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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 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↗
DOE OSTI2017

Modeling Seasonal Sudden Stratospheric Warming Climatology Based on Polar Vortex Statistics

This report explores the climatological frequency distribution of sudden stratospheric warmings (SSWs). General circulation models (GCMs) tend to produce SSW maxima later in winter than observations, which has been considered as a model deficiency. Yet, the observed record is short, calling into question the representativeness of the observational record. To study the seasonality of SSWs and the factors behind it, the authors use observations, a long control simulation with a stratosphere resolving GCM, and also a simple statistical model that is based on the climatological seasonal cycle of the polar vortex winds. From the combined analysis, the authors conclude that the late-winter SSW maximum seen in most climate models is realistic and that observations would also have a late-winter SSW maximum if more data were available. The authors identify the seasonally varying strengths of the polar vortex and stratospheric wave driving as the two main factors behind the seasonal SSW distribution. The statistical model also indicates that there exists a continuum of weak polar vortex states and that SSWs simply form the tail of normally distributed stratospheric winds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Investigation and Comparison between New Satellite Impact Test Results and NASA Standard Breakup Model

This paper summarizes two new satellite impact tests conducted in order to investigate on the outcome of low- and hyper-velocity impacts on two identical target satellites. The first experiment was performed at a low velocity of 1.5 km/s using a 40-gram aluminum alloy sphere, whereas the second experiment was performed at a hyper-velocity of 4.4 km/s using a 4-gram aluminum alloy sphere by two-stage light gas gun in Kyushu Institute of Technology. To date, approximately 1,500 fragments from each impact test have been collected for detailed analysis. Each piece was analyzed based on the method used in the NASA Standard Breakup Model 2000 revision. The detailed analysis will conclude: 1) the similarity in mass distribution of fragments between low and hyper-velocity impacts encourages the development of a general-purpose distribution model applicable for a wide impact velocity range, and 2) the difference in area-to-mass ratio distribution between the impact experiments and the NASA standard breakup model suggests to describe the area-to-mass ratio by a bi-normal distribution.

Sakuraba, K.↗
NASA NTRS1974

The problem of the structure of the surface of the lunar maria

The results are described of geological and morphological interpretation of large-scale photographs of the surface of lunar maria. A morphological classification is proposed for small craters. It is shown that the classification of a crater in a given morphological category, reflecting the degree of its morphological maturity, is determined by the age of the given crater. A check on the nature of distribution of small craters, as done on the basis of the nearest neighbor method, show that the distribution is governed by a near-random law. It is found that variations of the probability density function for the craters conform to a normal distribution law. An empirical relation is found for the coefficient of variation as a function of crater diameter and the dimensions of the area on which the counts are made. The rockfalls near craters of various morphological classes are described.

Florenskiy, K. P.↗
NASA NTRS2001

The AutoBayes Program Synthesis System: System Description

AUTOBAYES is a fully automatic program synthesis system for the statistical data analysis domain. Its input is a concise description of a data analysis problem in the form of a statistical model; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. AUTOBAYES synthesizes code by a schema-guided deductive process. Schemas (i.e., code templates with associated semantic constraints) are applied to the original problem and recursively to emerging subproblems. AUTOBAYES complements this approach by symbolic computation to derive closed-form solutions whenever possible. In this paper, we concentrate on the interaction between the symbolic computations and the deductive synthesis process. A statistical model specifies for each problem variable (i.e., data or parameter) its properties and dependencies in the form of a probability distribution, A typical data analysis task is to estimate the best possible parameter values from the given observations or measurements. The following example models normal-distributed data but takes prior information (e.g., from previous experiments) on the data's mean value and variance into account.

Fischer, Bernd↗
NASA NTRS1986

Effect of rotopositioning on the growth and maturation of mandibular bone in immobilized Rhesus monkeys

The rates of bone formation and mineralization in the mandibular cortex of juvenile Rhesus monkeys exposed to immobilization/rotopositioning are evaluated. The monkeys were restrained in a supine position and rotated 90 deg every 30 minutes through a full 360 deg for 14 days. The microscopic distribution of mineral densities in osteonal bone and the porosity of cortical bone are studied using microradiographs, and osteon closure rates are assessed using tetracycline labeling; normal distributions of osteons of different mineral density and cortical bone porosity values are observed. It is concluded that 14 days of immobilization/rotopositioning did not cause abnormal changes in osteon mineralization, cortical porosity, and osteon closure rates.

Simmons, D. J.↗
NASA NTRS1995

Plume particle collection and sizing from static firing of solid rocket motors

A unique dart system has been designed and built at the NASA Marshall Space Flight Center to collect aluminum oxide plume particles from the plumes of large scale solid rocket motors, such as the space shuttle RSRM. The capability of this system to collect clean samples from both the vertically fired MNASA (18.3% scaled version of the RSRM) motors and the horizontally fired RSRM motor has been demonstrated. The particle mass averaged diameters, d43, measured from the samples for the different motors, ranged from 8 to 11 mu m and were independent of the dart collection surface and the motor burn time. The measured results agreed well with those calculated using the industry standard Hermsen's correlation within the standard deviation of the correlation . For each of the samples analyzed from both MNASA and RSRM motors, the distribution of the cumulative mass fraction of the plume oxide particles as a function of the particle diameter was best described by a monomodal log-normal distribution with a standard deviation of 0.13 - 0.15. This distribution agreed well with the theoretical prediction by Salita using the OD3P code for the RSRM motor at the nozzle exit plane.

Sambamurthi, Jay K.↗
NASA NTRS1978

Microwave scatter and sea state estimation - Two-scale ocean wave models

The efficient estimation of ocean wave-structure parameters with a remote, narrow-beam, pulsed, microwave radar at intermediate incidence angles is discussed. The sea surface is described as the sum of random small- and large-scale structures (waves), the latter the sum of a sinusoid and a random field. It is shown that the small-scale structure is responsible for scattering and that the scatter depends parametrically on the large-scale structure. For the estimation problem it is assumed, reasonably, that the received signal is normally distributed: a relatively simple processor which will efficiently estimate parameters of the sinusoidal structure is illustrated and its performance discussed. A brief comparison is made with a normal incidence system with which the variance of the large-scale random roughness can be estimated.

Harger, R. O.↗
NASA NTRS1994

Merged interaction regions and large-scale magnetic field fluctuations during 1991: Voyager 2 observations

This paper analyzes Voyager 2 observations of the magnetic field between 33.6 AU and 36.2 AU during 1991 when extraordinary events were observed on the Sun and in the heliosphere. The magnetic field strength signal B(t) has the unusual form of two large transient merged interaction regions (MIRs) on a fluctuating background. The two MIRs moved past the spacecraft in 32 days and 18 days, respectively. The mean field strength in each transient MIR was approx. equals 2.6 times the mean field during the remaining part of the year (0.11 nT). Each of the MIRs is related to a fast stream. The magnetic field is strong throughout each stream, suggesting that the strong fields are carried by the streams as well as produced by shock and stream compression. The fluctuations in B(t) during 1991 are not multifractal, and the MIRs cannot be approximated as multifractal clusters of intense magnetic fields. The distribution of the hour-averaged magnetic field strengths is approximately lognormal over 90% of its intermediate range, and it has an exponential tail for B greater than the average magnetic field strength. The elevation angles of B have a normal distribution with a standard deviation of 16 deg +/- 4 deg. The distributions of the azimuthal angles of B in the ranges 1 deg - 180 deg and 180 deg - 360 deg are approximately normal over a more limited range, and non-Gaussian tails associated with nearly radial magnetic fields; the standard deviations are approx. equal to 40 deg. Individual sectors are present throughout most of the interval, even in the MIRs, but there is no recurrent sector pattern. A model of the large-scale fluctuations in 1991 will have to include both determinaistic and statistical factors.

Burlaga, L. F.↗
DOE OSTI2015

The probabilistic distribution of metal whisker lengths

Significant reliability concerns in multiple industries are related to metal whiskers, which are random high aspect ratio filaments growing on metal surfaces and causing shorts in electronic packages. We derive a closed form expression for the probabilistic distribution of metal whisker lengths. Our consideration is based on the electrostatic theory of metal whiskers, according to which whisker growth is interrupted when its tip enters a random local “dead region” of a weak electric field. Here, we use the approximation neglecting the possibility of thermally activated escapes from the “dead regions,” which is later justified. We predict a one-parameter distribution with a peak at a length that depends on the metal surface charge density and surface tension. In the intermediate range, it fits well the log-normal distribution used in the experimental studies, although it decays more rapidly in the range of very long whiskers. In addition, our theory quantitatively explains how the typical whisker concentration is much lower than that of surface grains. Finally, it predicts the stop-and-go phenomenon for some of the whiskers growth.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

SU-E-T-121: Analyzing the Broadening Effect On the Bragg Peak Due to Heterogeneous Geometries and Implementing User-Routines in the Monte-Carlo Code FLUKA in Order to Reduce Computation Time

Purpose: Aim of this study was to analyze the modulating, broadening effect on the Bragg Peak due to heterogeneous geometries like multi-wire chambers in the beam path of a particle therapy beam line. The effect was described by a mathematical model which was implemented in the Monte-Carlo code FLUKA via user-routines, in order to reduce the computation time for the simulations. Methods: The depth dose curve of 80 MeV/u C12-ions in a water phantom was calculated using the Monte-Carlo code FLUKA (reference curve). The modulating effect on this dose distribution behind eleven mesh-like foils (periodicity ∼80 microns) occurring in a typical set of multi-wire and dose chambers was mathematically described by optimizing a normal distribution so that the reverence curve convoluted with this distribution equals the modulated dose curve. This distribution describes a displacement in water and was transferred in a probability distribution of the thickness of the eleven foils using the water equivalent thickness of the foil’s material. From this distribution the distribution of the thickness of one foil was determined inversely. In FLUKA the heterogeneous foils were replaced by homogeneous foils and a user-routine was programmed that varies the thickness of the homogeneous foils for each simulated particle using this distribution. Results: Using the mathematical model and user-routine in FLUKA the broadening effect could be reproduced exactly when replacing the heterogeneous foils by homogeneous ones. The computation time was reduced by 90 percent. Conclusion: In this study the broadening effect on the Bragg Peak due to heterogeneous structures was analyzed, described by a mathematical model and implemented in FLUKA via user-routines. Applying these routines the computing time was reduced by 90 percent. The developed tool can be used for any heterogeneous structure in the dimensions of microns to millimeters, in principle even for organic materials like lung tissue.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1994

Is a data set distributed as a power law? A test, with application to gamma-ray burst brightnesses

We present a method to determine whether an observed sample of data is drawn from a parent distribution that is pure power law. The method starts from a class of statistics which have zero expectation value under the null hypothesis, H(sub 0), that the distribution is a pure power law: F(x) varies as x(exp -alpha). We study one simple member of the class, named the `bending statistic' B, in detail. It is most effective for detection a type of deviation from a power law where the power-law slope varies slowly and monotonically as a function of x. Our estimator of B has a distribution under H(sub 0) that depends only on the size of the sample, not on the parameters of the parent population, and is approximated well by a normal distribution even for modest sample sizes. The bending statistic can therefore be used to test a set of numbers is drawn from any power-law parent population. Since many measurable quantities in astrophysics have distriibutions that are approximately power laws, and since deviations from the ideal power law often provide interesting information about the object of study (e.g., a `bend' or `break' in a luminosity function, a line in an X- or gamma-ray spectrum), we believe that a test of this type will be useful in many different contexts. In the present paper, we apply our test to various subsamples of gamma-ray burst brightness from the first-year Burst and Transient Source Experiment (BATSE) catalog and show that we can only marginally detect the expected steepening of the log (N (greater than C(sub max))) - log (C(sub max)) distribution.

Wijers, Ralph A. M. J.↗