example data sources, hardware and software, and data base delivery and installation. The poster also depicts future recommendations for a centrally located server to house each of the NASA Field Center data bases. The server will allow real-time data base updates with additional layers and models for each center. Expansion of the EGIS data base will continue to grow as site-specific applications are developed addressing the ongoing evolution of environmental concerns at all NASA Field Centers.

Smoot, James↗
NASA NTRS1997

Long-term variability in bright hard X-ray sources: 5+ years of BATSE data

The operation of the Compton Gamma Ray Observatory (CGRO)/burst and transient source experiment (BATSE) continues to provide data for inclusion into a data base for the analysis of long term variability in bright, hard X-ray sources. The all-sky capability of BATSE provides up to 30 flux measurements/day for each source. The long baseline and the various rising and setting occultation flux measurements allow searches for periodic and quasi-periodic signals with periods of between several hours to hundreds of days to be conducted. The preliminary results from an analysis of the hard X-ray variability in 24 of the brightest BATSE sources are presented. Power density spectra are computed for each source and profiles are presented of the hard X-ray orbital modulations in some X-ray binaries, together with amplitude modulations and variations in outburst durations and intensities in recurrent X-ray transients.

Robinson, C. R.↗
NASA NTRSDate not supplied

Breaking Barriers: Integrating Geo-Leo Aerosol Data with an Open-Source Approach

The scientific community is still examining the novel data from geostationary satellite observations and evaluating methods for effectively fusing the polar observations with various spatial and temporal resolutions. However, the merged data will present a significant ""Big Data"" challenge, including processing, storage, data discoverability, accessibility, and migration within cloud computing environments. We have developed an open-source package to fuse aerosol optical depths (AOD) products from six satellite sensors in the past four years (2019~2023), and this presentation will update our recent progress. Using this Python-based package, we produced a level 3 global (AOD) product in a quarter-degree spatial resolution every half-hour, fusing the Level 2 AOD data with the Dark Target aerosol retrieval algorithm from six satellites: three geostationary (GOES-16/17 and Himawari-8) with high temporal resolution, and three polar orbiting (TERRA/MODIS, AQUA/MODIS, and SNPP-VIIRS) with global coverage. By integrating these observations, the diurnal cycle of global AOD in this fused product can be characterized at local, regional, and global scales. Furthermore, we are committed to openness and transparency by providing our package and its associated functionalities as open-source. Our dedication to adhering to the FAIR, CARE, and TRUST principles ensures that our users can rely on the integrity and ethical standards of our work. For instance of Interoperability, this package fuses remote sensing products on demand into desired temporal and spatial domains. It can be run in a central processing unit (CPU) or a Graphics processing unit (GPU) mode. This package will empower researchers and practitioners to use satellite and sensor data efficiently in various applications and research.

Xiaohua Pan↗
NASA NTRS1983

Satellite freeze forecast system: Executive summary

A satellite-based temperature monitoring and prediction system consisting of a computer controlled acquisition, processing, and display system and the ten automated weather stations called by that computer was developed and transferred to the national weather service. This satellite freeze forecasting system (SFFS) acquires satellite data from either one of two sources, surface data from 10 sites, displays the observed data in the form of color-coded thermal maps and in tables of automated weather station temperatures, computes predicted thermal maps when requested and displays such maps either automatically or manually, archives the data acquired, and makes comparisons with historical data. Except for the last function, SFFS handles these tasks in a highly automated fashion if the user so directs. The predicted thermal maps are the result of two models, one a physical energy budget of the soil and atmosphere interface and the other a statistical relationship between the sites at which the physical model predicts temperatures and each of the pixels of the satellite thermal map.

Martsolf, J. D.↗
NASA NTRS1983

Processing system

To implement the analysis techniques and to provide end-to-end processing, a system was designed with the following capabilities: receive and catalog data from many sources; organize the data on mass storage for rapid access; edit for reasonableness; create new data sets by sorting on parameter, averaging and merging; provide statistical analysis and display tools; and distribute data on demand. Consideration was given to developing a flexible system that could meet immediate workshop needs and respond to future requirements. System architecture and data set details implemented are discussed.

Hilland, J. E.↗
NASA NTRS1984

ACARS wind measurements - An intercomparison with radiosonde, cloud motion and VAS thermally derived winds

Statistical comparisons between winds measured by ACARS and winds obtained from radiosondes, geostationary satellite image cloud motions, and VAS are presented. Observations from three separate comparisons reveal over 60 percent of wind vector magnitude differences are within 9 m/s, and 70 percent of the directional differences are within 15 deg. The comparisons indicate that the ACARS system provides an independent source of wind data that complements other sources of wind data for constructing composite wind field analyses.

Lord, R. J.↗
NASA NTRS1984

Designing systems to satisfy their users - The coming changes in aviation weather and the development of a central weather processor

Attention is given to the development history of the Central Weather Processor (CWP) program of the Federal Aviation Administration. The CWP will interface with high speed digital communications links, accept data and information products from new sources, generate data processing products, and provide meteorologists with the capability to automate data retrieval and dissemination. The CWP's users are operational (air traffic controllers, meteorologists and pilots), institutional (logistics, maintenance, testing and evaluation personnel), and administrative.

Bush, M. W.↗
NASA NTRS1989

Visualizing large data sets in the earth sciences

The authors describe the capabilities of McIDAS, an interactive visualization system that is vastly increasing the ability of earth scientists to manage and analyze data from remote sensing instruments and numerical simulation models. McIDAS provides animated three-dimensionsal images and highly interactive displays. The software can manage, analyze, and visualize large data sets that span many physical variables (such as temperature, pressure, humidity, and wind speed), as well as time and three spatial dimensions. The McIDAS system manages data from at least 100 different sources. The data management tools consist of data structures for storing different data types in files, libraries of routines for accessing these data structures, system commands for performing housekeeping functions on the data files, and reformatting programs for converting external data to the system's data structures. The McIDAS tools for three-dimensional visualization of meteorological data run on an IBM mainframe and can load up to 128-frame animation sequences into the workstations. A highly interactive version of the system can provide an interactive window into data sets containing tens of millions of points produced by numerical models and remote sensing instruments. The visualizations are being used for teaching as well as by scientists.

Hibbard, William↗
NASA NTRS1990

Applications of ISES for instrument science

It is often the case that some instruments being used for geophysical measurements cannot measure some parameters that are important for processing the data obtained using the instrument. However, the parameters of interest may be measured by other instruments and these data made available to the operators of the first instrument. Processing the data immediately after it is acquired is useful in directing the operation of the same or different instrument or in providing a quick look data set to users on the ground. The four applications which are considered are: the decision to acquire data due to some important occurrence detected by Eos instruments; the decision not to acquire data at a scheduled time and/or location; the decision to acquire additional data to improve data quality; and combining data from several sources to enhance data quality. General examples are presented, which may or may not apply directly to Eos instruments on the various platforms.

Grant, William B.↗
NASA NTRS1993

An analysis of the Voyager 2 Ultraviolet Spectrometer occultation data at Uranus - Inferring heat sources and model atmospheres

Heat source information is derived here from the Voyager 2 Ultraviolet Spectrometer occultation data of Uranus. Analytic functions for the local heat dependence on altitude are used to obtain a temperature profile by solving the heat equation. The stellar entrance and exit occultation and a solar occultation are used to infer the thermal and density structure of the atmosphere. The least squares fit solution to the solar occultation data gives one source located at 1.8 x 10 exp -5 microbar with a strength of 0.056 +/- 0.01 erg/sq cm/s. Latitudinal temperature gradients are obtained.

Stevens, Michael H.↗
NASA NTRS2002

The NASA John C. Stennis Environmental Geographic Information System

The Environmental Geographic Information System (EGIS) at Stennis Space Center (SSC) covers four counties in Mississippi and four parishes in Louisiana. The EGIS includes 410 data layers including vector and raster data from various public and private sources. These data layers provide information on natural and cultural features. SSC initially used the EGIS to: 1) Monitor on and off-site impacts of propulsion testing; 2) Classify land cover at SSC to predict the impacts of future programs. This viewgraph presentation provides an overview of ongoing projects and future applications for the EGIS.

Cohan, Tyrus↗
NASA NTRS2004

Autonomous Multi-Sensor Coordination: The Science Goal Monitor

Many dramatic earth phenomena are dynamic and coupled. In order to fully understand them, we need to obtain timely coordinated multi-sensor observations from widely dispersed instruments. Such a dynamic observing system must include the ability to Schedule flexibly and react autonomously to sciencehser driven events; Understand higher-level goals of a sciencehser defined campaign; Coordinate various space-based and ground-based resources/sensors effectively and efficiently to achieve goals. In order to capture transient events, such a 'sensor web' system must have an automated reactive capability built into its scientific operations. To do this, we must overcome a number of challenges inherent in infusing autonomy. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe dynamic phenomena. The SGM system enables users to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of data to identify occurrences of the key events previously specified by the scientisther. When an event occurs, the system autonomously coordinates the execution of the users' desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems' Aqua/Terra spacecrafts' MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM was used to investigate forest fires, floods and volcanic eruptions. We are now identifying new Earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Koratkar, Anuradha↗
NASA NTRS2004

Autonomous Multi-sensor Coordination: The Science Goal Monitor

Next-generation science and exploration systems will employ new observation strategies that will use multiple sensors in a dynamic environment to provide high quality monitoring, self-consistent analyses and informed decision making. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing of earth phenomenon. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe the dynamic phenomena. The SGM system enables users to specify events of interest and how to react when an event is detected. The system monitors streams of data to identify occurrences of the key events previously specified by the scientist/user. When an event occurs, the system autonomously coordinates the execution of the users desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems Aqua/Terra spacecrafts MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM is being used to investigate forest fires, floods and volcanic eruptions. We are now identifying new earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Koratkar, Anuradha↗
NASA NTRS2009

Event Driven Messaging with Role-Based Subscriptions

Event Driven Messaging with Role-Based Subscriptions (EDM-RBS) is a framework integrated into the Service Management Database (SMDB) to allow for role-based and subscription-based delivery of synchronous and asynchronous messages over JMS (Java Messaging Service), SMTP (Simple Mail Transfer Protocol), or SMS (Short Messaging Service). This allows for 24/7 operation with users in all parts of the world. The software classifies messages by triggering data type, application source, owner of data triggering event (mission), classification, sub-classification and various other secondary classifying tags. Messages are routed to applications or users based on subscription rules using a combination of the above message attributes. This program provides a framework for identifying connected users and their applications for targeted delivery of messages over JMS to the client applications the user is logged into. EDMRBS provides the ability to send notifications over e-mail or pager rather than having to rely on a live human to do it. It is implemented as an Oracle application that uses Oracle relational database management system intrinsic functions. It is configurable to use Oracle AQ JMS API or an external JMS provider for messaging. It fully integrates into the event-logging framework of SMDB (Subnet Management Database).

Bui, Tung↗
NASA NTRS2007

Automated Recognition of 3D Features in GPIR Images

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Park, Han↗
NASA NTRS2010

Comparison of Test Stand and Helicopter Oil Cooler Bearing Condition Indicators

The focus of this paper was to compare the performance of HUMS condition indicators (CI) when detecting a bearing fault in a test stand or on a helicopter. This study compared data from two sources: first, CI data collected from accelerometers installed on two UH-60 Black Hawk helicopters when oil cooler bearing faults occurred, along with data from helicopters with no bearing faults; and second, CI data that was collected from ten cooler bearings, healthy and faulted, that were removed from fielded helicopters and installed in a test stand. A method using Receiver Operating Characteristic (ROC) curves to compare CI performance was demonstrated. Results indicated the bearing energy CI responded differently for the helicopter and the test stand. Future research is required if test stand data is to be used validate condition indicator performance on a helicopter.

Dempsey, Paula J.↗
NASA NTRS2017

Biosensor Integration Development ExMC/Canadian Space Agency Collaboration

In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development.

Vital signs↗