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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

NAE Twin Otter operations in FIFE 1989

During the summer of 1989, the National Aeronautical Establishment (Canada) Twin Otter Atmospheric Research Aircraft was flow in support of the NASA sponsored First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment called FIFE-89. Airborne measurements of the fluxes of heat, momentum, water vapor and carbon dioxide were made during 16 flow-altitude flights over the FIFE project area in central Kansas. The Twin Otter operations in FIFE are documented and details are included on the instrumentation, software, flight procedures, atmospheric conditions and analysis methods. Comparisons of Twin Otter measured fluxes are made with those determined at several surface sites and with those made by other instrumented aircraft in the FIFE-87 measurements. Airborne flux measurements are related to run length, altitude, and environmental parameters such as vegetation type, temperature, and wind speed. One night flight was run in an attempt to measure the respiration component of the CO2 flux. The use of aircraft was studied for regional observations of fluxes and to relate these to satellite radiance measurements. Run average data are presented for all 285 flux runs flown by the Twin Otter in FIFE-89. This should serve as as a working reference for scientists utilizing Twin Otter data either directly of through the FIFE data archive.

Macpherson, J. I.↗
NASA NTRS1999

Automatic Data Distribution for CFD Applications on Structured Grids

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAPT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAPT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

Frumkin, Michael↗
NASA NTRS2000

Automatic Data Distribution for CFD Applications on Structured Grids

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAFT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAFT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

Frumkin, Michael↗
NASA NTRSDate not supplied

Design and Analysis of Convolutional Neural Network for RF Signal Modulation Classification for In-Orbit Deployment

To effectively transmit data to and from satellites requires a complex and robust RF communication system. Commonly, several different types of signal modulations may be required to maximize satellite efficiency depending on a variety of unexpected channel impairments. We propose a neural network algorithm capable of learning these RF signal modulations using a supervised learning technique designed for low power, high-efficiency in-orbit deployment. The work presented demonstrates a convolutional neural network (CNN) capable of learning and recognizing a set of modulation schemes commonly used to transmit RF information. We are capable of recognizing the modulation scheme from the I and Q data channels directly, with no preprocessing or data conversion required other than breaking the incoming signal into a set of uniform normalized samples. We perform a network design and size analysis, showing that reasonably high accuracy can be obtained using networks with a relatively low number of trainable parameters. Given that a user of a system such as this may wish to receive a signal using a modulation scheme that the network has not previously learned, we demonstrate that transfer learning can learn new modulation schemes by retraining only the fully connected layers in the CNN. Thus, this type of network would excel in outer space deployment using high-efficiency transfer learning hardware. Modulation recognition can be performed through rapid feedforward computation, and the CNN training process is significantly simplified when learning new modulations is required.

CNN↗
DOE OSTI2025

Fostering Geothermal Machine Learning Success: Elevating Big Data Accessibility and Automated Data Standardization in the Geothermal Data Repository

The Department of Energy's (DOE's) Geothermal Data Repository (GDR) has implemented improvements to both its data lakes and its data standards and automated data pipelines. The GDR data lakes have reduced storage and compute-related barriers to using large geothermal datasets, enabling these large datasets to be accessed by anyone with a modern computer and internet access. More recently, the GDR has been working to further reduce barriers through streamlining the data intake process, educating users on the process and requirements, and helping users access data from the data lakes. These improvements have augmented the quantity of datasets the GDR is able to accept into its data lakes and have enabled users who are new to cloud tools to access these datasets more easily, overall increasing the accessibility of big geothermal data for use in machine learning and other projects. In addition, the GDR now has built-in data standards and pipelines for drilling data, geospatial data, and distributed acoustic sensing (DAS) data. These standardization efforts aim to enhance the real-world applicability of geothermal machine learning outcomes by improving the quality of training data. Specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, thus allowing more time for actual research. By automating this process, the burden of standardization is lifted from the user, ultimately increasing the availability of standardized data. This paper provides an update on recent improvements made to the GDR's data lakes and automated data pipelines, including: (1) streamlining the data lake intake process, (2) better educating users on the process and requirements through a new data lakes page, (3) adding data lake direct access links to GDR data lake submission pages, (4) implementing a DAS data pipeline to convert DAS data uploaded in SEG-Y format to a standardized hierarchical data format v5 (HDF5), (5) extending this pipeline to encompass data in the GDR data lake, (6) adding metadata requirements for geospatial data, (7) making user interface/user experience (UX) enhancements to the data pipelines' documentation pages, and (8) improving the GDR's data standards and pipelines pages to better guide users in ensuring that their data is standardized by the GDR's automated data pipelines. 2024 Geothermal Resources Council. All rights reserved.

accessibility↗
NASA NTRS1987

Low cost, microcomputer-based interactive analysis system for direct-reception and archived remote sensing data

A hardware/software system has been developed for use in meteorological field experiments and by developing countries which need low-cost remote sensing data analysis capabilities. The system can directly receive satellite transmissions of the AVHRR, TOVS, Argos, GOES, GMS, and Meteosat systems. Also, the system can process computer tapes from Landsat. Received data are ingested directly into the computer's disk storage, eliminating the need for a wide-band analog tape drive. Data may be interpreted in terms of cloud imagery, cloudtop temperature, sea surface temperature, vegetation index, and temperature/humidity profiles with overlays of geographic boundaries and latitude/longitude grids. The image processing, enhancement functions, and modeling capabilities of the system are discussed.

Vermillion, Charles H.↗
NASA NTRS2017

CERES S’COOL Project Update: The Evolution and Value of a Long-Running Education Project With a Foundation in NASA Earth Science Missions

In January 1997, the Students’ Cloud Observations On-Line (S’COOL; http://scool.larc.nasa.gov) Project began with NASA scientists visiting rural Gloucester, Virginia to observe clouds with middle school students. In the 19 years since, this educational outreach component of NASA’s Clouds and the Earth’s Radiant Energy System (CERES) mission has collected ~141,000 observations from every continent and ocean basin around the world. Thousands of students and teachers have directly engaged in S’COOL. Beginning in 2008 we invited citizen scientists to participate as well. Over time S’COOL has added more components that engage participants directly with science data analysis, continuing direct ties to CERES research. Whenever possible, the S’COOL team extracts corresponding subsets of CERES data, which are sent to the participant to analyze. Observations can now be matched to images and cloud retrievals from MODIS and measurements from CALIPSO. To date, more than half of S'COOL observation reports correspond to one (or more) CERES overpasses. Comparisons with CERES geostationary satellite cloud retrievals were recently added, making cloud observations at almost any time of day over non-polar regions useful for validation. A thorough analysis of co-located S’COOL and satellite data was conducted during summer 2015. Results show that the S’COOL community provides high quality observations offering useful insights on the strengths and shortcomings of passive cloud remote sensing from space. This reconfirmed the utility of S’COOL observations to the scientific community and provides observers with deeper insight into the challenges associated with validation of space-based cloud property retrievals.

Lin H Chambers↗
NASA NTRS1998

Locating Biodiversity Data Through The Global Change Master Directory

The Global Change Master Directory (GCMD) presently holds descriptions for almost 7000 data sets held worldwide. The directory's primary purpose is for data discovery. The information provided through the GCMD's Directory Interchange Format (DIF) is the set of information that a researcher would need to determine if a particular data set could be of value. By offering data set descriptions worldwide in many scientific disciplines - including meteorology, oceanography, ecology, geology, hydrology, geophysics, remote sensing, paleoclimate, solar-terrestrial physics, and human dimensions of climate change - the GCMD simplifies the discovery of data sources. Direct linkages to many of the data sets are also provided. In addition, several data set registration tools are offered for populating the directory. To search the directory, one may choose the Guided Search or Free-Text Search. Two experimental interfaces were also made available with the latest software release - one based on a keyword search and another based on a graphical interface. The graphical interface was designed in collaboration with the Human Computer Interaction Laboratory at the University of Maryland. The latest version of the software, Version 6, was released in April, 1998. It features the implementation of a scheme to handle hierarchical data set collections (parent-child relationships); a hierarchical geospatial location search scheme; a Java-based geographic map for conducting geospatial searches; a Related-URL field for project-related data set collections, metadata extensions (such as more detailed inventory information), etc.; a new implementation of the Isite software; a new dataset language field; hyperlinked email addresses, and more. The key to the continued evolution of the GCMD is in the flexibility of the GCMD database, allowing modifications and additions to made relatively easily to maintain currency, thus providing the ability to capitalize on current technology while importing all existing records. Changes are discussed and approved through an online "interoperability" forum. The next major release of the GCMD is scheduled for early 1999 and will include the incorporation of a new matrix-based interface, a rapid valids-based query system; improvement in the operations facility - important for future distributed options; new streamlined code for greater performance and maintainability; improvements in the handling of seven current fields proposed through the interoperability forum (at no expense to the data providers); and the release of DOCmorph, a more robust version of DIFmorph to translate many 'standards' multi-directionally. Issues and actions will also be addressed.

Olsen, Lola M.↗
NASA NTRS1991

Inferring vegetation characteristics using a knowledge-based system

A knowledge-based system for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input is developed. A portion of this system has been developed to discriminate between user-defined vegetation classes using spectral and directional reflectance relationships. This discrimination program was used to classify targets into user-defined ground cover and plant height classes. The program learns class descriptors from samples (both positive and negative) of spectral, directional reflectance data of natural surfaces (bare soils, natural vegetation, and agricultural vegetation). The system is designed to handle any combination of directional view angles. The explicit relationships used in the class descriptions include greater-than relationships between combinations of two view angles and maximum and minimum value relationships. The class descriptions are used to classify an unknown target using the same directional views. The program was tested by learning class descriptions of various categories of percent ground cover and vegetation height.

Kimes, D. S.↗
NASA NTRS1992

High resolution gravity models combining terrestrial and satellite data

Spherical harmonic expansions to degree 360 have been developed that combine satellite potential coefficient information, terrestrial gravity data, satellite altimeter information as a direct tracking data type and topographic information. These models define improved representations of the Earth's gravitational potential beyond that available from just satellite or terrestrial data. The development of the degree 360 models, however, does not imply a uniform accuracy in the determination of the gravity field as numerous geographic areas are devoid of terrestrial data or the resolution of such data is limited to, for example, 100 km. This paper will consider theoretical and numerical questions related to the combination of the various data types. Various models of the combination process are discussed with a discussion of various correction terms for the different models. Various sources of gravity data will be described. The new OSU91 360 model will be discussed with comparisons made to previous 360 models and to other potential coefficient models that are complete to degree 50. Future directions in high degree potential coefficient models will be discussed.

Rapp, Richard H.↗
NASA NTRS1987

Estimation of canopy parameters of row planted vegetation canopies using reflectance data for only four view directions

A procedure for estimating leaf area index (LAI) and percentage of ground cover (GC) for inhomogeneous row planted vegetation canopies using measurement of canopy reflectance (CR) data for only four directions is presented. This procedure, referred to as 'reconstructive inversion', uses the CR data for these directions to first 'reconstruct' the complete bidirectional surface, which is then used to estimate the canopy parameters using the standard inversion of a CR model technique. The technique has been successfully applied to soybeam and corn canopies in various stages of growth.

Goel, Narendra S.↗
DOE OSTI2022

An efficient method to propagate model uncertainty when inverting seismic data for time domain seismic moment tensors

SUMMARY We present a computationally efficient method to approximately propagate uncertainty when linearly inverting seismic data for point source, time variable moment tensor components. The method is based on the assumption that the data residual, given by the difference between the observed seismic data and the data predicated by a linear inversion, contains the effects of both data and model uncertainty. Our method uses a distribution of data residuals, added directly to the data, in a pseudo-Monte Carlo scheme. Using the assumption that the data residual is a stochastic process, we use the well-known Karhunen–Loève (KL) theorem to construct a distribution of data residuals, where the required basis functions are constructed using Fourier series. The Fourier series are scaled by a product of a random variable and the real-valued spectral amplitudes of the original data residual’s spectrum. Thus, the Fourier series and spectral amplitudes are eigenfunction-eigenvalue pairs used in the KL-based construction of data residual distribution. Using tests with synthetic data, we show that our method compares closely with a Finite Difference Monte Carlo (FDMC) method that we presented previously. More importantly, the method presented here is computationally several orders of magnitude faster than our previous FDMC method, and requires no a priori assumptions of model and/or data uncertainty.

Poppeliers, Christian (ORCID:0000000159526849)↗
NASA NTRS1987

Modeling scalar flux and the energy and dissipation equations

Closure models derived from the Two-Scale Direct-Interaction Approximation were compared with data from direct simulations of turbulence. Attention was restricted to anisotropic scalar diffusion models, models for the energy dissipation equation, and models for energy diffusion.

Yoshizawa, A.↗
NASA NTRS1990

High resolution spectroscopy in the microwave and far infrared

High resolution rotational spectroscopy has long been central to remote sensing techniques in atmospheric sciences and astronomy. As such, laboratory measurements must supply the required data to make direct interpretation of data for instruments which sense atmospheres using rotational spectra. Spectral measurements in the microwave and far infrared regions are also very powerful tools when combined with infrared measurements for characterizing the rotational structure of vibrational spectra. In the past decade new techniques were developed which have pushed high resolution spectroscopy into the wavelength region between 25 micrometers and 2 mm. Techniques to be described include: (1) harmonic generation of microwave sources, (2) infrared laser difference frequency generation, (3) laser sideband generation, and (4) ultrahigh resolution interferometers.

Pickett, Herbert M.↗
NASA NTRS2013

Assessment of Soil Moisture Data Requirements by the Potential SMAP Data User Community: Review of SMAP Mission User Community

NASA's Soil Moisture Active and Passive (SMAP) mission is planned for launch in October 2014 and will provide global measurements of soil moisture and freeze thaw state. The project is driven by both basic research and applied science goals. Understanding how application driven end-users will apply SMAP data, prior to the satellite's launch, is an important goal of NASA's applied science program and SMAP mission success. Because SMAP data are unique, there are no direct proxy data sets that can be used in research and operational studies to determine how the data will interact with existing processes. The objective of this study is to solicit data requirements, accuracy needs, and current understanding of the SMAP mission from the potential user community. This study showed that the data to be provided by the SMAP mission did substantially meet the user community needs. Although there was a broad distribution of requirements stated, the SMAP mission fit within these requirements.

applications↗
NASA NTRS2000

Benchmark of FDNS CFD Code For Direct Connect RBCC Test Data

Computational Fluid Dynamics (CFD) analysis results are compared with experimental data from the Pennsylvania State University's (PSU) Propulsion Engineering Research Center (PERC) rocket based combined cycle (RBCC) rocket-ejector experiments. The PERC RBCC experimental hardware was in a direct-connect configuration in diffusion and afterburning (DAB) operation. The objective of the present work was to validate the Finite Difference Navier Stokes (FDNS) CFD code for the rocket-ejector mode internal fluid mechanics and combustion phenomena. A second objective was determine the best application procedures to use FDNS as a predictive/engineering tool. Three-dimensional CFD analysis was performed. Solution methodology and grid requirements are discussed. CFD results are compared to experimental data for static pressure, Raman Spectroscopy species distribution data and RBCC net thrust and specified impulse.

Ruf, J. H.↗
DOE OSTI2020

UMLS users and uses: a current overview

Abstract The US National Library of Medicine regularly collects summary data on direct use of Unified Medical Language System (UMLS) resources. The summary data sources include UMLS user registration data, required annual reports submitted by registered users, and statistics on downloads and application programming interface calls. In 2019, the National Library of Medicine analyzed the summary data on 2018 UMLS use. The library also conducted a scoping review of the literature to provide additional intelligence about the research uses of UMLS as input to a planned 2020 review of UMLS production methods and priorities. 5043 direct users of UMLS data and tools downloaded 4402 copies of the UMLS resources and issued 66 130 951 UMLS application programming interface requests in 2018. The annual reports and the scoping review results agree that the primary UMLS uses are to process and interpret text and facilitate mapping or linking between terminologies. These uses align with the original stated purpose of the UMLS.

Amos, Liz↗