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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Studies of QCD structure in high-energy collisions

”Studies of QCD structure in high-energy collisions” is a research project in theoretical particle physics at Southern Methodist University funded by US DOE Award DE-SC0013681. The award furnished bridge funding for one year (2015/04/15-2016/03/31) between the periods funded by Nadolsky’s DOE Early Career Research Award DE-SC0003870 (in 2010-2015) and a DOE grant DE-SC0010129 for SMU Department of Physics (starting in April 2016). The primary objective of the research is to provide theoretical predictions for Run-2 of the CERN Large Hadron Collider (LHC). The LHC physics program relies on state-of-the-art predictions in the field of quantum chromodynamics. The main effort of our group went into the global analysis of parton distribution functions (PDFs) employed by the bulk of LHC computations. Parton distributions describe internal structure of protons during ultrarelivistic collisions. A new generation of CTEQ parton distribution functions (PDFs), CT14, was released in summer 2015 and quickly adopted by the HEP community. The new CT14 parametrizations of PDFs were obtained using benchmarked NNLO calculations and latest data from LHC and Tevatron experiments. The group developed advanced methods for the PDF analysis and estimation of uncertainties in LHC predictions associated with the PDFs. We invented and refined a new ’meta-parametrization’ technique that streamlines usage of PDFs in Higgs boson production and other numerous LHC processes, by combining PDFs from various groups using multivariate stochastic sampling. In 2015, the PDF4LHC working group recommended to LHC experimental collaborations to use ’meta-parametrizations’ as a standard technique for computing PDF uncertainties. Finally, to include new QCD processes into the global fits, our group worked on several (N)NNLO calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Radiograph and passive data analysis using mixed variable optimization

Disclosed herein are representative embodiments of methods, apparatus, and systems for performing radiography analysis. For example, certain embodiments perform radiographic analysis using mixed variable computation techniques. One exemplary system comprises a radiation source, a two-dimensional detector for detecting radiation transmitted through a object between the radiation source and detector, and a computer. In this embodiment, the computer is configured to input the radiographic image data from the two-dimensional detector and to determine one or more materials that form the object by using an iterative analysis technique that selects the one or more materials from hierarchically arranged solution spaces of discrete material possibilities and selects the layer interfaces from the optimization of the continuous interface data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1983

An interactive Barnes objective map analysis scheme for use with satellite and conventional data

The Barnes (1973) objective map analysis scheme is employed to develop an interactive analysis package for assessing the impact of satellite-derived data on analyses of conventional meteorological data sets. The method permits modification of the values of input parameters in the objective analysis within objectively determined, internally set limits. The effects of the manipulations are rapidly displayed, and methods are included for assimilating the spatially clustered characteristics of satellite data and the various horizontal resolutions of the data types. Data sets from the SESAME rawinsonde wind data with uniform spatial distribution, with the same data set plus satellite cloud motion data, and a data set from the atmospheric sounder radiometer on the GOES satellite were analyzed as examples. The scheme is demonstrated to recover details after two iterations through the data.

Koch, S. E.↗
DOE OSTI2024

Implementing Superresolution of Nonstationary Tides with Wavelets: An Introduction to CWT_Multi

Abstract Tides are often nonstationary due to nonastronomical influences. Investigating variable tidal properties implies a trade-off between separating adjacent frequencies (using long analysis windows) and resolving their time variations (short analysis windows). Previous continuous wavelet transform (CWT) tidal methods resolved tidal species. Here, we present CWT_Multi, a MATLAB code that 1) uses CWT linearity (via the “response coefficient method”) to implement superresolution, i.e., resolving tidal constituents beyond the Rayleigh criterion; 2) provides a Munk–Hasselmann constituent selection criterion appropriate for superresolution; and 3) introduces an objective, time-variable form of inference (“dynamic inference”) based on time-varying data properties. CWT_Multi resolves tidal species on time scales of days, and multiple constituents per species with fortnightly filters. It outputs astronomical phase lags and admittances, analyzes multiple records, and provides power spectra of the signal(s), residual(s), and reconstruction(s); confidence limits; and signal-to-noise ratios. Artificial data and water levels from the Lower Columbia River Estuary (LCRE) and San Francisco Bay Delta (SFBD) are used to test CWT_Multi and compare it to harmonic analysis programs NS_Tide and UTide. CWT_Multi provides superior reconstruction, detiding, dynamic analysis utility, and time resolution of constituents (but with broader confidence limits). Dynamic inference resolves closely spaced constituents (like K 1 , S 1 , and P 1 ) on fortnightly time scales, quantifying impacts of diel power peaking (with a 24-h period, like S 1 ) on water levels in the LCRE. CWT_Multi also helps quantify the impacts of high flows and a salt barrier closing on tidal properties in the SFBD. On the other hand, CWT_Multi does not excel at prediction, and results depend on analysis details, as for any method applied to nonstationary data. Significance Statement Ocean tides, especially in coastal and estuarine systems, are often nonstationary, in the sense that the mean and standard deviation of tidal properties vary over time, usually in response to some nontidal process. We introduce here a MATLAB code, CWT_Multi, that uses wavelet transforms to resolve both tidal species and constituents on time scales from a few days to months. Our code accommodates multiple scalar time series and has typical tidal analysis features like constituent selection and inference, plus two forms of uncertainty analyses. It is flexible, allowing the user to adapt analysis properties to diverse datasets. CWT_Multi is applicable to many problems involving time-variable tides, including sea level rise, compound flooding, sediment transport, and wetland habitat analyses. Application to vector data is a straightforward extension, but further development of our uncertainty analysis is merited. Because nonstationary tidal analysis is rapidly advancing, we also define the features of a “well-formed” analysis code.

Lobo, Matthew↗
NASA NTRS1990

New interplanetary proton fluence model

A new predictive engineering model for the interplanetary fluence of protons with above 10 MeV and above 30 MeV is described. The data set used is a combination of observations made from the earth's surface and from above the atmosphere between 1956 and 1963 and observations made from spacecraft in the vicinity of earth between 1963 and 1985. The data cover a time period three times as long as the period used in earlier models. With the use of this data set the distinction between 'ordinary proton events' and 'anomalously large events' made in earlier work disappears. This permitted the use of statistical analysis methods developed for 'ordinary events' on the entire data set. The greater than 10 MeV fluences at 1 AU calculated with the new model are about twice those expected on the basis of models now in use. At energies above 30 MeV, the old and new models agree. In contrast to earlier models, the results do not depend critically on the fluence from any one event and are independent of sunspot number. Mission probability curves derived from the fluence distribution are presented.

Feynman, Joan↗
NASA NTRS1990

Cloud-tracked winds from Pioneer Venus OCPP images

Results are presented on the analysis of the Pioneer Venus Orbiter Cloud Photopolarimeter (OCPP) UV images, covering 80-day periods from 1979 to 1985. The analysis provides a method for determining wind speeds at the cloud level, from the motions of cloud UV features. Data used for tracking the cloud feature motions are described along with the analysis method. The results identified four wave modes: a diurnal solar tide, a semidiurnal solar tide, a '4-day equatorial' wave, and a '5-day midlatitude' wave. The features of these wave modes are described.

Rossow, William B.↗
DOE OSTI2016

Measurements of Neutron Importance Distribution in {sup 235}U Fast Critical Reactor

The reactor physics related integral experiments are significant to criticality safety analysis and the design of the next generation nuclear system. Measurements of parameters such as prompt neutron decay constant α, prompt neutron generation time Λ, effective delayed neutron fraction β{sub eff}, neutron importance distribution, etc., can provide data for the verification of calculation methods, computer codes and cross-section data in criticality safety analysis and test the design of new reactors. Among these parameters, neutron importance distribution has its unique value. Beside verification and validation of nuclear data, computer codes, and simulation methods, the experimental results of neutron importance distribution are also useful to the correcting of the spatial effects in Rossi-α measurement, which is based on point-reactor neutron kinetics. The relative neutron importance distribution experiments were performed on the {sup 235}U fast critical reactor of China Academy of Engineering Physics (CAEP). The key experimental objective was to obtain the importance distribution data for nuclear data validation and criticality safety analysis. We demonstrate in this paper the experiment and the data analysis. {sup 252}Cf neutron importance spatial distributions in the diametral hole of a depleted uranium reflected {sup 235}U fast critical reactor were measured. The evaluated uncertainties of the experiment data were varying with the source location but within 1.5% ranges in all. The experiment results can provide useful data for applications like nuclear data validation and the determination of rectification factor R of Rossi-a measurements. However, the experimental uncertainties are not satisfying and can be further reduced by using a {sup 252}Cf source with much higher intensity, recording more precisely the absolute position of the neutron source, and carrying out the experiment in more shallow subcritical states in which the system multiplication is larger. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1976

Analysis of pressure distortion testing

The development of a distortion methodology, method D, was documented, and its application to steady state and unsteady data was demonstrated. Three methodologies based upon DIDENT, a NASA-LeRC distortion methodology based upon the parallel compressor model, were investigated by applying them to a set of steady state data. The best formulation was then applied to an independent data set. The good correlation achieved with this data set showed that method E, one of the above methodologies, is a viable concept. Unsteady data were analyzed by using the method E methodology. This analysis pointed out that the method E sensitivities are functions of pressure defect level as well as corrected speed and pattern.

Koch, K. E.↗
DOE OSTI2017

Hyperspectral Image Classification Using Graph Clustering Methods

Hyperspectral imagery is a challenging modality due to the dimension of the pixels which can range from hundreds to over a thousand frequencies depending on the sensor. Most methods in the literature reduce the dimension of the data using a method such as principal component analysis, however this procedure can lose information. More recently methods have been developed to address classification of large datasets in high dimensions. This paper presents two classes of graph-based classification methods for hyperspectral imagery. Using the full dimensionality of the data, we consider a similarity graph based on pairwise comparisons of pixels. The graph is segmented using a pseudospectral algorithm for graph clustering that requires information about the eigenfunctions of the graph Laplacian but does not require computation of the full graph. We develop a parallel version of the Nyström extension method to randomly sample the graph to construct a low rank approximation of the graph Laplacian. With at most a few hundred eigenfunctions, we can implement the clustering method designed to solve a variational problem for a graph-cut-based semi-supervised or unsupervised classification problem. We implement OpenMP directive-based parallelism in our algorithms and show performance improvement and strong, almost ideal, scaling behavior. The method can handle very large datasets including a video sequence with over a million pixels, and the problem of segmenting a data set into a pre-determined number of classes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

BeyondPlanck X. Bandpass and beam leakage corrections

We discuss the treatment of bandpass and beam leakage corrections in the Bayesian BeyondPlanck CMB analysis pipeline as applied to the Planck LFI measurements. As a preparatory step, we first apply three corrections to the nominal LFI bandpass profiles including removal of a known systematic effect in the ground measuring equipment at 61 GHz; smoothing of standing wave ripples; and edge regularization. The main net impact of these modifications is an overall shift in the 70 GHz bandpass of +0.6 GHz; we argue that any analysis of LFI data products, either from Planck or BeyondPlanck, should use these new bandpasses. In addition, we fit a single free bandpass parameter for each radiometer of the form Δ i = Δ 0 + $δ$ i , where Δ 0 represents an absolute frequency shift per frequency band and $δ$i is a relative shift per detector. The absolute correction is only fitted at 30 GHz with a full $\chi$ 2 -based likelihood, resulting in a correction of Δ 30 = 0.24 ± 0.03 GHz. The relative corrections are fitted using a spurious map approach, fundamentally similar to the method pioneered by the WMAP team, but without introducing many additional degrees of freedom. All bandpass parameters are sampled using a standard Metropolis sampler within the main BeyondPlanck Gibbs chain, and bandpass uncertainties are thus propagated to all other data products in the analysis. In total, we find that our bandpass model significantly reduces leakage effects. For beam leakage corrections, we adopt the official Planck LFI beam estimates without additional degrees of freedom, and only marginalize over the underlying sky model. We note that this is the first-time leakage from beam mismatch has been included for Planck LFI maps.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2007

Stepwise Regression Analysis of MDOE Balance Calibration Data Acquired at DNW

This paper reports a comparison of two experiment design methods applied in the calibration of a strain-gage balance. One features a 734-point test matrix in which loads are varied systematically according to a method commonly applied in aerospace research and known in the literature of experiment design as One Factor At a Time (OFAT) testing. Two variations of an alternative experiment design were also executed on the same balance, each with different features of an MDOE experiment design. The Modern Design of Experiments (MDOE) is an integrated process of experiment design, execution, and analysis applied at NASA's Langley Research Center to achieve significant reductions in cycle time, direct operating cost, and experimental uncertainty in aerospace research generally and in balance calibration experiments specifically. Personnel in the Instrumentation and Controls Department of the German Dutch Wind Tunnels (DNW) have applied MDOE methods to evaluate them in the calibration of a balance using an automated calibration machine. The data have been sent to Langley Research Center for analysis and comparison. This paper reports key findings from this analysis. The chief result is that a 100-point calibration exploiting MDOE principles delivered quality comparable to a 700+ point OFAT calibration with significantly reduced cycle time and attendant savings in direct and indirect costs. While the DNW test matrices implemented key MDOE principles and produced excellent results, additional MDOE concepts implemented in balance calibrations at Langley Research Center are also identified and described.

DeLoach, RIchard↗
DOE OSTI2017

Novel Histogram Based Unsupervised Classification Technique to Determine Natural Classes From Biophysically Relevant Fit Parameters to Hyperspectral Data

Hyperspectral image analysis has benefited from an array of methods that take advantage of the increased spectral depth compared to multispectral sensors; however, the focus of these developments has been on supervised classification methods. Lack of a priori knowledge regarding land cover characteristics can make unsupervised classification methods preferable under certain circumstances. An unsupervised classification technique is presented in this paper that utilizes physically relevant basis functions to model the reflectance spectra. These fit parameters used to generate the basis functions allow clustering based on spectral characteristics rather than spectral channels and provide both noise and data reduction. Histogram splitting of the fit parameters is then used as a means of producing an unsupervised classification. Unlike current unsupervised classification techniques that rely primarily on Euclidian distance measures to determine similarity, the unsupervised classification technique uses the natural splitting of the fit parameters associated with the basis functions creating clusters that are similar in terms of physical parameters. The data set used in this work utilizes the publicly available data collected at Indian Pines, Indiana. This data set provides reference data allowing for comparisons of the efficacy of different unsupervised data analysis. The unsupervised histogram splitting technique presented in this paper is shown to be better than the standard unsupervised ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. Finally, this improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA.

58 GEOSCIENCES↗
DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Long-range collectivity in small collision systems with two- and four-particle correlations at STAR

New STAR measurements of two- and four-particle (c 2 {4}) azimuthal angle correlations are reported for p+Au collisions at 200 GeV and d+Au collisions from 19.6 to 200 GeV. A negative c 2 {4}, consistent with collective anisotropic flow, is observed in high multiplicity d+Au events at 62.4 and 200 GeV where the statistical significance of the data allows an analysis. A template fitting method, employed to subtract non-flow contributions to the two-particle correlations, allows the extraction of the anisotropy coefficients (ν 2 ) for these systems at their respective energies. The ν 2 results for different energies show a common dependence on the charged particle multiplicity density ( < dN ch /dη > ), which provide important insight on the nature of collective behavior in small collision systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Comparative analysis of the methods for quantitative determination of water content in skin from diffuse reflectance spectroscopy data

The predictive properties of methods aimed for estimating the water content in skin from the spectral diffuse reflection characteristics near the water absorption line in the near-IR spectral range are analysed. Numerical simulation data, experimental data on diffuse reflection from human skin phantoms, and data from the reference data set of human skin reflectance spectra are used to consider the possibility of gaining additional information about the water distribution in skin. The influence of variations in the scattering coefficient and oxyhaemoglobin concentration on the water content estimates is investigated. (paper)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Reverberation mapping of the Seyfert 1 galaxy NGC 7469

A large reverberation-mapping study of the Seyfert 1 galaxy NGC 7469 has yielded emission-line lags for Hβ λ4861 and He II λ4686 and a central black hole mass measurement M {sub BH} ≈ 1 × 10{sup 7} M {sub ☉}, consistent with previous measurements. A very low level of variability during the monitoring campaign precluded meeting our original goal of recovering velocity-delay maps from the data, but with the new Hβ measurement, NGC 7469 is no longer an outlier in the relationship between the size of the Hβ-emitting broad-line region and the luminosity of the active galactic nucleus. It was necessary to detrend the continuum and Hβ and He II λ4686 line light curves and those from archival UV data for different time-series analysis methods to yield consistent results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Accurate gravities of F, G, and K stars from high resolution spectra without external constraints

We demonstrate a new procedure to derive accurate and precise surface gravities from high resolution spectra without the use of external constraints. Our analysis utilizes Spectroscopy Made Easy with robust spectral line constraints and uses an iterative process to mitigate degeneracies in the fitting process. We adopt an updated radiative transfer code, a new treatment for neutral perturber broadening, a line list with multiple gravity constraints and separate fitting for global stellar properties and abundance determinations. To investigate the sources of temperature dependent trends in determining log g noted in previous studies, we obtained Keck HIRES spectra of 42 Kepler asteroseismic stars. In comparison to asteroseismically determined log g our spectroscopic analysis has a constant offset of 0.01 dex with a rms scatter of 0.05 dex. We also analyzed 30 spectra which had published surface gravities determined using the a/R{sub ∗} technique from planetary transits and found a constant offset of 0.06 dex and rms scatter of 0.07 dex. The two samples covered effective temperatures between 5000 and 6700 K with log g between 3.7 and 4.6.

79 ASTRONOMY AND ASTROPHYSICS↗