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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

AVIRIS as a tool for carbonatite exploration: Comparison of SPAM and Mbandmap data analysis methods

Data acquired with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) of the Mountain Pass, San Bernadino County, California, area were analyzed to evaluate the use of narrow-band imaging data for carbonatite exploration. Carbonatites are igneous carbonate-rich rocks that are economically important in part because they are the major source for rare-earth minerals. Because the 224 AVIRIS spectral channels have a nominal spectral resolution of 10 nm, narrow absorption features such as those displayed by the rare-earth elements neodymium (Nd) and samarium (Sm) may be detected. The Mountain Pass region encompasses a well-exposed sequence of sedimentary, metamorphic, and igneous rocks, including an alkalic carbonatite intrusion. The carbonatite was emplaced in Precambrian granitic rocks that are fault bounded by a thick suite of Paleozoic, sedimentary rock, predominantly dolomite. The carbonatite stock, the major source of light rare-earth elements (REE) in the United States, affords the opportunity to test AVIRIS capabilities for detecting REE absorption features. Nd-bearing minerals display narrow, sharp and distinctive spectral features at 580, 740, 800, and 870 nm. Minerals bearing Sm display similarly sharp features near 1090, 1250, 1410, and 1550 nm. The more common REE, lanthanum and cerium, do not display absorption features in the visible/near-infrared region in their natural oxidation states.

Kingston, Marguerite J.↗
NASA NTRS1983

Nonlinear effect on modal data analysis method

How the presence of nonlinearities in structural test data can be detected when using modern linear modal data analysis methods is discussed. The extent to which linear algorithms can provide useful information on nonlinear systems was discussed. The modal data analysis method successfully identified the frequency components (but not damping) of the true solution of a nonlinear systems. It was found that the approximate modal parameters of the linear system can be identified by the modal method when low levels of nonlinearities are present. The modal method successfully identified the modal parameters of a linear mode in the presence of a nonlinear response.

Horta, L. G.↗
DOE OSTI2020

Interlaboratory Reproducibility of Contour Method Data Analysis and Residual Stress Calculation

While the contour method for residual stress assessment has developed rapidly, no published study documents its interlaboratory reproducibility. Objective: Here we report an initial reproducibility experiment focused on contour method data analysis and residual stress calculation. The experiment uses surface topography data from a physical process simulation of elastic-plastic beam bending. The simulation provides surface topography, for input to the contour method data analysis, as well as a known residual stress field with 130 MPa peak magnitude. Additionally, to increase realism, noise and specific artifacts are added to the topography data. A group of participants received the topography data (without the known residual stress), independently analyzed the data, and submitted results as a two-dimensional residual stress field. Analysis of submissions provides a group average residual stress field and the spatial distribution of reproducibility standard deviation. The group average residual stress agrees with the known stress in magnitude and spatial trend. The reproducibility standard deviation ranges from 2 to 54 MPa over the measurement plane, with an average of 5.4 MPa. Reproducibility standard deviation is smaller in the cross-section interior (≤ 5 MPa), modest near local extrema in the stress field (5 to 10 MPa), and larger near the cross-section boundaries (10 to 30 MPa). Overall, the largest values of reproducibility standard deviation (up to 54 MPa) occur in limited areas where artifacts had been added to the topography data; while some participants identified and removed these artifacts, some did not, leading to systematic differences that elevated the standard deviation.

42 ENGINEERING↗
DOE OSTI2023

A data analysis method to rapidly characterize gallium concentration in plutonium matrices using LIBS

The processing of actinide samples is a complex and costly endeavor that requires compositional analysis at various stages. Laser-induced breakdown spectroscopy (LIBS) has been used to analyze actinide-containing samples in many nuclear applications including waste management, fuel processing and forensics. The LIBS spectrum obtained from actinide materials are generally extremely complex, exhibiting many thousands of strong emission lines. This makes it difficult to identify other elements within the sample of interest, given the rich and dominant actinide spectrum. Here, in this article, we describe a recent effort to identify and quantify impurities and alloying constituents in plutonium matrices using a hand-held LIBS instrument that is used to rapidly and efficiently measure an emission spectrum from a material sample. We tabulate the emission line positions and intensities of plutonium. We report the development of machine-learning software that can identify gallium and quantify its concentration in plutonium matrices. This work has the potential to provide a rapid and nearly non-destructive technique that allows more confidence in characterizing the composition of materials that are present within complex actinide associated targets. We describe how our LIBS measurements and data analysis methods have successfully quantified the gallium concentration in a variety of samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2011

Sensitivity of Spaceborne and Ground Radar Comparison Results to Data Analysis Methods and Constraints

With the availability of active weather radar observations from space from the Precipitation Radar (PR) on board the Tropical Rainfall Measuring Mission (TR.MM) satellite, numerous studies have been performed comparing PR reflectivity and derived rain rates to similar observations from ground-based weather radars (GR). These studies have used a variety of algorithms to compute matching PR and GR volumes for comparison. Most studies have used a fixed 3-dimensional Cartesian grid centered on the ground radar, onto which the PR and GR data are interpolated using a proprietary approach and/or commonly available GR analysis software (e.g., SPRINT, REORDER). Other studies have focused on the intersection of the PR and GR viewing geometries either explicitly or using a hybrid of the fixed grid and PR/GR common fields of view. For the Dual-Frequency Precipitation Radar (DPR) of the upcoming Global Precipitation Measurement (GPM) mission, a prototype DPR/GR comparison algorithm based on similar TRMM PR data has been developed that defines the common volumes in terms of the geometric intersection of PR and GR rays, where smoothing of the PR and GR data are minimized and no interpolation is performed. The PR and GR volume-averaged reflectivity values of each sample volume are accompanied by descriptive metadata, for attributes including the variability and maximum of the reflectivity within the sample volume, and the fraction of range gates in the sample average having reflectivity values above an adjustable detection threshold (typically taken to be 18 dBZ for the PR). Sample volumes are further characterized by rain type (Stratiform or Convective), proximity to the melting layer, underlying surface (land/water/mixed), and the time difference between the PR and GR observations. The mean reflectivity differences between the PR and GR can differ between data sets produced by the different analysis methods; and for the GPM prototype, by the type of constraints and categorization applied to the data. In this paper, we will show results comparing the 3-D gridded analysis "black box" approach to the GPM prototype volume-matching approach, using matching TRMM PR and WSR-88D ground radar data. The affects of applying data constraints and data categorizations on the volume-matched data to the results will be shown, and explanations of the differences in terms of data and analysis algorithm characteristics will be presented. Implications of the differences to the determination of PR/DPR calibration differences and use of ground radar data to evaluate the PR and DPR attenuation correction algorithms will be discussed.

Morris, Kenneth R.↗
NASA NTRS2024

Preface to the Special Issue on Modeling and Data Analysis Methods for the SMILE mission

The SMILE (Solar wind Magnetosphere Ionosphere Link Explorer) project (http://www.nssc.cas.cn/smile/, https://www.cosmos.esa.int/web/smile/mission) is a joint spacecraft mission of the European Space Agency (ESA) and the Chinese Academy of Sciences (CAS) with an expected launch in 2025. SMILE aims to study the global interactions of solar wind–magnetosphere–ionosphere innovatively by imaging the Earth’s magnetosheath and cusps in soft X-rays and the northern auroral region in ultraviolet (UV) while simultaneously measuring plasma and magnetic field parameters in the solar wind and magnetosheath along a highly-elliptical and highly-inclined orbit. This special issue is composed of 22 articles, presenting recent progress in modeling and data analysis techniques developed for the SMILE mission. In this preface, we categorize the articles into the following seven topics and provide brief summaries: (1) instrument descriptions of the Soft X-ray Imager (SXI), (2) numerical modeling of the X-ray signals, (3) data processing of the X-ray images, (4) boundary tracing methods from the simulated images, (5) physical phenomena and a mission concept related to the scientific goals of SMILE-SXI, (6) studies of the aurora, and (7) ground-based support for SMILE.

SMILE↗
DOE OSTI2021

Novel data analysis method for obtaining better performance from a complex 3D-printed collimator

Additively manufactured scattered beam collimators are increasingly being employed to boost the sample to cell peak signal ratio in high pressure neutron diffraction studies because of manufacturing versatility and performance improvements. We study how the measured diffraction pattern is affected by the presence of a collimator downstream of the sample, and develop a novel protocol that provides more effective background rejection. This protocol takes into account critical performance-determinants that were identified in this study, namely: (i) effectively identifying the collimator pattern on the detector; (ii) understanding the dependence of this pattern on sample and cell composition; and (iii) accurately identifying and differentiating the different regions of the pattern on the detector based on the dependency of the cell or sample and finally (iv) resolving the intensities at regions of the detector where neutrons scattered from the sample are preferentially represented, in order to boost the sample to cell peak signal ratio. Application of this novel analysis protocol is shown to increase the collimator performance over the traditional method.

3D printing↗
DOE OSTI2018

A thought experiment to evaluate a proposed data analysis method

A statistical analysis was recently presented at a DOE review in reference to a particular problem. Here we attempt to capture the essence of this problem with a simple “toy” analog and demonstrate the incorrectness of the presented J figure of merit algorithm. We show that the incorrect usage of J gives PDFs that have erroneous long tails and significantly overestimate the rms deviations relative to those obtained by exact analytic methods. Conversely, a numerical Bayesian analysis gives the correct result.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Erasing the Variable: Empirical Foreground Discovery for Global 21 cm Spectrum Experiments

Spectral measurements of the 21 cm monopole background have the promise of revealing the bulk energetic properties and ionization state of our universe from z approx. 6 − 30. Synchrotron foregrounds are orders of magnitude larger than the cosmological signal, and are the principal challenge faced by these experiments. While synchrotron radiation is thought to be spectrally smooth and described by relatively few degrees of freedom, the instrumental response to bright foregrounds may be much more complex. To deal with such complexities, we develop an approach that discovers contaminated spectral modes using spatial fluctuations of the measured data. This approach exploits the fact that foregrounds vary across the sky while the signal does not. The discovered modes are projected out of each line-of-sight of a data cube. An angular weighting then optimizes the cosmological signal amplitude estimate by giving preference to lower-noise regions. Using this method, we show that it is essential for the passband to be stable to at least approx. 10(exp −4). In contrast, the constraints on the spectral smoothness of the absolute calibration are mainly aesthetic if one is able to take advantage of spatial information. To the extent it is understood, controlling polarization to intensity leakage at the approx. 10(exp −2) level will also be essential to rejecting Faraday rotation of the polarized synchrotron emission. Subject headings: dark ages, reionization, first stars - methods: data analysis - methods: statistical

Variable↗
DOE OSTI2020

The effect of lighting environment on task performance in buildings – A review

The effects of indoor environmental conditions on human health, satisfaction, and performance have been the focal point of research for decades. This paper reviews and summarizes the impact of lighting environment on task performance, specifically for the built environment audience. Existing studies included a variety of performance tests on cognitive performance and perception, visual acuity and reaction, memory, reasoning, and labor productivity. Illuminance, luminance ratio and correlated color temperature were found to affect performance in different ways, reflecting the impact of experimental techniques, conditions, performance evaluation methods used and data analysis methods. These were reviewed and categorized, with discussion on limitations related to sample size, modeling approach, carryover effects and other factors affecting individual differences in performance, with recommendations for future improvement. Although no universal conclusions can be made, in general, task performance seems to improve with higher illuminances, contrast ratios in the range of 7–11:1 (while always making sure that glare will not occur in the space) and higher correlated color temperature, while spectral tuning in the red or blue wavelengths has also shown positive effects. To obtain more generic evidence, future studies should be more consistent in terms of experimental procedures and overall light conditions, and also consider the effects of vertical illuminance, daylight provision/control, and outside views on task performance. Finally, studying performance with multi-factorial designs in a human-centered optimized manner (such as deploying variable lighting scenarios optimized for various tasks) can lead to deeper understanding of lighting effects on task performance, and ultimately to improved lighting design and operation in buildings overall.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods

This data catalog contains information on low temperature geothermal play types. The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) supports the Geothermal Heating and Cooling Geospatial Datasets and Analysis project, conducted by the National Renewable Energy Laboratory (NREL). This project is part of a broader effort to demonstrate the multifaceted value of integrating geothermal power and geothermal heating and cooling technologies into national decarbonization strategies and community energy plans. There is a need to establish baseline low-temperature geothermal resource data sets and evaluate methods for deploying these technologies. This project aims to reduce exploration risk of low temperature geothermal systems by collecting baseline datasets that can be used for Play Fairway Analysis methodologies. This data catalog contains links to publicly available datasets from different sources that can be relevant for the low temperature geothermal systems. This submission contains data catalogs for Alaska, Hawaii, and the Conterminous United States, as well as a technical report on the methods used to classify and asses the geothermal play types.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Scalable Proximity-Based Methods for Large-Scale Analysis of Atom Probe Data

Powered by recent advances in data acquisition technologies, today's state-of-the-art atom probe microscopes yield data sets with sizes ranging from a few million atoms to billions of atoms. Analysis of these atomic data sets within rea-sonable turnaround times is a pressing data analysis challenge for material scientists currently equipped with software systems that do not scale to these massive data sets. Here, we present the shared memory component of a larger ongoing effort to develop a multi-feature data analysis framework capable of analyzing atom probe data of all sizes and scales from desktop multicore machines to large-scale high-performance computing platforms with hybrid (shared and distributed memory) architectures. Our focus here is on a broad class of popular atom probe data analysis methods that rely on core time-consuming k-NN queries. We present a scalable, heuristic algorithm for k-NN queries using three-dimensional range trees. To demonstrate its efficacy, the k-NN algorithm is integrated with two use cases of atom probe data analysis methods and the resulting analysis times are shown to speedup by over 20X on a 32-core Cray XC40 node using workloads up to 8 million atoms, which is already beyond the at-scale capabilities of existing atom probe software. Using this k-NN algorithm, we also introduce a novel parameter estimation method for a class of cluster finding methods, called friends-of-friends (FoF) methods, to completely bypass their expensive pre-processing steps. In each case, we validate the results on a variety of control data sets.

Lu, Hao↗
NASA NTRS1995

SeaWiFS technical report series. Volume 26: Results of the SeaWiFS Data Analysis Round-Robin, July 1994 (DARR-1994)

The accurate determination of upper ocean apparent optical properties (AOP's) is essential for the vicarious calibration of the sea-viewing wide field-of-view sensor (SeaWiFS) instrument and the validation of the derived data products. To evaluate the role that data analysis methods have upon values of derived AOP's, the first Data Analysis Round-Robin (DARR-94) workshop was sponsored by the SeaWiFS Project during 21-23 July, 1994. The focus of this intercomparison study was the estimation of the downwelling irradiance spectrum just beneath the sea surface, E(sub d)(0(sup -), lambda); the upwelling nadir radiance just beneath the sea surface, L(sub u)(0(sup -), lambda); and the vertical profile of the diffuse attenuation coefficient spectrum, K(sub d)(z, lambda). In the results reported here, different methodologies from four research groups were applied to an identical set of 10 spectroradiometry casts in order to evaluate the degree to which data analysis methods influence AOP estimation, and whether any general improvements can be made. The overall results of DARR-94 are presented in Chapter 1 and the individual methods of the four groups are presented in Chapters 2-5. The DARR-94 results do not show a clear winner among data analysis methods evaluated. It is apparent, however, that some degree of outlier rejection is required in order to accurately estimate L(sub u)(0(sup -), lambda) or E(sub d)(0(sup -), lambda). Furthermore, the calculation, evaluation and exploitation of confidence intervals for the AOP determinations needs to be explored. That is, the SeaWiFS calibration and validation problem should be recast in statistical terms where the in situ AOP values are statistical estimates with known confidence intervals.

Hooker, Stanford B.↗