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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Fitting FFT-derived spectra: Theory, tool, and application to solar radio spike decomposition

Spectra derived from fast Fourier transform (FFT) analysis of time-domain data intrinsically contain statistical fluctuations whose distribution depends on the number of accumulated spectra contributing to a measurement. The tail of this distribution, which is essential for separating the true signal from the statistical fluctuations, deviates noticeably from the normal distribution for a finite number of accumulations. In this paper, we develop a theory to properly account for the statistical fluctuations when fitting a model to a given accumulated spectrum. The method is implemented in software for the purpose of automatically fitting a large body of such FFT-derived spectra. We apply this tool to analyze a portion of a dense cluster of spikes recorded by our FASR Subsystem Testbed instrument during a record-breaking event that occurred on 2006 December 6. The outcome of this analysis is briefly discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Statistical Properties of SGR 1900+14 Bursts

We study the statistics of soft gamma repeater (SGR) bursts, using a data base of 187 events detected with BATSE and 837 events detected with RXTE PCA, all from SGR 1900+14 during its 1998-1999 active phase. we find that the fluence or energy distribution of bursts is consistent with a power law of index 1.66, over 4 orders of magnitude. This scale-free distribution resembles the Gutenberg-Richter Law for earthquakes, and gives evidence for self-organized criticality in SGRS. The distribution of time intervals between successive bursts from SGR 1900+14 is consistent with a log-normal distribution. There is no correlation between burst intensity and the waiting times till the next burst, but there is some evidence for a correlation between burst intensity and the time elapsed since the previous burst. We also find a correlation between the duration and the energy of the bursts, but with significant scatter. In all these statistical properties, SGR bursts resemble earthquakes and solar flares more closely than they resemble any known accretion-powered or nuclear-powered phenomena. Thus our analysis lends support to the hypothesis that the energy source for SGR bursts is internal to the neutron star, and plausibly magnetic.

Gogus, Ersin↗
DOE OSTI2013

The Non-Gaussian Nature of Prostate Motion Based on Real-Time Intrafraction Tracking

Purpose: The objective of this work is to test the validity of the Gaussian approximation for prostate motion through characterization of its spatial distribution. Methods and Materials: Real-time intrafraction prostate motion was observed using Calypso 4-dimensional (4D) nonradioactive electromagnetic tracking system. We report the results from a total of 1024 fractions from 31 prostate cancer patients. First, the correlation of prostate motion in right/left (RL), anteroposterior (AP), and superoinferior (SI) direction were determined using Pearson's correlation of coefficient. Then the spatial distribution of prostate motion was analyzed for individual fraction, individual patient including all fractions, and all patients including all fractions. The displacement in RL, AP, SI, oblique, or total direction is fitted into a Gaussian distribution, and a Lilliefors test was used to evaluate the validity of the hypothesis that the displacement is normally distributed. Results: There is high correlation in AP/SI direction (61% of fractions with medium or strong correlation). This is consistent with the longitudinal oblique motion of the prostate, and likely the effect from respiration on an organ confined within the genitourinary diaphragm with the rectum sitting posteriorly and bladder sitting superiorly. In all directions, the non-Gaussian distribution is more common for individual fraction, individual patient including all fractions, and all patients including all fractions. The spatial distribution of prostate motion shows an elongated shape in oblique direction, indicating a higher range of motion in the AP and SI directions. Conclusions: Our results showed that the prostate motion is highly correlated in AP and SI direction, indicating an oblique motion preference. In addition, the spatial distribution of prostate motion is elongated in an oblique direction, indicating that the organ motion dosimetric modeling using Gaussian kernel may need to be modified to account for the particular organ motion character of prostate.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Effect of rapid thermal annealing temperature on the dispersion of Si nanocrystals in SiO{sub 2} matrix

Effect of rapid thermal annealing temperature on the dispersion of silicon nanocrystals (Si-NC’s) embedded in SiO{sub 2} matrix grown by atom beam sputtering (ABS) method is reported. The dispersion of Si NCs in SiO{sub 2} is an important issue to fabricate high efficiency devices based on Si-NC’s. The transmission electron microscopy studies reveal that the precipitation of excess silicon is almost uniform and the particles grow in almost uniform size upto 850 °C. The size distribution of the particles broadens and becomes bimodal as the temperature is increased to 950 °C. This suggests that by controlling the annealing temperature, the dispersion of Si-NC’s can be controlled. The results are supported by selected area diffraction (SAED) studies and micro photoluminescence (PL) spectroscopy. The discussion of effect of particle size distribution on PL spectrum is presented based on tight binding approximation (TBA) method using Gaussian and log-normal distribution of particles. The study suggests that the dispersion and consequently emission energy varies as a function of particle size distribution and that can be controlled by annealing parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Simultaneous observations of giant pulses from the crab pulsar, with the Murchison Widefield Array and Parkes radio telescope: Implications for the giant pulse emission mechanism

We report on observations of giant pulses from the Crab pulsar performed simultaneously with the Parkes radio telescope and the incoherent combination of the Murchison Widefield Array (MWA) antenna tiles. The observations were performed over a duration of approximately one hour at a center frequency of 1382 MHz with 340 MHz bandwidth at Parkes, and at a center frequency of 193 MHz with 15 MHz bandwidth at the MWA. Our analysis has led to the detection of 55 giant pulses at the MWA and 2075 at Parkes above a threshold of 3.5σ and 6.5σ, respectively. We detected 51% of the MWA giant pulses at the Parkes radio telescope, with spectral indices in the range of −3.6>α>−4.9 (S{sub ν}∝ν{sup α}). We present a Monte Carlo analysis supporting the conjecture that the giant pulse emission in the Crab is intrinsically broadband, the less than 100% correlation being due to the relative sensitivities of the two instruments and the width of the spectral index distribution. Our observations are consistent with the hypothesis that the spectral index of giant pulses is drawn from normal distribution of standard deviation 0.6, but with a mean that displays an evolution with frequency from −3.00 at 1382 MHz, to −2.85 at 192 MHz.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

An Empirical State Error Covariance Matrix Orbit Determination Example

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance is suspect. In its most straight forward form, the technique only requires supplemental calculations to be added to existing batch estimation algorithms. In the current problem being studied a truth model making use of gravity with spherical, J2 and J4 terms plus a standard exponential type atmosphere with simple diurnal and random walk components is used. The ability of the empirical state error covariance matrix to account for errors is investigated under four scenarios during orbit estimation. These scenarios are: exact modeling under known measurement errors, exact modeling under corrupted measurement errors, inexact modeling under known measurement errors, and inexact modeling under corrupted measurement errors. For this problem a simple analog of a distributed space surveillance network is used. The sensors in this network make only range measurements and with simple normally distributed measurement errors. The sensors are assumed to have full horizon to horizon viewing at any azimuth. For definiteness, an orbit at the approximate altitude and inclination of the International Space Station is used for the study. The comparison analyses of the data involve only total vectors. No investigation of specific orbital elements is undertaken. The total vector analyses will look at the chisquare values of the error in the difference between the estimated state and the true modeled state using both the empirical and theoretical error covariance matrices for each of scenario.

Frisbee, Joseph H., Jr.↗
DOE OSTI2019

ASSESSMENT OF NORMALITY FOR CRITICALITY SAFETY BIAS AND BIAS UNCERTAINTY CALCULATION

The single-sided lower tolerance factors frequently used for non-trending assessment of the validation bias and bias uncertainty are sensitive to departures from normality. When used properly, the tolerance limits ensure that an appropriate fraction of the true population of applicable critical experiments lies above the calculated lower tolerance limit with the required statistical confidence level. One condition necessary to ensure that the appropriate proportion of the true population of keff values in the validation suite lies above the lower tolerance limit is that the assumption that the normality of the underlying population of critical experiments is valid or conservative.This paper discusses various methods used to assess whether the assumption that the validation suite may be treated as a random sample drawn from a normal distribution is acceptable. Techniques for assessing the validity of this underlying assumption include common omnibus hypothesis tests for normality, assessment of sample skewness and kurtosis of the validation suite, and graphical techniques. These techniques are used to assess the nature and potential conservatism/nonconservatism imparted by various departures from normality where possible. A review of hypothesis testing is also presented to frame the discussion of omnibus normality tests. Additionally, two cases are analysed with these techniques to provide an example of how they should be implemented.

Clarity, Justin↗
DOE OSTI2022

Inference for Nonparanormal Partial Correlation via Regularized Rank-Based Nodewise Regression

Abstract Partial correlation is a common tool in studying conditional dependence for Gaussian distributed data. However, partial correlation being zero may not be equivalent to conditional independence under non-Gaussian distributions. In this paper, we propose a statistical inference procedure for partial correlations under the high-dimensional nonparanormal (NPN) model where the observed data are normally distributed after certain monotone transformations. The NPN partial correlation is the partial correlation of the normal transformed data under the NPN model, which is a more general measure of conditional dependence. We estimate the NPN partial correlations by regularized nodewise regression based on the empirical ranks of the original data. A multiple testing procedure is proposed to identify the nonzero NPN partial correlations. The proposed method can be carried out by a simple coordinate descent algorithm for lasso optimization. It is easy-to-implement and computationally more efficient compared to the existing methods for estimating NPN graphical models. Theoretical results are developed to show the asymptotic normality of the proposed estimator and to justify the proposed multiple testing procedure. Numerical simulations and a case study on brain imaging data demonstrate the utility of the proposed procedure and evaluate its performance compared to the existing methods. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Numerical simulations of turbulent molecular clouds regulated by radiation feedback forces. I. Star formation rate and efficiency

Radiation feedback from stellar clusters is expected to play a key role in setting the rate and efficiency of star formation in giant molecular clouds. To investigate how radiation forces influence realistic turbulent systems, we have conducted a series of numerical simulations employing the Hyperion radiation hydrodynamics solver, considering the regime that is optically thick to ultraviolet and optically thin to infrared radiation. Our model clouds cover initial surface densities between Σ{sub cl,0}∼10--300 M{sub ⊙} pc{sup −2}, with varying initial turbulence. We follow them through turbulent, self-gravitating collapse, star cluster formation, and cloud dispersal by stellar radiation. All our models display a log-normal distribution of gas surface density Σ; for an initial virial parameter α{sub vir,0}=2, the log-normal standard deviation is σ{sub lnΣ}=1--1.5 and the star formation rate coefficient ε{sub ff, ρ-bar }=0.3--0.5, both of which are sensitive to turbulence but not radiation feedback. The net star formation efficiency (SFE) ε{sub final} increases with Σ{sub cl,0} and decreases with α{sub vir,0}. We interpret these results via a simple conceptual framework, whereby steady star formation increases the radiation force, such that local gas patches at successively higher Σ become unbound. Based on this formalism (with fixed σ{sub lnΣ}), we provide an analytic upper bound on ε{sub final}, which is in good agreement with our numerical results. The final SFE depends on the distribution of Eddington ratios in the cloud and is strongly increased by the turbulent compression of gas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Angular Momentum Transfer and Fractional Moment of Inertia in Pulsar Glitches

We use the Jodrell Bank Observatory glitch database containing 472 glitches from 165 pulsars to investigate the angular momentum transfer during rotational glitches in pulsars. Our emphasis is on pulsars with at least five glitches, of which there are 26 that exhibit 261 glitches in total. This paper identifies four pulsars in which the angular momentum transfer, after many glitches, is almost linear with time. The Lilliefore test on the cumulative distribution of glitch spin-up sizes in these glitching pulsars shows that glitch sizes in 12 pulsars are normally distributed, suggesting that their glitches originate from the same momentum reservoir. In addition, the distribution of the fractional moment of inertia (i.e., the ratio of the moment of inertia of neutron star components that are involved in the glitch process) have a single mode, unlike the distribution of fractional glitch size (Δ ν / ν ), which is usually bimodal. The mean fractional moment of inertia in the glitching pulsars we sampled has a very weak correlation with the pulsar spin properties, thereby supporting a neutron star interior mechanism for the glitch phenomenon.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1954

A study of the application of power-spectral methods of generalized harmonic analysis to gust loads on airplanes

The applicability of some results from the theory of generalized harmonic analysis (or power-spectral analysis) to the analysis of gust loads on airplanes in continuous rough air is examined. The general relations for linear systems between power spectrums of a random input disturbance and an output response are used to relate the spectrum of airplane load in rough air to the spectrum of atmospheric gust velocity. The power spectrum of loads is shown to provide a measure of the load intensity in terms of the standard deviation (root mean square) of the load distribution for an airplane in flight through continuous rough air. For the case of a load output having a normal distribution, which appears from experimental evidence to apply to homogeneous rough air, the standard deviation is shown to describe the probability distribution of loads or the proportion of total time that the load has given values. Thus, for airplane in flight through homogeneous rough air, the probability distribution of loads may be determined from a power-spectral analysis. In order to illustrate the application of power-spectral analysis to gust-load analysis and to obtain an insight into the relations between loads and airplane gust-response characteristics, two selected series of calculations are presented. The results indicate that both methods of analysis yield results that are consistent to a first approximation.

Press, Harry↗
DOE OSTI2016

The ELM Survey. VII. Orbital properties of low-mass white dwarf binaries

We present the discovery of 15 extremely low-mass (5<logg<7) white dwarf (WD) candidates, 9 of which are in ultra-compact double-degenerate binaries. Our targeted extremely low-mass Survey sample now includes 76 binaries. The sample has a lognormal distribution of orbital periods with a median period of 5.4 hr. The velocity amplitudes imply that the binary companions have a normal distribution of mass with 0.76 M{sub ⊙} mean and 0.25 M{sub ⊙} dispersion. Thus extremely low-mass WDs are found in binaries with a typical mass ratio of 1:4. Statistically speaking, 95% of the WD binaries have a total mass below the Chandrasekhar mass, and thus are not type Ia supernova progenitors. Yet half of the observed binaries will merge in less than 6 Gyr due to gravitational wave radiation; probable outcomes include single massive WDs and stable mass transfer AM CVn binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

The asymptotic distribution of maxima in bivariate samples

The joint distribution (as n tends to infinity) of the maxima of a sample of n independent observations of a bivariate random variable (X,Y) is studied. A method is developed for deriving the asymptotic distribution of the maxima, assuming that X and Y possess asymptotic extreme-value distributions and that the probability element dF(x,y) can be expanded in a canonical series. Applied both to the bivariate normal distribution and to the bivariate gamma and compound correlated bivariate Poisson distributions, the method shows that maxima from all these distributions are asymptotically uncorrelated.

Campbell, J. W.↗
NASA NTRS1975

Design, development and manufacture of a breadboard radio frequency mass gauging system

The feasibility of the RF gauging mode, counting technique was demonstrated for gauging liquid hydrogen and liquid oxygen under all attitude conditions. With LH2, it was also demonstrated under dynamic fluid conditions, in which the fluid assumes ever changing positions within the tank, that the RF gauging technique on the average provides a very good indication of mass. It is significant that the distribution of the mode count data at each fill level during dynamic LH2 and LOX orientation testing does approach a statistical normal distribution. Multiple space-diversity probes provide better coupling to the resonant modes than utilization of a single probe element. The variable sweep rate generator technique provides a more uniform mode versus time distribution for processing.

Source record↗
NASA NTRS2006

Shielding Effectiveness in a Two-Dimensional Reverberation Chamber Using Finite-Element Techniques

Reverberation chambers are attaining an increased importance in determination of electromagnetic susceptibility of avionics equipment. Given the nature of the variable boundary condition, the ability of a given source to couple energy into certain modes and the passband characteristic due the chamber Q, the fields are typically characterized by statistical means. The emphasis of this work is to apply finite-element techniques at cutoff to the analysis of a two-dimensional structure to examine the notion of shielding-effectiveness issues in a reverberating environment. Simulated mechanical stirring will be used to obtain the appropriate statistical field distribution. The shielding effectiveness (SE) in a simulated reverberating environment is compared to measurements in a reverberation chamber. A log-normal distribution for the SE is observed with implications for system designers. The work is intended to provide further refinement in the consideration of SE in a complex electromagnetic environment.

Bunting, Charles F.↗
NASA NTRS1979

CLASSY: An adaptive maximum likelihood clustering algorithm

The CLASSY clustering method alternates maximum likelihood iterative techniques for estimating the parameters of a mixture distribution with an adaptive procedure for splitting, combining, and eliminating the resultant components of the mixture. The adaptive procedure is based on maximizing the fit of a mixture of multivariate normal distributions to the observed data using its first through fourth central moments. It generates estimates of the number of multivariate normal components in the mixture as well as the proportion, mean vector, and covariance matrix for each component. The basic mathematical model for CLASSY and the actual operation of the algorithm as currently implemented are described. Results of applying CLASSY to real and simulated LANDSAT data are presented and compared with those generated by the iterative self-organizing clustering system algorithm on the same data sets.

Lennington, R. K.↗
NASA NTRS1997

A New Approach to Extreme Value Estimation Applicable to a Wide Variety of Random Variables

Designing reliable structures requires an estimate of the maximum and minimum values (i.e., strength and load) that may be encountered in service. Yet designs based on very extreme values (to insure safety) can result in extra material usage and hence, uneconomic systems. In aerospace applications, severe over-design cannot be tolerated making it almost mandatory to design closer to the assumed limits of the design random variables. The issue then is predicting extreme values that are practical, i.e. neither too conservative or non-conservative. Obtaining design values by employing safety factors is well known to often result in overly conservative designs and. Safety factor values have historically been selected rather arbitrarily, often lacking a sound rational basis. To answer the question of how safe a design needs to be has lead design theorists to probabilistic and statistical methods. The so-called three-sigma approach is one such method and has been described as the first step in utilizing information about the data dispersion. However, this method is based on the assumption that the random variable is dispersed symmetrically about the mean and is essentially limited to normally distributed random variables. Use of this method can therefore result in unsafe or overly conservative design allowables if the common assumption of normality is incorrect.

Holland, Frederic A., Jr.↗
DOE OSTI2024

Yet Another Discriminant Analysis (YADA): A Probabilistic Model for Machine Learning Applications

This paper presents a probabilistic model for various machine learning (ML) applications. While deep learning (DL) has produced state-of-the-art results in many domains, DL models are complex and over-parameterized, which leads to high uncertainty about what the model has learned, as well as its decision process. Further, DL models are not probabilistic, making reasoning about their output challenging. In contrast, the proposed model, referred to as Yet Another Discriminate Analysis(YADA), is less complex than other methods, is based on a mathematically rigorous foundation, and can be utilized for a wide variety of ML tasks including classification, explainability, and uncertainty quantification. YADA is thus competitive in most cases with many state-of-the-art DL models. Ideally, a probabilistic model would represent the full joint probability distribution of its features, but doing so is often computationally expensive and intractable. Hence, many probabilistic models assume that the features are either normally distributed, mutually independent, or both, which can severely limit their performance. YADA is an intermediate model that (1) captures the marginal distributions of each variable and the pairwise correlations between variables and (2) explicitly maps features to the space of multivariate Gaussian variables. Numerous mathematical properties of the YADA model can be derived, thereby improving the theoretic underpinnings of ML. Validation of the model can be statistically verified on new or held-out data using native properties of YADA. However, there are some engineering and practical challenges that we enumerate to make YADA more useful.

97 MATHEMATICS AND COMPUTING↗