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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Preliminary analysis of NASA optical data obtained in barium ion cloud experiment of September 21, 1971.

This paper reviews the optical data obtained by NASA in the joint NASA-MPE experiment conducted on September 21, 1971, involving the release of a barium cloud at an altitude of about 31,500 km over Colombia, South America. The data indicated an anomalously high rate of elongation and an unexpectedly large rate of deceleration of the main core of the ion cloud. The outermost striational features achieved a steady velocity within a few minutes, thus indicating that they had acquired the velocity of the ambient plasma. From the observed drift of these striations, one deduces an electric field that, when referred to a coordinate system rotating with the earth, has a meridional component directed toward the interior of the magnetic loop of 0.14 mV/m and a component perpendicular to the meridional plane of 0.15 mV/m directed to the west.

Adamson, D.↗
NASA NTRS1992

Analysis, review, and documentation of the activation data from LDEF material

Samples removed from Long Duration Exposure Facility (LDEF-1) are being studied at various laboratories to determine the specific activity(pCi/kg) produced in orbit by exposure to protons and neutrons in near-Earth orbit. These activities are being corrected for efficiency, self-attenuation, and background. The activities and associated gamma-ray spectra are being collected, analyzed, documented and reviewed by faculty and graduate students at Eastern Kentucky University. The currently available activation results have been tabulated and reviewed in this report. Approximately 500 spectra have been accumulated for future archival and analysis. The effect of the changing satellite orbit on the activation is reported herein and was calculated using more recent estimates of the flux of Van Allen belt protons.

Laird, C. E.↗
NASA NTRS2009

Space Flight Plasma Data Analysis

This slide presentation reviews a method to analyze the plasma data that is reported on board the International Space station (ISS). The Floating Potential Measurement Unit (FPMU), the role of which is to obtain floating potential and ionosphere plasma measurements for validation of the ISS charging model, assess photo voltaic array variability and interpreting IRI predictions, is composed of four probes: Floating Potential Probe (FPP), Wide-sweep Langmuir Probe (WLP), Narrow-sweep Langmuir Probe (NLP) and the Plasma Impedance Probe (PIP). This gives redundant measurements of each parameter. There are also many 'boxes' that the data must pass through before being captured by the ground station, which leads to telemetry noise. Methods of analysis for the various signals from the different sets are reviewed. There is also a brief discussion of LP analysis of Low Earth Orbit plasma simulation source.

Wright, Kenneth H.↗
NASA NTRS2007

Study Pollution Impacts on Upper-Tropospheric Clouds with Aura, CloudSat, and CALIPSO Data

This viewgraph presentation reviews the impact of pollution on clouds in the Upper Troposphere. Using the data from the Aura Microwave Limb Sounder (MLS), CloudSat, CALIPSO the presentation shows signatures of pollution impacts on clouds in the upper troposphere. The presentation demonstrates the complementary sensitivities of MLS , CloudSat and CALIPSO to upper tropospheric clouds. It also calls for careful analysis required to sort out microphysical changes from dynamical changes.

radar↗
DOE OSTI2020

Electrical Energy Storage Data Submission Guidelines

Energy storage technologies are positioned to play a substantial role in power delivery systems. They are being touted as an effective new resource to maintain reliability and allow for increased penetration of renewable energy. However, due to their relative infancy, there is a lack of knowledge on how these resources truly operate over time. Data analysis can help ascertain the operational and performance characteristics of these emerging technologies. Rigorous testing and data analysis are important for all stakeholders to ensure a safe, reliable system that performs predictably on a macro level. Standardizing testing and analysis approaches to verifying the performance of energy storage devices, equipment, and systems when integrating them into the grid will improve the understanding and benefit of energy storage over time from technical and economic vantage points. Demonstrating the life-cycle value and capabilities of energy storage systems begins with the data the provider supplies for analysis. After review of energy storage data received from several providers, it has become clear that some of these data are inconsistent and incomplete, raising the question of their efficacy for robust analysis. This report reviews and proposes general guidelines such as sampling rates and data points that providers must supply for robust data analysis to take place. Consistent guidelines are the basis of the proper protocol and ensuing standards to (a) reduce the time it takes data to reach those who are providing analysis; (b) allow them to better understand the energy storage installations; and (c) enable them to provide high-quality analysis of the installations. This report is intended to serve as a starting point for what data points should be provided when monitoring. As battery technologies continue to advance and the industry expands, this report will be updated to remain current.

25 ENERGY STORAGE↗
NASA NTRS1978

Aerodynamic derivatives for an oblique wing aircraft estimated from flight data by using a maximum likelihood technique

There are several practical problems in using current techniques with five degree of freedom equations to estimate the stability and control derivatives of oblique wing aircraft from flight data. A technique was developed to estimate these derivatives by separating the analysis of the longitudinal and lateral directional motion without neglecting cross coupling effects. Although previously applied to symmetrical aircraft, the technique was not expected to be adequate for oblique wing vehicles. The application of the technique to flight data from a remotely piloted oblique wing aircraft is described. The aircraft instrumentation and data processing were reviewed, with particular emphasis on the digital filtering of the data. A complete set of flight determined stability and control derivative estimates is presented and compared with predictions. The results demonstrated that the relatively simple approach developed was adequate to obtain high quality estimates of the aerodynamic derivatives of such aircraft.

Maine, R. E.↗
NASA NTRS2016

Summary of LaRC 2-inch Erectable Joint Hardware Heritage Test Data

As the National Space Transportation System (STS, also known as the Space Shuttle) went into service during the early 1980's, NASA envisioned many missions of exploration and discovery that could take advantage of the STS capabilities. These missions included: large orbiting space stations, large space science telescopes and large spacecraft for manned missions to the Moon and Mars. The missions required structures that were significantly larger than the payload volume available on the STS. NASA Langley Research Center (LaRC) conducted studies to design and develop the technology needed to assemble the large space structures in orbit. LaRC focused on technology for erectable truss structures, in particular, the joint that connects the truss struts at the truss nodes. When the NASA research in large erectable space structures ended in the early 1990's, a significant amount of structural testing had been performed on the LaRC 2-inch erectable joint that was never published. An extensive set of historical information and data has been reviewed and the joint structural testing results from this historical data are compiled and summarized in this report.

Dorsey, John T.↗
NASA NTRS2019

Weather Design Considerations for the TASAR Traffic Aware Planner

The Traffic Aware Planner (TAP) is a decision support automation tool for trajectory planning and optimization intended for use on today’s flight deck. Drawing from a variety of on- and off-board data sources, TAP employs a sophisticated trajectory optimization algorithm that provides the aircrew with fuel- and time-saving reroute recommendations that are free of known conflicts with traffic, special use airspace, and severe convective weather. As this kind of weather is a significant part of the pilot’s decision-making process while planning trajectory changes en route, a series of investigations has been conducted into the integration of weather data and associated functionality into the TAP software. This paper reviews the weather data sources and functionality that have been incorporated into TAP to date, along with experience gathered in the course of the design process.

Lewis, Timothy A.↗
NASA NTRS1983

Solar wind variations in the 60-100 year period range: A review

The evidence for and against the reality of a solar wind variation in the period range of 60-100 years is reexamined. Six data sets are reviewed; sunspot numbers, geomagnetic variations, two auroral data sets and two (14)C data sets. These data are proxies for several different aspects of the solar wind and the presence or absence of 60-100 year cyclic behavior in a particular data set does not necessarily imply the presence or absence of this variation in other sets. It was concluded that two different analyses of proxy data for a particular characteristic of the heliospheric solar wind yielded conflicting results. This conflict can be resolved only by future research. It is also definitely confirmed that proxy data for the solar wind in the ecliptic at 1 A.U. undergo a periodic variation with a period of approximately 87 years. The average amplitude and phase of this variation as seen in eleven cycles of proxy data are presented.

Feynman, J.↗
NASA NTRS1988

The search for structure - Object classification in large data sets

Research concerning object classifications schemes are reviewed, focusing on large data sets. Classification techniques are discussed, including syntactic, decision theoretic methods, fuzzy techniques, and stochastic and fuzzy grammars. Consideration is given to the automation of MK classification (Morgan and Keenan, 1973) and other problems associated with the classification of spectra. In addition, the classification of galaxies is examined, including the problems of systematic errors, blended objects, galaxy types, and galaxy clusters.

Kurtz, Michael J.↗
NASA NTRS1989

The use of aircraft laser ranging data for forest mensuration

Laser studies dealing with various aspects of forest canopy measurement are reviewed. Aircraft LIDAR data have been used to estimate canopy density, tree heights, forest volume and biomass, to discriminate terrain units, and to add a height component to multispectral forest cover classifications. Linear comparisons between photogrammetrically-estimated canopy density and laser metrics indicate that the laser explains 45-65 percent of the variation noted in the photo estimates.

Nelson, Ross F.↗
NASA NTRS1993

Minimum Hamiltonian ascent trajectory evaluation (MASTRE) program (update to automatic flight trajectory design, performance prediction, and vehicle sizing for support of shuttle and shuttle derived vehicles) users manual

Documentation for the User Interface Program for the Minimum Hamiltonian Ascent Trajectory Evaluation (MASTRE) is provided. The User Interface Program is a separate software package designed to ease the user input requirements when using the MASTRE Trajectory Program. This document supplements documentation on the MASTRE Program that consists of the MASTRE Engineering Manual and the MASTRE Programmers Guide. The User Interface Program provides a series of menus and tables using the VAX Screen Management Guideline (SMG) software. These menus and tables allow the user to modify the MASTRE Program input without the need for learning the various program dependent mnemonics. In addition, the User Interface Program allows the user to modify and/or review additional input Namelist and data files, to build and review command files, to formulate and calculate mass properties related data, and to have a plotting capability.

Lyons, J. T.↗
DOE OSTI2023

Advances in imaging, scattering, spectroscopy, and machine learning-aided approaches for multiscale characterization of cementitious systems

Recent progress in methods used in the multiscale characterization of cementitious systems is reviewed, focusing on advances in imaging, scattering, and spectroscopy. The review includes relevant applications and developments in machine learning and other data analytics approaches to enhance characterization. Developments in imaging using light and electron microscopy as well as x-ray (i.e., from synchrotron) methods are summarized. Updates include scanning electron microscopy (SEM), transmission electron microscopy (TEM), tomography, and holography. A critical overview of spectroscopy (e.g., MAS NMR, Raman) and scattering (e.g., neutron, x-ray, synchrotron x-ray) methods is provided, and the intersection of these with imaging is developed (e.g., Raman imaging). Additionally, the paper summarizes recent developments in and implementations of state-of-the-art machine-learning algorithms and data analytics methods for automated, systematic, and/or quantitative analyses of image data sets. The review considers but is not limited to the application of these methods for investigating the hydration and microstructure development of cement phases, low-carbon-footprint cements (e.g., limestone calcined clay cements, LC3), environmental interactions (e.g., ASR) and model systems. Finally, the present work provides a critical presentation of advances in characterization methods that link together the composition and multiscale structure of cementitious materials.

42 ENGINEERING↗
DOE OSTI2023

Semi-Automatic Geographic Information System Framework for Creating Photo-Realistic Digital Twin Cities to Support Autonomous Driving Research

Digital twin cities are frequently used in vehicle and traffic simulations to render realistic on-road driving scenarios under various traffic and environmental conditions. These digital twins provide a high-fidelity replica of the physical world (e.g., buildings, roads, infrastructures, traffic) to create three-dimensional (3D) virtual-physical environments to support various emerging vehicle and transportation technologies such as connected and automated vehicles. These virtual environments provide a cost-effective digital proving ground to evaluate, validate, and test emerging technologies that include control algorithms, localization, perception, and sensors. Replicating a real-world traffic scenario in a digital twin using a traditional 3D modeling approach is a time-consuming and labor-intensive effort. Here this paper presents a semi-automated spatial framework to construct realistic 3D digital twin cities to support autonomous driving research using readily available geographic information system (GIS) data and 3D prefabricated (prefab) models. We start with a comprehensive review of geospatial data sources of essential digital entities required in a 3D digital twin city and present an integrated GIS-3D modeling pipeline using customized QGIS/GDAL and Blender scripting in Python. The pipeline outputs are realistic 3D digital twin cities compatible with common vehicle simulation software, such as CARLA and IPG CarMaker. The paper closes with a showcase to demonstrate the quality and usability of a digital twin city created to replicate the Shallowford Road corridor in Chattanooga in both Unity and Unreal engine-based virtual environment. The generated digital twin city can be applied to a hardware-in-the-loop simulation environment with an actual testing vehicle to facilitate autonomous driving research.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2017

Ask-the-expert: Active Learning Based Knowledge Discovery Using the Expert

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the backend. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

software↗