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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Quantitative multielement analysis using high energy particle bombardment

Charged particles ranging in energy from 0.8 to 4.0 MeV are used to induce resonant nuclear reactions, Coulomb excitation (gamma X-rays), and X-ray emission in both thick and thin targets. Quantitative analysis is possible for elements from Li to Pb in complex environmental samples, although the matrix can severely reduce the sensitivity. It is necessary to use a comparator technique for the gamma-rays, while for X-rays an internal standard can be used. A USGS standard rock is analyzed for a total of 28 elements. Water samples can be analyzed either by nebulizing the sample doped with Cs or Y onto a thin formvar film or by extracting the sample (with or without an internal standard) onto ion exchange resin which is pressed into a pellet.

Clark, P. J.↗
NASA NTRS1995

Chromatic Image Analysis For Quantitative Thermal Mapping

Chromatic image analysis system (CIAS) developed for use in noncontact measurements of temperatures on aerothermodynamic models in hypersonic wind tunnels. Based on concept of temperature coupled to shift in color spectrum for optical measurement. Video camera images fluorescence emitted by phosphor-coated model at two wavelengths. Temperature map of model then computed from relative brightnesses in video images of model at those wavelengths. Eliminates need for intrusive, time-consuming, contact temperature measurements by gauges, making it possible to map temperatures on complex surfaces in timely manner and at reduced cost.

Buck, Gregory M.↗
NASA NTRS1993

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists.

Brugel, Edward W.↗
NASA NTRS1993

Visualization techniques to aid in the analysis of multispectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists. Twenty-one examples of the use of visualization for astrophysical data are included with this report. Sixteen publications related to efforts performed during or initiated through work on this project are listed at the end of this report.

Brugel, E. W.↗
NASA NTRS1974

United States manned spacecraft reliability experience

Attention is given to the reliability controls in manned spacecraft programs, taking into account the project Mercury, the Gemini program, the Apollo program, the Skylab program, and the Apollo-Soyuz test project. Reliability controls used in these programs are related to reliability management, parts and materials control, failure mode and effects analysis, reliability quantitative analysis, problem reporting and corrective action control, test control, limited-life control, and milestone reviews. A summary is presented of the major reliability tasks and innovations being used on the Space Shuttle program. Examples of these innovations include improved management techniques and an early identification of specific certification tests.

Kleinknecht, K. S.↗
NASA NTRS1986

Quantitative Schlieren analysis applied to holograms of crystals grown on Spacelab 3

In order to extract additional information about crystals grown in the microgravity environment of Spacelab, a quantitative schlieren analysis technique was developed for use in a Holography Ground System of the Fluid Experiment System. Utilizing the Unidex position controller, it was possible to measure deviation angles produced by refractive index gradients of 0.5 milliradians. Additionally, refractive index gradient maps for any recorded time during the crystal growth were drawn and used to create solute concentration maps for the environment around the crystal. The technique was applied to flight holograms of Cell 204 of the Fluid Experiment System that were recorded during the Spacelab 3 mission on STS 51B. A triglycine sulfate crystal was grown under isothermal conditions in the cell and the data gathered with the quantitative schlieren analysis technique is consistent with a diffusion limited growth process.

Brooks, Howard L.↗
NASA NTRS2006

Fusing Quantitative Requirements Analysis with Model-based Systems Engineering

A vision is presented for fusing quantitative requirements analysis with model-based systems engineering. This vision draws upon and combines emergent themes in the engineering milieu. "Requirements engineering" provides means to explicitly represent requirements (both functional and non-functional) as constraints and preferences on acceptable solutions, and emphasizes early-lifecycle review, analysis and verification of design and development plans. "Design by shopping" emphasizes revealing the space of options available from which to choose (without presuming that all selection criteria have previously been elicited), and provides means to make understandable the range of choices and their ramifications. "Model-based engineering" emphasizes the goal of utilizing a formal representation of all aspects of system design, from development through operations, and provides powerful tool suites that support the practical application of these principles. A first step prototype towards this vision is described, embodying the key capabilities. Illustrations, implications, further challenges and opportunities are outlined.

optimization↗
NASA NTRS1979

Marine chlorophyll a analysis

Quantitative distribution maps of chlorophyll a and other important environmental parameters of coastal zones are prepared by regression analysis of sea-truth data and data collected by aircraft multispectral scanners.

Johnson, R. W.↗
NASA NTRS1994

Experiment K-7-18: Effects of Spaceflight in the Muscle Adductor Longus of Rats Flown in the Soviet Biosatellite Cosmos 2044: Quantitative Autoradiographic Analysis of Gaba (Benzodiazepine) and Muscarinic (Cholinergic) Receptors in the Forebrain of Rats Flown on Cosmos 2044 - Part 2

Quantitative autoradiographic analysis of receptors for GABA and acetylcholine in the forebrain of rats flown on COSMOS 2044 was undertaken as part of a joint US-Soviet study to determine the effects of microgravity on the central nervous system, and in particular on the sensory and motor portions of the forebrain. Changes in binding of these receptors in tissue from animals exposed to microgravity would provide evidence for possible changes in neural processing as a result of exposure to microgravity. Tritium-labelled diazepam and Quinuclidinyl-benzilate (QNB) were used to visualize GABA (benzodiazepine) and muscarinic (cholinergic) receptors, respectively. The density of tritium-labelled radioligands bound to various regions in the forebrain of both flight and control animals were measured from autoradiograms. Data from rats flown in space and from ground-based control animals that were not exposed to microgravity were compared.

Wu, L.↗
DOE OSTI2025

Solar cities: A case study analysis of city-level enablers of expanded solar energy access

Rooftop solar photovoltaic (PV) adoption can benefit households by reducing electricity bills and enhancing energy resiliency. Low and moderate-income (LMI) households have been less likely to adopt PV and experience these benefits in the United States than higher-income households. Adopter income trends are often explored through quantitative analysis with limited explanatory power. Our quantitative analysis only explains around one-third of city-level variation in LMI adoption trends through socioeconomic factors such as median home values and income inequality and PV market factors such as cumulative adoption and incentives. We implement semi-structured interviews in three case studies of cities with relatively high rates of LMI PV adoption to better understand the factors that explain PV adopter income trends. The case studies partly reiterate findings from quantitative analysis, such as the role of PV incentives. The case studies reveal a broader set of LMI adoption drivers that are missed in quantitative analyses. The case studies show how city contexts can affect LMI adoption, such as the role of supportive city governments. The case studies also reveal the importance of partnerships, such as partnerships between city governments and state LMI PV program implementers. Finally, interviewees emphasized the importance of building trust among prospective LMI PV adopters. Interviewees suggested that partnerships, outreach, and consumer protection measures were crucial to building trust in PV installers among LMI households.

Adoption↗
NASA NTRS1974

Neurological applications of man-machine systems analysis

Quantitative descriptions of human control properties are formulated that take into account the dynamics of muscle actuation units, neuromuscular sensor units, and sensory feedback mechanics. Detailed dynamic measurements on neurologically disordered patients are correlated with clinical manifestations of various neurological syndromes to quantify operator behavior.

Mcruer, D. T.↗
NASA NTRSDate not supplied

Quantitative Phenotypic Analysis of Arabidopsis Thaliana Grown in Microgravity Using Soap, an Applied Artificial Intelligence

Phenotypic analysis is an essential step in studying the gravitropic responses and gravitational stress experienced by plants grown in microgravity. Many of the phenotypic traits analyzed in gravitropism studies, such as root length, leaf area, secondary root count, and number of root hairs, currently rely upon manual measurement methods for quantification. However, new advances in data analysis technology using artificial intelligence offer an opportunity for more efficient phenotypic analysis and a reduction of time spent in the data collection phase. In this project, the ability of a new artificially intelligent data collection software, SOAP (Simple Object Access Protocol), to collect and quantify phenotypic traits of Arabidopsis thaliana will be assessed. This project will test the measurements taken by an initial draft of the software. SOAP will take measurements of shoot length, a key phenotype used to assess A. thaliana stress response when grown in microgravity conditions. Shoot length measurements made by SOAP will be compared against a series of manual shoot length measurements. The comparison between the two methods of data measurement will provide valuable insight into the relative accuracy of SOAP and the margin of human error when conducting lab measurements.

Arabidopsis↗
DOE OSTI2026

Affine Transformations to Enable Machine Learning for Semi-Quantitative EDS Analysis

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1991

An infrared analysis of Puppis A

A quantitative analysis of the infrared emission of the supernova remnant (SNR) Puppis A as seen by the Infrared Astronomical Satellite is presented. Physical parameters of the remnant (and the surrounding interstellar medium), including density, mass, temperature, and age are estimated. The infrared spectrum of Puppis A is fit by models of thermal emission from interstellar dust grains which have been swept up into the SNR where they are collisionally heated by the shocked gas. Evidence of an enhanced abundance of very small grains in the interstellar medium near Puppis A, and evidence of their destruction by the advancing blast wave, are found.

Arendt, Richard G.↗
NASA NTRS1997

Convergence Estimates for Multidisciplinary Analysis and Optimization

A quantitative analysis of coupling between systems of equations is introduced. This analysis is then applied to problems in multidisciplinary analysis, sensitivity, and optimization. For the sensitivity and optimization problems both multidisciplinary and single discipline feasibility schemes are considered. In all these cases a "convergence factor" is estimated in terms of the Jacobians and Hessians of the system, thus it can also be approximated by existing disciplinary analysis and optimization codes. The convergence factor is identified with the measure for the "coupling" between the disciplines in the system. Applications to algorithm development are discussed. Demonstration of the convergence estimates and numerical results are given for a system composed of two non-linear algebraic equations, and for a system composed of two PDEs modeling aeroelasticity.

Arian, Eyal↗
NASA NTRS1989

Database for LDV Signal Processor Performance Analysis

A comparative and quantitative analysis of various laser velocimeter signal processors is difficult because standards for characterizing signal bursts have not been established. This leaves the researcher to select a signal processor based only on manufacturers' claims without the benefit of direct comparison. The present paper proposes the use of a database of digitized signal bursts obtained from a laser velocimeter under various configurations as a method for directly comparing signal processors.

Baker, Glenn D.↗
DOE OSTI2024

Quantitative Particle Analysis of Neptunium-237 Oxides: Optimization of MAMA Analysis for Modified Direct Denitration Products

The production of plutonium-238 through irradiation of neptunium-237 ( 237 Np) target materials for the use in radioisotope thermoelectric generators is paramount for continued deep space exploration. This work employs scanning electron microscopy to analyze 237 Np materials coupled with a well-developed image analysis framework (Morphological Analysis for Material Attribution, or MAMA) to determine the degree of micron-scale homogeneity in the materials. This work demonstrated how the quantification of particle characteristics can validate production materials and affirm the qualitative similarities observed in micrographs. The 237 Np oxide particle analysis determined that the materials from five production runs were quantitatively homogenous (significant at α = 0.05) in particle area, circularity, equivalent circular diameter, and ellipse aspect ratio, with two of the sampling dates having statistically significant different means for one of the four characteristics. Furthermore, these metrics not only confirm general homogeneity of the material but also expand the application of MAMA workflows to 237 Np materials, demonstrating the utility of MAMA analysis for a wider breadth of nuclear materials than previously reported. In the open literature, this study is the first time that these microanalytical techniques were applied to 237 Np materials to this degree.

MAMA↗
NASA NTRS2006

Calibration Issues and Operating System Requirements for Electron-Probe Microanalysis

Instrument purchase requirements and dialogue with manufacturers have established hardware parameters for alignment, stability, and reproducibility, which have helped improve the precision and accuracy of electron microprobe analysis (EPMA). The development of correction algorithms and the accurate solution to quantitative analysis problems requires the minimization of systematic errors and relies on internally consistent data sets. Improved hardware and computer systems have resulted in better automation of vacuum systems, stage and wavelength-dispersive spectrometer (WDS) mechanisms, and x-ray detector systems which have improved instrument stability and precision. Improved software now allows extended automated runs involving diverse setups and better integrates digital imaging and quantitative analysis. However, instrumental performance is not regularly maintained, as WDS are aligned and calibrated during installation but few laboratories appear to check and maintain this calibration. In particular, detector deadtime (DT) data is typically assumed rather than measured, due primarily to the difficulty and inconvenience of the measurement process. This is a source of fundamental systematic error in many microprobe laboratories and is unknown to the analyst, as the magnitude of DT correction is not listed in output by microprobe operating systems. The analyst must remain vigilant to deviations in instrumental alignment and calibration, and microprobe system software must conveniently verify the necessary parameters. Microanalysis of mission critical materials requires an ongoing demonstration of instrumental calibration. Possible approaches to improvements in instrument calibration, quality control, and accuracy will be discussed. Development of a set of core requirements based on discussions with users, researchers, and manufacturers can yield documents that improve and unify the methods by which instruments can be calibrated. These results can be used to continue improvements of EPMA.

Carpenter, P.↗