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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 847 records · Page 47

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NASA NTRS1988

DS/LPI autocorrelation detection in noise plus random-tone interference

The authors present and analyze a frequency-noncoherent two-lag autocorrelation statistic for the wideband detection of random BPSK signals in noise-plus-random-multitone interference. It is shown that this detector is quite robust to the presence or absence of interference and its specific parameter values, contrary to the case of an energy detector. The rule assumes knowledge of the data rate and the active scenario under H0. It is concluded that the real-time autocorrelation domain and its samples (lags) are a viable approach for detecting random signals in dense environments.

Hinedi, S.↗

NASA NTRS1990

DS/LPI autocorrelation detection in noise plus random-tone interference

An analysis is presented of a frequency-noncoherent, two-lag autocorrelation statistic for the wideband detection of random binary phase-shift keying (BPSK) signals in noise plus random multitone interference. It is shown that this detector is quite robust to the presence or absence of interference and its specific parameter values contrary to an energy detector. The rule assumes knowledge of the data rate and the active scenario under H0. The purpose of the paper is to promote the real-time autocorrelation domain and its samples (lags) as a viable approach for detecting random signals in dense environments.

Hinedi, Sami↗

DOE OSTI2016

POF-Darts: Geometric adaptive sampling for probability of failure

We introduce a novel technique, POF-Darts, to estimate the Probability Of Failure based on random disk-packing in the uncertain parameter space. POF-Darts uses hyperplane sampling to explore the unexplored part of the uncertain space. We use the function evaluation at a sample point to determine whether it belongs to failure or non-failure regions, and surround it with a protection sphere region to avoid clustering. We decompose the domain into Voronoi cells around the function evaluations as seeds and choose the radius of the protection sphere depending on the local Lipschitz continuity. As sampling proceeds, regions uncovered with spheres will shrink, improving the estimation accuracy. After exhausting the function evaluation budget, we build a surrogate model using the function evaluations associated with the sample points and estimate the probability of failure by exhaustive sampling of that surrogate. In comparison to other similar methods, our algorithm has the advantages of decoupling the sampling step from the surrogate construction one, the ability to reach target POF values with fewer samples, and the capability of estimating the number and locations of disconnected failure regions, not just the POF value. Furthermore, we present various examples to demonstrate the efficiency of our novel approach.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1985

The inference of vector magnetic fields from polarization measurements with limited spectral resolution

A method is presented for recovery of the vector magnetic field and thermodynamic parameters from polarization measurement of photospheric line profiles measured with filtergraphs. The method includes magneto-optic effects and may be utilized on data sampled at arbitrary wavelengths within the line profile. The accuracy of this method is explored through inversion of synthetic Stokes profiles subjected to varying levels of random noise, instrumental wave-length resolution, and line profile sampling. The level of error introduced by the systematic effect of profile sampling over a finite fraction of the 5 minute oscillation cycle is also investigated. The results presented here are intended to guide instrumental design and observational procedure.

Lites, B. W.↗

DOE OSTI2021

Multi-scale investigation on mechanical behavior and microstructural alteration of C-S-H in carbonated Alite paste

Carbonation treatment is a promising option to enhance recycled concrete aggregate (RCA) quality and eventually improve concrete performance. This study investigated the multi-scale mechanical properties of calcium silicate hydrates (C-S-H) in a mature alite paste subjected to accelerated carbonation treatment by testing macro compressive strength, microhardness and nanoindentation. The results show that, carbonation treatment resulted in a heterogeneous distribution of carbonation products in the alite sample. Reinforcement of C-S-H by the randomly precipitated calcite and vaterite crystals prevailed over the nano-structural and compositional alteration of C-S-H induced by carbonation, leading to an increase of nano-indentation modulus at the edge of the sample. Also, the microhardness at the edge zone was markedly higher than that at the core of the carbonated sample. The carbonated peripheral zone with improved nano-scale modulus and microhardness was likely serving as a “hard shell”, contributing to the improved macro compressive strength. The new insights into the multi-scale mechanical properties of carbonated C-S-H contribute to further understanding of the enhanced properties of RCA after carbonation treatment.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Metallographic Characterization of Wrought Depleted Uranium

Metallographic characterization was performed on wrought depleted uranium (DU) samples taken from the longitudinal and transverse orientations from specific locations on two specimens. Characterization of the samples included general microstructure, inclusion analysis, grain size analysis, and microhardness testing. Comparisons of the characterization results were made to determine any differences based on specimen, sample orientation, or sample location. In addition, the characterization results for the wrought DU samples were also compared with data obtained from the metallographic characterization of cast DU samples previously characterized. No differences were observed in microstructure, inclusion size, morphology, and distribution, or grain size in regard to specimen, location, or orientation for the wrought depleted uranium samples. However, a small difference was observed in average hardness with regard to orientation at the same locations within the same specimen. The longitudinal samples were slightly harder than the transverse samples from the same location of the same specimen. This was true for both wrought DU specimens. Comparing the wrought DU sample data with the previously characterized cast DU sample data, distinct differences in microstructure, inclusion size, morphology and distribution, grain size, and microhardness were observed. As expected, the microstructure of the wrought DU samples consisted of small recrystallized grains which were uniform, randomly oriented, and equiaxed with minimal twinning observed in only a few grains. In contrast, the cast DU microstructure consisted of large irregularly shaped grains with extensive twinning observed in most grains. Inclusions in the wrought DU samples were elongated, broken and cracked and light and dark phases were observed in some inclusions. The mean inclusion area percentage for the wrought DU samples ranged from 0.08% to 0.34% and the average density from all wrought DU samples was 1.62E+04/cm 2 . Inclusions in the cast DU samples were equiaxed and intact with light and dark phases observed in some inclusions. The mean inclusion area percentage for the cast DU samples ranged from 0.93% to 1.00% and the average density from all wrought DU samples was 2.83E+04/cm 2 . The average mean grain area from all wrought DU samples was 141 μm 2 while the average mean grain area from all cast DU samples was 1.7 mm2. The average Knoop microhardness from all wrought DU samples was 215 HK and the average Knoop microhardness from all cast DU samples was 264 HK.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1996

Is the Non-Dipole Magnetic Field Random?

Statistical modelling of the Earth's magnetic field B has a long history. In particular, the spherical harmonic coefficients of scalar fields derived from B can be treated as Gaussian random variables. In this paper, we give examples of highly organized fields whose spherical harmonic coefficients pass tests for independent Gaussian random variables. The fact that coefficients at some depth may be usefully summarized as independent samples from a normal distribution need not imply that there really is some physical, random process at that depth. In fact, the field can be extremely structured and still be regarded for some purposes as random. In this paper, we examined the radial magnetic field B(sub r) produced by the core, but the results apply to any scalar field on the core-mantle boundary (CMB) which determines B outside the CMB.

Walker, Andrew D.↗

DOE OSTI2024

Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning

Abstract Electron energy loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) provide detailed information about bonding, distributions and locations of atoms, and their coordination numbers and oxidation states. However, analysis of XAS/EELS data often relies on matching an unknown experimental sample to a series of simulated or experimental standard samples. This limits analysis throughput and the ability to extract quantitative information from a sample. In this work, we have trained a random forest model capable of predicting the oxidation state of copper based on its L-edge spectrum. Our model attains an R 2 score of 0.85 and a root mean square error of 0.24 on simulated data. It has also successfully predicted experimental L-edge EELS spectra taken in this work and XAS spectra extracted from the literature. We further demonstrate the utility of this model by predicting simulated and experimental spectra of mixed valence samples generated by this work. This model can be integrated into a real-time EELS/XAS analysis pipeline on mixtures of copper-containing materials of unknown composition and oxidation state. By expanding the training data, this methodology can be extended to data-driven spectral analysis of a broad range of materials.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Binary pseudorandom array test standard optimized for characterization of large field-of-view optical interferometers

Recently, a technique for calibrating the modulation transfer function (MTF) of a broad variety of metrology instrumentation has been demonstrated. This technique is based on test samples structured as one-dimensional binary pseudo-random (BPR) sequences and two-dimensional BPR arrays (BPRAs). The inherent power spectral density of BPR gratings (sequences) and arrays has a deterministic white-noise-like character that allows direct determination of the MTF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. As such, the BPR samples satisfy the characteristics of a test standard: functionality, ease of specification and fabrication, reproducibility, and low sensitivity to manufacturing error. Here we discuss our recent developments directed to the optimization of the sample design, fabrication, application, and data processing procedures, suitable for thorough characterization of large aperture optical interferometers. Compared with the previous coded-aperture based design, the improved, 'highly randomized' BPRA pattern of the new test standard provides better accuracy and reliability of instrument MTF and aberration characterization, and enables operation optimization of large aperture optical interferometers. We describe the pattern generation algorithm and tests to verify the compliance to desired BPRA topography. The data acquisition and analysis procedures for different applications of the technique are also discussed.

Yashchuk, Valeriy V.↗

DOE OSTI2024

SDSS-IV MaNGA: calibration of astrophysical line-widths in the Hα region using HexPak observations

ABSTRACT We have re-observed $\rm \sim$40 low-inclination, star-forming galaxies from the MaNGA survey (σ ∼ 65 km s−1) at ∼6.5 times higher spectral resolution (σ ∼ 10 km s−1) using the HexPak integral field unit on the WIYN 3.5-m telescope. The aim of these observations is to calibrate MaNGA’s instrumental resolution and to characterize turbulence in the warm interstellar medium and ionized galactic outflows. Here we report the results for the Hα region observations as they pertain to the calibration of MaNGA’s spectral resolution. Remarkably, we find that the previously reported MaNGA line-spread-function (LSF) Gaussian width is systematically underestimated by only 1 per cent. The LSF increase modestly reduces the characteristic dispersion of H ii regions-dominated spectra sampled at 1–2 kpc spatial scales from 23 to 20 km s−1 in our sample, or a 25 per cent decrease in the random-motion kinetic energy. This commensurately lowers the dispersion zeropoint in the relation between line-width and star-formation rate surface-density in galaxies sampled on the same spatial scale. This modest zero-point shift does not appear to alter the power-law slope in the relation between line-width and star-formation rate surface-density. We also show that adopting a scheme whereby corrected line-widths are computed as the square root of the median of the difference in the squared measured line width and the squared LSF Gaussian avoids biases and allows for lower signal-to-noise data to be used reliably.

Chattopadhyay, Sabyasachi↗

DOE OSTI2016

Molecular organization in MAPLE-deposited conjugated polymer thin films and the implications for carrier transport characteristics

The morphological structure of poly(3-hexylthiophene) (P3HT) thin films deposited by both Matrix Assisted Pulsed Laser Evaporation (MAPLE) and solution spin-casting methods are investigated. We found that the MAPLE samples possessed a higher degree of disorder, with random orientations of polymer crystallites along the side-chain stacking, π-π stacking, and conjugated backbone directions. Furthermore, the average molecular orientations and relative degrees of crystallinity of MAPLE-deposited polymer films are insensitive to the chemistries of the substrates onto which they were deposited; this is in stark contrast to the films prepared by the conventional spin-casting technique. In spite of the seemingly unfavorable molecular orientations and the highly disordered morphologies, the in-plane charge carrier transport characteristics of the MAPLE samples are comparable to those of spin-cast samples, exhibiting similar transport activation energies (56 meV versus 54 meV) to those reported in the literature for high mobility polymers.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Highly Textured BaTiO 3 via Templated Grain Growth and Resulting Polarization Reversal Dynamics

Samples of bulk textured polycrystalline BaTiO 3 ceramics were fabricated using a templated grain growth ( TGG ) approach in order to investigate effects of polycrystallinity and texture related to ferroelectric domain reversal under high‐power drive conditions. Barium titanate platelets were formed via two‐step topochemical conversion of bismuth titanate platelets grown via molten salt synthesis, then aligned via tape casting within a matrix of fine BaTiO 3 powder. The coarse‐grained parts showed a high degree of crystallographic texture after sintering. Combined with ceramics of similar density and polycrystallinity, but random orientation and commercial single‐crystal specimens, this sample set enabled direct isolation of crystallographic texture and polycrystallinity as the primary variables for high‐power polarization reversal studies. These studies have also demonstrated a link between grain size and polarization reversal time that strongly suggests that grain boundaries serve effectively as nucleation sites during the ferroelectric switching process.

Meier, William↗

DOE OSTI2020

Estimation of distributions via multilevel Monte Carlo with stratified sampling

We design and implement a novel algorithm for computing a multilevel Monte Carlo (MLMC) estimator of the joint cumulative distribution function (CDF) of a vector-valued quantity of interest in problems with random input parameters and initial conditions. Our approach combines MLMC with stratified sampling of the input sample space by replacing standard Monte Carlo at each level with stratified Monte Carlo initialized with proportionally allocated samples. We show that the resulting stratified MLMC (sMLMC) algorithm is more efficient than its standard MLMC counterpart due to the additional variance reduction provided by the stratification of the random parameter's domain, especially at the coarsest levels. Additional computational cost savings are obtained by smoothing the indicator function with a Gaussian kernel, which proves to be an efficient and robust alternative to recently developed polynomial-based techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Graph Sampling for Visual Analytics

Effectively visualizing large graphs and capturing the statistical properties are two challenging tasks. To aid in these two tasks, many sampling approaches for graph simplification have been proposed, falling into three categories: node sampling, edge sampling, and traversal-based sampling. It is still unknown which approach is the best. We evaluate commonly used graph sampling methods through a combined visual and statistical comparison of graphs sampled at various rates. We conduct our evaluation on three graph models: random graphs, small-world graphs, and scale-free graphs. Initial results indicate that the effectiveness of a sampling method is dependent on the graph model, the size of the graph, and the desired statistical property. This benchmark study can be used as a guideline in choosing the appropriate method for a particular graph sampling task, and the results presented can be incorporated into graph visualization and analysis tools.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1979

Studies in astronomical time series analysis: Modeling random processes in the time domain

Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

Scargle, J. D.↗

NASA NTRS2006

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Pohorille, Andrew↗

DOE OSTI2019

Correcting for fibre assignment incompleteness in the DESI Bright Galaxy Survey

The Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) will be a survey of bright, low-redshift galaxies, which is planned to cover an area of ~14000 square degrees in three passes. Each pass will cover the survey area with ~2000 pointings, each of area ~8 square degrees. The BGS is currently proposed to consist of a bright high priority sample to an r-band magnitude limit r ~ 19.5, with a fainter low priority sample to r ~ 20. The geometry of the DESI fibre positioners in the focal plane of the telescope affects the completeness of the survey and has a non-trivial impact on clustering measurements. Using a BGS mock catalogue, we demonstrate that completeness due to fibre assignment primarily depends on the surface density of galaxies. Completeness is high (>95 per cent) in low-density regions, but very low (<10 per cent) in the centre of massive clusters. We apply the pair inverse probability (PIP) weighting correction to clustering measurements from a BGS mock which has been through the fibre assignment algorithm. This method is only unbiased if it is possible to observe every galaxy pair. To expedite this, we randomly promote a small fraction of the fainter sample to be high priority, and dither the set of tile positions by a small angle. We show that inverse pair weighting combined with angular upweighting provides an unbiased correction to galaxy clustering measurements for the complete three pass survey, and also after one pass, which is highly incomplete.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2003

Estimating Uncertainty in GPCP and TRMM Multi-Satellite Precipitation Estimates

One of the high-priority problems in satellite precipitation estimation is developing algorithms for estimating the errors in precipitation retrievals by individual sensors and subsequent multi-satellite combinations. Classically, we distinguish between "random" and "bias" errors, which do and do not, respectively average to zero over a "big enough" time/space sample. The current operational GPCP and TRMM multi-satellite algorithms are nearly unique in estimating random error for the monthly precipitation estimates from individual sensor systems (including gauge), following Huffman, and then making multi-sensor combinations. No routinely operational global precipitation produces estimates of bias error. Subsequently, a similar scheme has been followed to provide random error estimates for the Multi-satellite Precipitation Analysis (MPA) being computed in real time and after real time for TRMM. The Huffman algorithm for random error is briefly reviewed, including a discussion of the limitations imposed on the algorithm by standard monthly precipitation data sets. Starting from a very simple theoretical treatment of the histogram of precipitation samples in a month, an equation is developed that depends on the estimated average precipitation rate for the month, the number of samples in the month, and two constants. The constants are set separately for each source of precipitation estimate (such as "raingauge") by calibration at selected ground sites. We discuss recent work validating the random error estimates to highlight the successes and limitations of this first-generation approach. We then consider what information is needed from the individual sensor algorithms to facilitate additional accuracy in the estimation of random errors across the time/space span of climate regimes which a global estimation system must handle. In addition, the thorny issue of estimating bias is raised. Finally, the role of error estimates (and the qualitative errors!) in creating combinations of precipitation estimates from different individual sensors is discussed. This issue is particularly important when fine scales in space and time are being considered, say the 0.25 x 0.25-deg 3-hourly estimates in the MPA.

Huffman, G. J.↗