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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Gene Transfers Between Distantly Related Organisms

With the completion of numerous microbial genome sequences, reports of individual gene transfers between distantly related prokaryotes have become commonplace. On the other hand, transfers between prokaryotes and eukaryotes still excite the imagination. Many of these claims may be premature, but some are certainly valid. In this chapter, the kinds of supporting data needed to propose transfers between distantly related organisms and cite some interesting examples are considered.

Doolittle, Russell F.↗
NASA NTRS2005

An Agent-Based Interface to Terrestrial Ecological Forecasting

The latest generation of NASA Earth Observing System (EOS) satellites has brought a new dimension to continuous monitoring of the living part of the Earth System, the biosphere. EOS data can now provide weekly global measures of vegetation productivity and ocean chlorophyll, and many related biophysical factors such as land cover changes or snowmelt rates. However, the highest economic value would come from forecasting impending conditions of the biosphere, to allow decision makers to mitigate dangers or exploit positive trends. NASA's strategic plan for the Earth Science Enterprise i d e n a s ecological forecasting as a focus for research. Ecological forecasting predicts the effects of changes in the physical, chemical and biological environment on ecosystem activity. Possible applications of such a system include predicting shortfalls or bumper crops of agricultural production, populations of threatened or invasive species or wildfire danger in time to allow improves preparation and logistical efficiency. Petabytes of remote sensing data are now available to help measure, understand and forecast changes in the Earth system, but using these data effectively can be surprisingly hard. The volume and variety of data files and formats are daunting. Simple data management activities, such as locating and transferring files, changing file formats, gridding point data, and scaling and reprojecting gridded data, can consume far more personnel time and resources than the actual data analysis. Some scientists commit to a particular data source or resolution just because using anything different would be more effort that it's worth. Better tools can help, but most of the tools developed to date are little more than shell scripts; they lack the flexibility to meet the diverse needs of users and are difficult to extend to handle changes in available data sources.

Golden, Keith↗
DOE OSTI2021

Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures

Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that data compression is becoming a critical technique to mitigate the storage burden and data movement cost. Huffman coding is arguably the most efficient Entropy coding algorithm in information theory, such that it could be found as a fundamental step in many modern compression algorithms such as DEFLATE. On the other hand, today's HPC applications are more and more relying on the accelerators such as GPU on supercomputers, while Huffman encoding suffers from low throughput on GPUs, resulting in a significant bottleneck in the entire data processing. In this paper, we propose and implement an efficient Huffman encoding approach based on modern GPU architectures, which addresses two key challenges: (1) how to parallelize the entire Huffman encoding algorithm, including codebook construction, and (2) how to fully utilize the high memory-bandwidth feature of modern GPU architectures. The detailed contribution is fourfold. (1) We develop an efficient parallel codebook construction on GPUs that scales effectively with the number of input symbols. (2) We propose a novel reduction based encoding scheme that can efficiently merge the codewords on GPUs. (3) We optimize the overall GPU performance by leveraging the state-of-the-art CUDA APIs such as Cooperative Groups. (4) We evaluate our Huffman encoder thoroughly using six real-world application datasets on two advanced GPUs and compare with our implemented multithreaded Huffman encoder. Experiments show that our solution can improve the encoding throughput by up to 5.0× and 6.8× on NVIDIA RTX 5000 and V100, respectively, over the state-of-the-art GPU Huffman encoder, and by up to 3.3× over the multithread encoder on two 28-core Xeon Platinum 8280 CPUs.

Tian, Jiannan↗
NASA NTRS1986

External calibration of SIR-B Imagery with area-extended and point targets

Data collected by the Shuttle Imaging Radar-B (SIR-B) on two ascending orbits over a site in west-central Illinois were used to establish end-to-end transfer functions for conversion of the digital numbers on the eight-bit image to values of the radar backscattering coefficient, sigma(0). The transfer function for each data take was defined by the SIR response to an array of six calibrated point targets of known radar cross section and to a large number of area-extended targets, also with a known cross section, as measured by externally calibrated, truck-mounted scatterometers. In spite of variance in the SIR transmit power, end-to-end transfer functions generated from either point targets or area-extended targets were found to yield close agreement for a given pass, indicating that targets of known radar cross section can be used to provide transfer functions for orbital SAR. Although the use of area-extended targets yielded the most satisfactory results, the use of point targets is far simpler and may be the preferred alternative for many situations.

Dobson, M. C.↗
NASA NTRS1990

Longwave cloud radiative forcing at the surface from ISCCP-C1 data

A method for deriving one component of the total cloud forcing picture, namely, the LW cloud forcing at the surface, is presented. The method is based on a validated radiative transfer technique and utilizes meteorological data available from the International Satellite Cloud Climatology Project. The radiative transfer model used was validated earlier and the TOVS-derived temperature and water vapor data used were generally reasonable. On a monthly-average basis, random error was estimated to be in the 5-10 W/sq m range, but biases as large as 10-20 W/sq m can occur in some regions. The lack of information on cloud-base heights were found to be the largest source of errors in the models and the meteorological data.

Gupta, Shashi K.↗
NASA NTRS1992

Comparing the results of an analytical model of the no-vent fill process with no-vent fill test results for a 4.96 cu m (175 cu ft) tank

NASA-Lewis has been investigating a no-vent fill method for refilling cryogenic storage tanks in low gravity. Analytical modeling based on analyzing the heat transfer of a droplet has successfully represented the process in 0.034 and 0.142 sq m commercial dewars using liquid nitrogen and hydrogen. Recently a large tank (4.96 sq m) was tested with hydrogen. This lightweight tank is representative of spacecraft construction. This paper presents efforts to model the large tank test data. The droplet heat transfer model is found to overpredict the tank pressure level when compared to the large tank data. A new model based on equilibrium thermodynamics has been formulated. This new model is compared to the published large scale tank's test results as well as some additional test runs with the same equipment. The results are shown to match the test results within the measurement uncertainty of the test data except for the initial transient wall cooldown where it is conservative (i.e., overpredicts the initial pressure spike found in this time frame).

Taylor, William J.↗
NASA NTRS1984

Complete flowfields over low and wide angle AOTV conceptual configurations

Flowfields over two conceptual aeroassisted orbital transfer vehicles, a moderate lift-to-drag ratio biconic, and an axisymmetric zero lift aerobrake are investigated. The solution procedures employ a compressible Navier-Stokes time-asymptotic technique for blunt body flow and a Parabolized Navier-Stokes spatial marching technique for the primarily supersonic shock layer flow over low-angle bodies. Emphasis is placed on the laminar convective heating predictions and comparisons to experimental data where available. Code robustness and solution times are discussed and guidelines are given for the specification of various numerical parameters. The Parabolized Navier-Stokes technique has a high probability of solution success for the range of applications considered herein, and very good comparisons with experimental heat-transfer data have been obtained. The blunt body Navier-Stokes code is more sensitive to parameter specification for the aerobrake calculations. Still, coarse grid solutions can be obtained quickly to get a good first cut at flowfield definition. Fair to good comparisons have been obtained between experimental heating and pressure data and coarse and fine grid solutions.

Gnoffo, P. A.↗
DOE OSTI2023

Data-driven quantum approximate optimization algorithm for power systems

Abstract Quantum technology provides a ground-breaking methodology to tackle challenging computational issues in power systems. It is especially promising for Distributed Energy Resources (DERs) dominant systems that have been widely developed to promote energy sustainability. In those systems, knowing the maximum sections of power and data delivery is essential for monitoring, operation, and control. However, high computational effort is required. By leveraging quantum resources, Quantum Approximate Optimization Algorithm (QAOA) provides a means to search for these sections efficiently. However, QAOA performance relies heavily on critical parameters, especially for weighted graphs. Here we present a data-driven QAOA, which transfers quasi-optimal parameters between weighted graphs based on the normalized graph density. We verify the strategy with 39,774 expectation value calculations. Without parameter optimization, our data-driven QAOA is comparable with the Goemans-Williamson algorithm. This work advances QAOA and pilots its practical application to power systems in noisy intermediate-scale quantum devices.

Jing, Hang (ORCID:0000000256343489)↗
NASA NTRS1998

Technology Assessment of High Capacity Data Storage Systems: Can We Avoid a Data Survivability Crisis?

This technology assessment of long-term high capacity data storage systems identifies an emerging crisis of severe proportions related to preserving important historical data in science, healthcare, manufacturing, finance and other fields. For the last 50 years, the information revolution, which has engulfed all major institutions of modem society, centered itself on data-their collection, storage, retrieval, transmission, analysis and presentation. The transformation of long term historical data records into information concepts, according to Drucker, is the next stage in this revolution towards building the new information based scientific and business foundations. For this to occur, data survivability, reliability and evolvability of long term storage media and systems pose formidable technological challenges. Unlike the Y2K problem, where the clock is ticking and a crisis is set to go off at a specific time, large capacity data storage repositories face a crisis similar to the social security system in that the seriousness of the problem emerges after a decade or two. The essence of the storage crisis is as follows: since it could take a decade to migrate a peta-byte of data to a new media for preservation, and the life expectancy of the storage media itself is only a decade, then it may not be possible to complete the transfer before an irrecoverable data loss occurs. Over the last two decades, a number of anecdotal crises have occurred where vital scientific and business data were lost or would have been lost if not for major expenditures of resources and funds to save this data, much like what is happening today to solve the Y2K problem. A pr-ime example was the joint NASA/NSF/NOAA effort to rescue eight years worth of TOVS/AVHRR data from an obsolete system, which otherwise would have not resulted in the valuable 20-year long satellite record of global warming. Current storage systems solutions to long-term data survivability rest on scalable architectures having parallel paths for data migration.

Halem, M.↗
DOE OSTI2026

Machine Learning Digital Twin for Lithium Ion Battery State of Health Predictions

A digital twin system has been established to model the long term degradation of the state of health of lithium ion batteries. Two data streams result from the computational model of the system and from the physical experiment measurements. A machine learning pipeline has been developed at the nexus of these data streams. Leveraging the unique data sources in multiple transfer learning approaches has lead to the development of multiple cell specific machine learning digital twins. Our discussion on this first of its kind technology will cover challenges in data ingestion, scalability, architecture and orchestration, and research findings.

25 - ENERGY STORAGE↗
NASA NTRS1993

Comparing the results of an analytical model of the no-vent fill process with no-vent fill test results for a 4.96 cubic meters (175 cubic feet) tank

The NASA Lewis Research Center (NASA/LeRC) have been investigating a no-vent fill method for refilling cryogenic storage tanks in low gravity. Analytical modeling based on analyzing the heat transfer of a droplet has successfully represented the process in 0.034 m and 0.142 cubic m commercial dewars using liquid nitrogen and hydrogen. Recently a large tank (4.96 cubic m) was tested with hydrogen. This lightweight tank is representative of spacecraft construction. This paper presents efforts to model the large tank test data. The droplet heat transfer model is found to over predict the tank pressure level when compared to the large tank data. A new model based on equilibrium thermodynamics has been formulated. This new model is compared to the published large scale tank's test results as well as some additional test runs with the same equipment. The results are shown to match the test results within the measurement uncertainty of the test data except for the initial transient wall cooldown where it is conservative (i.e., overpredicts the initial pressure spike found in this time frame).

Taylor, William J.↗
NASA NTRS1993

The turbulent thermal boundary layer with an abrupt change from a rough to a smooth wall

The work reported here was motivated by concern over the use of smooth heat flux gages for heat transfer measurements on the otherwise rough turbine blades. Stanton number distributions and boundary layer profiles of mean temperature, mean velocity, and turbulence intensity are reported for a surface with a step change from a rough to a smooth surface. In most cases, the Stanton number immediately downstream of the change in roughness drops below the all-smooth-wall data at the same x-Reynolds number. The alignment of the smooth surface between the bases and crests of the roughness elements is shown to have only a weak effect on the Stanton number distribution. It is concluded that the use of smooth heat flux gages on otherwise rough surfaces can cause large errors. It is recommended that heat transfer data collected in this manner be used with caution.

Taylor, Robert P.↗
DOE OSTI2022

Data-driven Mapping of the Mouse Connectome: The utility of transfer learning to improve the performance of deep learning models performing axon segmentation on light-sheet microscopy images

Light sheet microscopy has made possible the high temporal and spatial 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual process. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through the application of refinements such as transfer learning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Potential structures - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains shapefiles, geotiffs, and symbology for the revised-from-Play-Fairway potential structures/structural settings used in the Nevada Geothermal Machine Learning project. Layers include potential structural setting ellipses, centroids, and distance-to-centroid raster. A submission linking the full GitHub repository for our machine learning Jupyter Notebooks will appear in the related datasets section of this page once available.

15 GEOTHERMAL ENERGY↗
NASA NTRS1994

Pen-based computers: Computers without keys

The National Space Transportation System (NSTS) is comprised of many diverse and highly complex systems incorporating the latest technologies. Data collection associated with ground processing of the various Space Shuttle system elements is extremely challenging due to the many separate processing locations where data is generated. This presents a significant problem when the timely collection, transfer, collation, and storage of data is required. This paper describes how new technology, referred to as Pen-Based computers, is being used to transform the data collection process at Kennedy Space Center (KSC). Pen-Based computers have streamlined procedures, increased data accuracy, and now provide more complete information than previous methods. The end results is the elimination of Shuttle processing delays associated with data deficiencies.

Conklin, Cheryl L.↗
NASA NTRS1994

A hypertext-based Internet-assessable database for the MSFC Technology Transfer Office

There exists a continuing need to disseminate technical information and facilities capabilities from NASA field centers in an effort to promote the successful transfer of technologies developed with public funds to the private sector. As technology transfer is a stated NASA mission, there exists a critical need for NASA centers to document technology capabilities and disseminate this information on as wide a basis as possible. Certainly local and regional dissemination is critical, but global dissemination of scientific and engineering facilities and capabilities gives NASA centers the ability to contribute to technology transfer on a much broader scale. Additionally, information should be disseminated in a complete and rapidly available form. To accomplish this information dissemination, the unique capabilities of the Internet are being exploited. The Internet allows widescale information distribution in a rapid fashion to aid in the accomplishment of technology transfer goals established by the NASA/MSFC Technology Transfer Office. Rapid information retrieval coupled with appropriate electronic feedback, allows the scientific and technical capabilities of Marshall Space Flight Center, often unique in the world, to be explored by a large number of potential benefactors of NASA (or NASA-derived) technologies. Electronic feedback, coupled with personal contact with the MSFC Technology Transfer Office personnel, allows rapid responses to technical requests from industry and academic personnel as well as private citizens. The remainder of this report gives a brief overview of the Mosaic software and a discussion of technology transfer office and laboratory facilities data that have been made available on the Internet to promote technology transfer.

Jackson, Jeff↗