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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Causes of Long-Term Drought in the United States Great Plains

The United States Great Plains (USGP) experienced a number of multi-year droughts during the last century, most notably the droughts of the 1930s and 1950s. This study examines the causes of such droughts using ensembles of long term (1930-1999) simulations carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTs). The results show that the model produces long-term (multi-year) variations in the USGP precipitation that are similar to those observed. A correlative analysis suggests that the ensemble mean low frequency (time scales longer than about 6 years) rainfall variations in the USGP are linked to a pan-Pacific pattern of SST variability that is the leading empirical orthogonal function (EOF) in the low frequency SST data. The link between the SST and the Great Plains precipitation is confirmed in idealized AGCM simulations, in which the model is forced by the 2 polarities of the pan-Pacific SST pattern. The idealized simulations further show that it is primarily the tropical part of the SST anomalies that influence the USGP. As such, the USGP tend to have above normal precipitation when the tropical Pacific SSTs are above normal, while there is a tendency for drought when the tropical SSTs are cold. The upper tropospheric response to the pan-Pacific SST EOF shows a global-scale pattern with a strong wave response in the Pacific and a substantial zonally-symmetric component in which USGP pluvial (drought) conditions are associated with reduced (enhanced) heights throughout the extra-tropics. The potential predictability of rainfall in the USGP associated with SSTs is rather modest, with on average about 1/3 of the total low frequency rainfall variance forced by SST anomalies. Further idealized experiments with climatological SST, suggest that the remaining low frequency variance in the USGP precipitation is the result of interactions with soil moisture. In particular, simulations with soil moisture feedback show a six-fold increase in the variance in annual USGP precipitation compared with simulations in which the soil feedback is excluded. In addition to increasing variance, the interactions with the soil introduce year-to-year memory in the hydrological cycle that is consistent with a red noise process, in which the low frequencies in the deep soil are the result of integrating a net forcing (precipitation-evaporation-runoff) that is white noise on interannual time scales. As such, the role of low frequency SST variability is to introduce a bias to the net forcing on the soil moisture that drives the random process preferentially to either wet or dry conditions.

Schubert, Siegfried D.↗
NASA NTRS1999

Phased Array Transmit Antenna for a Satellite

Active phased array antennas with electronically scanned beams offer advantages over high gain parabolic dish antennas currently used on spacecraft. Benefits include the elimination of deployable structures, no moving parts, and no torque disturbances that moving antennas impart to the spacecraft. The latter results in the conservation of spacecraft power, and the ability to take precision optical data while transmitting data. Such an antenna has been built under a contract from NASA Goddard Space Flight Center for the New Millennium Program EO- 1 satellite where it will act as the primary highspeed scientific data communication link. The antenna operates at X-band, has an integral controller and power conditioner, communicates with the spacecraft over a 1773 optical data bus, and is space qualified for low earth orbit (705 Km altitude). The nominal mission length is one year, and the operational requirement is for one 10 minute transmission a day over Spitsbergen, Norway. Details of the antenna and its performance will be described in the following paper.

Huggins, R. W.↗
NASA NTRS2011

STRS SpaceWire FPGA Module

An FPGA module leverages the previous work from Goddard Space Flight Center (GSFC) relating to NASA s Space Telecommunications Radio System (STRS) project. The STRS SpaceWire FPGA Module is written in the Verilog Register Transfer Level (RTL) language, and it encapsulates an unmodified GSFC core (which is written in VHDL). The module has the necessary inputs/outputs (I/Os) and parameters to integrate seamlessly with the SPARC I/O FPGA Interface module (also developed for the STRS operating environment, OE). Software running on the SPARC processor can access the configuration and status registers within the SpaceWire module. This allows software to control and monitor the SpaceWire functions, but it is also used to give software direct access to what is transmitted and received through the link. SpaceWire data characters can be sent/received through the software interface, as well as through the dedicated interface on the GSFC core. Similarly, SpaceWire time codes can be sent/received through the software interface or through a dedicated interface on the core. This innovation is designed for plug-and-play integration in the STRS OE. The SpaceWire module simplifies the interfaces to the GSFC core, and synchronizes all I/O to a single clock. An interrupt output (with optional masking) identifies time-sensitive events within the module. Test modes were added to allow internal loopback of the SpaceWire link and internal loopback of the client-side data interface.

Lux, James P.↗
NASA NTRS2019

Cognitive Communications for NASA Space Systems

The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset scheduling. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.

Chelmins, David↗
NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repairs Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, it will be necessary to understand how crew repair and maintenance timelines are impacted by mission operations and technology changes. Past work has been done using historical ISS data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available data sets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat, and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA International Space Station (ISS) maintenance and crew time data are logged into two central databases, the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS) respectively. Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. MDC provides a detailed catalog of failure events and an overview of the failure’s required maintenance and OPTimIS provides a description of crew activities and crew time durations dedicated to maintenance. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair times for each failure event. Data is also classified by the outcome of each repair event, whether the failed component was replaced or whether it was repaired in place. The entire maintenance activity dataset is then categorized based on the class of failed component to allow for a statistically significant sample size for each class and to provide accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time To Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗
NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repair Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, understanding how crew repair and maintenance timelines are impacted by mission operations and technology changes is vital for future mission planning. Past work has been done using historical International Space Station (ISS) data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available datasets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat (SH), and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA ISS maintenance and crew time data are logged into two central databases: the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS). Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair time for each failure and repair event. The entire maintenance activity dataset is then categorized based on the class of failed component to ensure a significant sample size for each class and accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time to Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. The authors applied these modeling methods to a case study of a crewed mission to the planned SH and produced expected corrective maintenance crew time distributions. The results produced an expected corrective maintenance crew time at over 24 hours per mission, and a maintenance crew time distribution that reflects the importance of planning for sufficient maintenance requirements each mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗
NASA NTRS1999

An Overview of Future NASA Missions, Concepts, and Technologies Related to Imaging of the World's Land Areas

In the near term NASA is entering into the peak activity period of the Earth Observing System (EOS). The EOS AM-1 /"Terra" spacecraft is nearing launch and operation to be followed soon by the New Millennium Program (NMP) Earth Observing (EO-1) mission. Other missions related to land imaging and studies include EOS PM-1 mission, the Earth System Sciences Program (ESSP) Vegetation Canopy Lidar (VCL) mission, the EOS/IceSat mission. These missions involve clear advances in technologies and observational capability including improvements in multispectral imaging and other observing strategies, for example, "formation flying". Plans are underway to define the next era of EOS missions, commonly called "EOS Follow-on" or EOS II. The programmatic planning includes concepts that represent advances over the present Landsat-7 mission that concomitantly recognize the advances being made in land imaging within the private sector. The National Polar Orbiting Environmental Satellite Series (NPOESS) Preparatory Project (NPP) is an effort that will help to transition EOS medium resolution (herein meaning spatial resolutions near 500 meters), multispectral measurement capabilities such as represented by the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) into the NPOESS operational series of satellites. Developments in Synthetic Aperture Radar (SAR) and passive microwave land observing capabilities are also proceeding. Beyond these efforts the Earth Science Enterprise Technology Strategy is embarking efforts to advance technologies in several basic areas: instruments, flight systems and operational capability, and information systems. In the case of instruments architectures will be examined that offer significant reductions in mass, volume, power and observational flexibility. For flight systems and operational capability, formation flying including calibration and data fusion, systems operation autonomy, and mechanical and electronic innovations that can reduce spacecraft and subsystem resource requirements. The efforts in information systems will include better approaches for linking multiple data sets, extracting and visualizing information, and improvements in collecting, compressing, transmitting, processing, distributing and archiving data from multiple platforms. Overall concepts such as sensor webs, constellations of observing systems, and rapid and tailored data availability and delivery to multiple users comprise and notions Earth Science Vision for the future.

Salomonson, Vincent V.↗
NASA NTRS1986

Relative performance of 8.5-GHz and 32-GHz telemetry links on the basis of total data return per pass

The performance of X-band (8.5-GHz) and 32-GHz telemetry links is compared on the basis of the total data return per DSN station pass. Differences in spacecraft transmitter efficiency, transmit circuit loss, and transmitting antenna area efficiency and pointing loss are not considered in these calculations. Thus, the performance differentials calculated in this memo are those produced by a DSN 70-m station antenna gain and clear weather receiving system noise temperature and by weather. These calculations show that, assuming mechanical compensation of the DSN 70-m antenna for 32-GHz operation, a performance advantage for 32 GHz over X-band of 8.2 dB can be achieved for at least one DSN station location. Even if only Canberra and Madrid are used, a performance advantage of 7.7 dB can be obtained for at least one DSN station location. A system using a multiple beam feed (electronic compensation) should achieve similar results.

Koerner, M. A.↗
NASA NTRS1992

A system for verifying models and classification maps by extraction of information from a variety of data sources

Recent updates to a geographical information system (GIS) called VICAR (Video Image Communication and Retrieval)/IBIS are described. The system is designed to handle data from many different formats (vector, raster, tabular) and many different sources (models, radar images, ground truth surveys, optical images). All the data are referenced to a single georeference plane, and average or typical values for parameters defined within a polygonal region are stored in a tabular file, called an info file. The info file format allows tracking of data in time, maintenance of links between component data sets and the georeference image, conversion of pixel values to `actual' values (e.g., radar cross-section, luminance, temperature), graph plotting, data manipulation, generation of training vectors for classification algorithms, and comparison between actual measurements and model predictions (with ground truth data as input).

Norikane, L.↗
NASA NTRS2011

Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Projects Data and Services at the GES DISC

NASA's Earth Science Program is dedicated to advancing Earth remote sensing and pioneering the scientific use of satellite measurements to improve human understanding of our home planet. Through the MEaSUREs Program, NASA is continuing its commitment to expand understanding of the Earth system using consistent data records. Emphasis is on linking together multiple data sources to form coherent time-series, and facilitating the use of extensive data in the development of comprehensive Earth system models. A primary focus of the MEaSUREs Program is the creation of Earth System Data Records (ESDRs). An ESDR is defined as a unified and coherent set of observations of a given parameter of the Earth system, which is optimized to meet specific requirements for addressing science questions. These records are critical for understanding Earth System processes; for the assessment of variability, long-term trends, and change in the Earth System; and for providing input and validation means to modeling efforts. Seven MEaSUREs projects will be archived and distributed through services at the Goddard Earth Sciences Data and Information Services Center (GES DISC).

Vollmer, Bruce E.↗
NASA NTRS2015

Data Recipes: Toward Creating How-To Knowledge Base for Earth Science Data

Both the diversity and volume of Earth science data from satellites and numerical models are growing dramatically, due to an increasing population of measured physical parameters, and also an increasing variety of spatial and temporal resolutions for many data products. To further complicate matters, Earth science data delivered to data archive centers are commonly found in different formats and structures. NASA data centers, managed by the Earth Observing System Data and Information System (EOSDIS), have developed a rich and diverse set of data services and tools with features intended to simplify finding, downloading, and working with these data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data due to varying levels of familiarity with data services, tools, and or formats. The data recipe project at Goddard Earth Science Data and Information Services Center (GES DISC) was initiated in late 2012 for enhancing user support. A data recipe is a How-To online explanatory document, with step-by-step instructions and examples of accessing and working with real data (http:disc.sci.gsfc.nasa.govrecipes). The current suite of recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant, even though the data recipe topics are still limited. An Earth Science Data System Working Group (ESDSWG) for data recipes was established in the spring of 2014, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group is working on an inventory and analysis of existing data recipes and tutorials, and will provide guidelines and recommendation for writing and grouping data recipes, and for cross linking recipes to data products. This presentation gives an overview of the data recipe activites at GES DISC and ESDSWG. We are seeking requirements and input from a broader data user community to establish a strong knowledge base for Earth science data research and application implementations.

data recipe↗
NASA NTRS1970

The role of remotely sensed and relayed data in the Delaware River Basin

A discussion is presented of the planned integration of the existing Delaware River Basin water quality monitoring and data processing systems with a data relay experiment proposed for the Earth Resources Technology Satellite (ERTS)-A, which will be launched in 1972. The experiment is designed to use ERTS-A as a data relay link for a maximum of 20 hydrologic stations in the basin, including streamgaging, reservoir level, ground water level,and water quality monitoring stations. This experiment has the potential for reducing the timelag between data collection and dissemination to less than 12 hours. At present there is a significant timelag between the time when the data are recorded at a monitoring site and the water resources agencies receive the data. The timelag exists because most of these instruments operate in remote locations without telementry, and the data records are removed manually, generally at a weekly frequency. For most water quality monitoring, the data do not reach water resources agencies for a period of 2 weeks to 2 months.

Paulson, R. W.↗
NASA NTRS2000

Observations on Rotating Cavitation and Cavitation Surge from the Development of the Fastrac Engine Turbopump

Observations regarding rotating cavitation and cavitation surge experienced during the development of the Fastrac engine turbopump are discussed. Detailed observations acquired from the analysis of both water flow and liquid oxygen test data are offered in this paper. Scaling and general comparison of rotating cavitation between water flow and liquid oxygen testing are discussed. Complex data features linking the localized rotating cavitation mechanism of the inducer to system surge components are described in detail. Finally a description of a lumped-parameter hydraulic system model developed to better understand observed data is given.

Zoladz, Thomas F.↗
NASA NTRS2006

Controlled Vocabularies Boost International Participation and Normalization of Searches

The Global Change Master Directory's (GCMD) science staff set out to document Earth science data and provide a mechanism for it's discovery in fulfillment of a commitment to NASA's Earth Science progam and to the Committee on Earth Observation Satellites' (CEOS) International Directory Network (IDN.) At the time, whether to offer a controlled vocabulary search or a free-text search was resolved with a decision to support both. The feedback from the user community indicated that being asked to independently determine the appropriate 'English" words through a free-text search would be very difficult. The preference was to be 'prompted' for relevant keywords through the use of a hierarchy of well-designed science keywords. The controlled keywords serve to 'normalize' the search through knowledgeable input by metadata providers. Earth science keyword taxonomies were developed, rules for additions, deletions, and modifications were created. Secondary sets of controlled vocabularies for related descriptors such as projects, data centers, instruments, platforms, related data set link types, and locations, along with free-text searches assist users in further refining their search results. Through this robust 'search and refine' capability in the GCMD users are directed to the data and services they seek. The next step in guiding users more directly to the resources they desire is to build a 'reasoning' capability for search through the use of ontologies. Incorporating twelve sets of Earth science keyword taxonomies has boosted the GCMD S ability to help users define and more directly retrieve data of choice.

Olsen, Lola M.↗
NASA NTRS2001

Overview of Rotating Cavitation and Cavitation Surge in the Fastrac Engine LOX Turbopump

Observations regarding rotating cavitation and cavitation surge experienced during the development of the Fastrac 60 Klbf engine turbopump are discussed. Detailed observations from the analysis of both water flow and liquid oxygen test data are offered. Scaling and general comparison of rotating cavitation between water flow and liquid oxygen testing are discussed. Complex data features linking the localized rotating cavitation mechanism of the inducer to system surge components are described in detail. Finally a description of a simple lumped-parameter hydraulic system model developed to better understand observed data is given.

Zoladz, Thomas↗
NASA NTRS2010

Updates of Land Surface and Air Quality Products in NASA MAIRS and NEESPI Data Portals

Following successful support of the Northern Eurasia Earth Sciences Partner Initiative (NEESPI) project with NASA satellite remote sensing data, from Spring 2009 the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has been working on collecting more satellite and model data to support the Monsoon Asia Integrated Regional Study (MAIRS) project. The established data management and service infrastructure developed for NEESPI has been used and improved for MAIRS support.Data search, subsetting, and download functions are available through a single system. A customized Giovanni system has been created for MAIRS.The Web-based on line data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) allows scientists to explore, quickly analyze, and download data easily without learning the original data structure and format. Giovanni MAIRS includes satellite observations from multiple sensors and model output from the NASA Global Land Data Assimilation System (GLDAS), and from the NASA atmospheric reanalysis project, MERRA. Currently, we are working on processing and integrating higher resolution land data in to Giovanni, such as vegetation index, land surface temperature, and active fire at 5km or 1km from the standard MODIS products. For data that are not archived at the GESDISC,a product metadata portal is under development to serve as a gateway for providing product level information and data access links, which include both satellite, model products and ground-based measurements information collected from MAIRS scientists.Due to the large overlap of geographic coverage and many similar scientific interests of NEESPI and MAIRS, these data and tools will serve both projects.

Shen, Suhung↗