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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

An investigation of the marine boundary layer during cold air outbreak

Methods for use in the remote estimation of ocean surface sensible and latent heat fluxes were developed and evaluated. Three different techniques were developed for determining these fluxes. These methods are: (1) Obtaining surface sensible and latent heat fluxes from satellite measurements; (2)Obtaining surface sensible and latent heat fluxes from an MABL model; (3) A method using horizontal transfer coefficients. These techniques are not very sensitive to errors in the data and therefore appear to hold promise of producing useful answers. Questions remain about how closely the structure of the real atmosphere agrees with the assumptions made for each of these techniques, and, therefore about how well these techniques can perform in actual use. The value of these techniques is that they promise to provide methods for the determination of fluxes over regions where very few traditional measurement exist.

Stage, S. A.↗
NASA NTRS1986

A universal equation of state for solids

The total energy versus interatomic spacing of ionic, metallic, covalent, and rare-gas solids is examined, and a universal form for pressure as a function of volume for all classes of solids in compression is derived. The relation is shown to hold for pressure-volume data for hydrogen and deuterium, xenon, cesium, molybdenum, sodium chloride, and magnesium oxide.

Vinet, P.↗
NASA NTRS1985

An experimental study of biaxial yield in modified 9Cr-1Mo steel at room temperature

Described are two biaxial experiments which investigated yield, hardening, and flow behavior in modified 9Cr-1Mo steel at room temperature. The aim of these experiments was to determine whether the procedures recommended in NE Standard F9-5T for inelastic design analysis are applicable for this material in normalized and tempered condition. The first experiment investigated small offset yield behavior subsequent to radial preloads (sq rt of 3 sub sigma 12 = sub sigma 11) in tension-torsion stress space. The second experiment investigated yield behavior subsequent to nonradial preloads and also the time-dependent flow occurring during 0.5 hour periods at constant stress. The results of these experiments were qualitatively similar to those obtained earlier for types 304 and 316 stainless steel. Specifically, the von Mises yield criterion was found to provide a reasonable approximation of initial yield behavior. Although the subsequent yield surfaces suffered considerable distortion from their near-circular form after both radial and nonradial preloads, the hardening behavior was to the first order kinematic in nature. The strain-time data obtained during the 0.5 hr hold periods showed characteristics typical of creep curves. As in the case of earlier experiments, the high initial flow rates diminished more rapidly than would be estimated from elevated temperature data.

Ellis, J. R.↗
NASA NTRS1992

Shot noise limits to sensitivity of optical interferometry

By arguing that the limiting noise is the photoelectron shot noise, we show that the sensitivity of image synthesis by an ideal optical interferometer is independent of the details of beam-splitting and recombination. The signal-to-noise ratio of the synthesized image is proportional to the square root of the total number of photoelectrons detected by the entire array. For non-ideal interferometers, which are forced to employ a closure-phase method of indirect inference of the visibility data, essentially the same result holds for strong sources, but at weak light levels beam-splitting degrades sensitivity.

Prasad, Sudhakar↗
NASA NTRS1943

The induction of water to the inlet air as a means of internal cooling in aircraft-engine cylinders

Report presents the results of investigations conducted on a full-scale air-cooled aircraft-engine cylinder of 202-cubic inch displacement to determine the effects of internal cooling by water induction on the maximum permissible power and output of an internal-combustion engine. For a range of fuel-air and water-fuel ratios, the engine inlet pressure was increased until knock was detected aurally, the power was then decreased 7 percent holding the ratios constant. The data indicated that water was a very effective internal coolant, permitting large increases in engine power as limited by either knock or by cylinder temperatures.

Rothrock, Addison M↗
NASA NTRS1994

1994 Science Information Management and Data Compression Workshop

This document is the proceedings from the 'Science Information Management and Data Compression Workshop,' which was held on September 26-27, 1994, at the NASA Goddard Space Flight Center, Greenbelt, Maryland. The Workshop explored promising computational approaches for handling the collection, ingestion, archival and retrieval of large quantities of data in future Earth and space science missions. It consisted of eleven presentations covering a range of information management and data compression approaches that are being or have been integrated into actual or prototypical Earth or space science data information systems, or that hold promise for such an application. The workshop was organized by James C. Tilton and Robert F. Cromp of the NASA Goddard Space Flight Center.

Tilton, James C.↗
NASA NTRS1995

The 1995 Science Information Management and Data Compression Workshop

This document is the proceedings from the 'Science Information Management and Data Compression Workshop,' which was held on October 26-27, 1995, at the NASA Goddard Space Flight Center, Greenbelt, Maryland. The Workshop explored promising computational approaches for handling the collection, ingestion, archival, and retrieval of large quantities of data in future Earth and space science missions. It consisted of fourteen presentations covering a range of information management and data compression approaches that are being or have been integrated into actual or prototypical Earth or space science data information systems, or that hold promise for such an application. The Workshop was organized by James C. Tilton and Robert F. Cromp of the NASA Goddard Space Flight Center.

Tilton, James C.↗
NASA NTRS1987

A comparative study of diversification events: the early Paleozoic versus the Mesozoic

We compare two major long-term diversifications of marine animal families that began during periods of low diversity but produced strikingly different numbers of phyla, classes, and orders. The first is the early-Paleozoic diversification (late Vendian-Ordovician; 182 MY duration) and the other the Mesozoic phase of the post-Paleozoic diversification (183 MY duration). The earlier diversification was associated with a great burst of morphological invention producing many phyla, classes, and orders and displaying high per taxon rates of family origination. The later diversification lacked novel morphologies recognized as phyla and classes, produced fewer orders, and displayed lower per taxon rates of family appearances. The chief difference between the diversifications appears to be that the earlier one proceeded from relatively narrow portions of adaptive space, whereas the latter proceeded from species widely scattered among adaptive zones and representing a variety of body plans. This difference is believed to explain the major differences in the products of these great radiations. Our data support those models that hold that evolutionary opportunity is a major factor in the outcome of evolutionary processes.

NASA Discipline Exobiology↗
NASA NTRS2020

Machine Learning-Based Predictive Analytics for Aircraft Engine Conceptual Design

Big data and artificial intelligence/machine learning are transforming the global business environment. Data is now the most valuable asset for enterprises in every industry. Companies are using data-driven insights for competitive advantage. With that, the adoption of machine learning-based data analytics is rapidly taking hold across various industries, producing autonomous systems that support human decision-making. This work explored the application of machine learning to aircraft engine conceptual design. Supervised machine-learning algorithms for regression and classification were employed to study patterns in an existing, open-source database of production and research turbofan engines, and resulting in predictive analytics for use in predicting performance of new turbofan designs. Specifically, the author developed machine learning-based analytics to predict cruise thrust specific fuel consumption (TSFC) and core sizes of high-efficiency turbofan engines, using engine design parameters as the input. The predictive analytics were trained and deployed in Keras, an open-source neural networks application program interface (API) written in Python, with Google’s TensorFlow (an open source library for numerical computation) serving as the backend engine. The promising results of the predictive analytics show that machine-learning techniques merit further exploration for application in aircraft engine conceptual design.

deep-learning↗
NASA NTRSDate not supplied

pyQuARC: Preparing for Full Release

Metadata holds the contextual information about data and is the underlying structure for many data search portals. High quality metadata optimizes search results, allowing users to quickly retrieve the data they need. With the abundant volume and diversity of Earth observation datasets, data discovery and metadata quality are critical for end users. The Common Metadata Repository (CMR), for example, currently hosts metadata for over 9,000 Earth observation data products archived across 12 NASA Distributed Active Archive Centers (DAACs). The Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, assesses the completeness, correctness, and consistency of these metadata records to ensure they are accessible, usable, and discoverable. In 2021, ARC began developing pyQuARC, an open source library for Earth Observation Metadata Quality Assessment to automate this effort. The tool uses ARC’s existing metadata quality framework to provide prioritized recommendations for metadata improvement. During initial testing, pyQuARC automatically identified 58% of metadata findings when compared with a sample of manually reviewed records. Using the results from initial testing, this presentation will focus on recent advancements and improvements of the tool as the ARC team prepares for pyQuARC’s full release. It will also demonstrate pyQuARC's enrichment value, not only for the ARC team, but the broader EOSDIS metadata community as well.

Essence Raphael↗
NASA NTRS1994

A terabyte linear tape recorder

A plan has been formulated and selected for a NASA Phase 2 SBIR award for using the VLBA tape recorder for recording general data. The VLBA tape recorder is a high-speed, high-density linear tape recorder developed for Very Long Baseline Interferometry (VLBI) which is presently capable of recording at rates up to 2 Gbit/sec and holding up to 1 Terabyte of data on one tape, using a special interface and not employing error correction. A general-purpose interface and error correction will be added so that the recorder can be used in other high-speed, high-capacity applications.

Webber, John C.↗
NASA NTRS2014

Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data Assimilation

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Error Covariance↗
NASA NTRS2014

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗
NASA NTRS1983

Particle-sampling statistics in laser anemometers Sample-and-hold systems and saturable systems

The effect of the data-processing system on the particle statistics obtained with laser anemometry of flows containing suspended particles is examined. Attention is given to the sample and hold processor, a pseudo-analog device which retains the last measurement until a new measurement is made, followed by time-averaging of the data. The second system considered features a dead time, i.e., a saturable system with a significant reset time with storage in a data buffer. It is noted that the saturable system operates independent of the particle arrival rate. The probabilities of a particle arrival in a given time period are calculated for both processing systems. It is shown that the system outputs are dependent on the mean particle flow rate, the flow correlation time, and the flow statistics, indicating that the particle density affects both systems. The results are significant for instances of good correlation between the particle density and velocity, such as occurs near the edge of a jet.

Edwards, R. V.↗
NASA NTRS2006

Serving Fisheries and Ocean Metadata to Communities Around the World

NASA's Global Change Master Directory (GCMD) assists the oceanographic community in the discovery, access, and sharing of scientific data by serving on-line fisheries and ocean metadata to users around the globe. As of January 2006, the directory holds more than 16,300 Earth Science data descriptions and over 1,300 services descriptions. Of these, nearly 4,000 unique ocean-related metadata records are available to the public, with many having direct links to the data. In 2005, the GCMD averaged over 5 million hits a month, with nearly a half million unique hosts for the year. Through the GCMD portal (http://qcrnd.nasa.qov/), users can search vast and growing quantities of data and services using controlled keywords, free-text searches or a combination of both. Users may now refine a search based on topic, location, instrument, platform, project, data center, spatial and temporal coverage. The directory also offers data holders a means to post and search their data through customized portals, i.e. online customized subset metadata directories. The discovery metadata standard used is the Directory Interchange Format (DIF), adopted in 1994. This format has evolved to accommodate other national and international standards such as FGDC and IS019115. Users can submit metadata through easy-to-use online and offline authoring tools. The directory, which also serves as a coordinating node of the International Directory Network (IDN), has been active at the international, regional and national level for many years through its involvement with the Committee on Earth Observation Satellites (CEOS), federal agencies (such as NASA, NOAA, and USGS), international agencies (such as IOC/IODE, UN, and JAXA) and partnerships (such as ESIP, IOOS/DMAC, GOSIC, GLOBEC, OBIS, and GoMODP), sharing experience, knowledge related to metadata and/or data management and interoperability.

Meaux, Melanie↗
NASA NTRS2007

Serving Fisheries and Ocean Metadata to Communities Around the World

NASA's Global Change Master Directory (GCMD) assists the oceanographic community in the discovery, access, and sharing of scientific data by serving on-line fisheries and ocean metadata to users around the globe. As of January 2006, the directory holds more than 16,300 Earth Science data descriptions and over 1,300 services descriptions. Of these, nearly 4,000 unique ocean-related metadata records are available to the public, with many having direct links to the data. In 2005, the GCMD averaged over 5 million hits a month, with nearly a half million unique hosts for the year. Through the GCMD portal (http://gcmd.nasa.gov/), users can search vast and growing quantities of data and services using controlled keywords, free-text searches, or a combination of both. Users may now refine a search based on topic, location, instrument, platform, project, data center, spatial and temporal coverage, and data resolution for selected datasets. The directory also offers data holders a means to advertise and search their data through customized portals, which are subset views of the directory. The discovery metadata standard used is the Directory Interchange Format (DIF), adopted in 1988. This format has evolved to accommodate other national and international standards such as FGDC and IS019115. Users can submit metadata through easy-to-use online and offline authoring tools. The directory, which also serves as the International Directory Network (IDN), has been providing its services and sharing its experience and knowledge of metadata at the international, national, regional, and local level for many years. Active partners include the Committee on Earth Observation Satellites (CEOS), federal agencies (such as NASA, NOAA, and USGS), international agencies (such as IOC/IODE, UN, and JAXA) and organizations (such as ESIP, IOOS/DMAC, GOSIC, GLOBEC, OBIS, and GoMODP).

Meaux, Melanie F.↗
NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗
NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗