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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Luminescence Decay of Colloidal Quantum Dots and Stretched Exponential (Kohlrausch) Relaxation Function

The room temperature non-exponential luminescence decay of colloidal quantum dots is investigated theoretically in an attempt to identify the underlying physical mechanisms responsible for the shape of the decay. It is shown that a stretched exponential functional form of the luminescence decay can be understood in terms of long-range resonance energy transfer from quantum dots to acceptors (molecules, quantum dots, or anharmonic molecular vibrations) or by contact quenching by quenchers (surface traps, molecules or quantum dots) distributed statistically (Poisson distribution) on the surface of the dots. These non-radiative transition processes are assigned to different ranges of the stretching parameter β.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Characterization of spatial statistics of distributed targets in SAR data

A statistical approach to the analysis of spatial statistics in polarimetric multifrequency SAR data, which is aimed at extracting the intrinsic variability of the target by removing variability from other sources, is presented. An image model, which takes into account three sources of spatial variability, namely, image speckle, system noise, and the intrinsic spatial variability of the target or texture, is described. It is shown that the presence of texture increases the image variance-to-mean square ratio and introduces deviations of the image autocovariance function from the expected SAR system response. The approach is exemplified by sea-ice SAR imagery acquired by the Jet Propulsion Laboratory three-frequency polarimetric airborne SAR. Data obtained indicate that, for different sea-ice types, the spatial statistics seem to vary more across frequency than across polarization and the observed differences increase in magnitude with decreasing frequency.

Rignot, E.↗
DOE OSTI2019

Radionuclide Risk Coefficient Uncertainty Distributions for Use in Performance Assessments - 19156

Traditionally, radiation dose has been used as the regulatory criterion for decision making in performance assessments (PAs), despite the concept of cancer risk arguably being a more easily understood endpoint than dose for the public, and a preferable metric for decision analysis. However, the United States Environmental Protection Agency (EPA) has developed risk parameters for use in risk assessments and PAs in the form of radionuclide-specific risk coefficients, or RCs, which are published in various Federal Guidance Reports (FGRs). RCs are employed as scalars to convert environmental radionuclide exposure (via ingestion, inhalation, and external exposure) estimates to incremental lifetime cancer risk (ILCR). ILCR is the additional cancer risk averaged over a lifetime, over-and-above all-cause cancer risk, associated with carcinogen exposure. Uncertainties associated with RCs are discussed in FGR 13 and in a joint report published by EPA and Oak Ridge National Laboratory, but statistical distributions for the RCs were not directly developed. The uncertainty assessments in the EPA/ONRL report were based on dosimetric modeling and elicitation of nine experts. From these sources, five uncertainty categories were defined based on ratios of the 5. and 95. quantiles of uncertainty. Thus, the representations of uncertainty defined by EPA/ORNL are not distributions in a traditional sense. Furthermore, the authors only addressed uncertainty in RCs for inhalation and ingestion pathways. We develop a methodology for assigning statistical distributions to EPA's published mortality RC values (i.e. to estimate the probability of dying from radiation-induced cancers) for the inhalation (slow, medium, and fast absorption types), ingestion (water, food, and soil), and external exposure pathways associated with all cancer types. We employed the same dosimetric concepts and assumptions as EPA/ORNL, including cancer risk (dose-response) distributional information from a previous expert elicitation, which was also employed by EPA/ORNL in their work. We assumed that uncertainty in RCs can be described by lognormal distributions based on the modeling conducted previously by EPA/ORNL, and that point estimates tabulated in FGR 13 represent median values of the distributions. We also extended EPA/ORNL's uncertainty ratios to statistical distributions for external exposure RCs. The results are a set of radionuclide-specific distributions that are applicable in PAs that focus on cancer mortality. These distributions are currently and will subsequently be employed in PAs at various sites, in addition to the required regulatory dose limits. Quantification of ILCRs and associated uncertainty in PAs will provide regulators and the public with additional information for good decision making. Future directions include further refinement of the distributions and development of statistical distributions for morbidity RCs, which are used to estimate the probability of developing, but not necessarily dying as a result of, radiation-induced cancer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Performance Comparison of Circular and Spherical Error Probable Estimators

This report compares the performance of three Circular Error Probable (CEP) estimators: the Grubbs-Patnaik estimator, a new, non-iterative, radial-integration estimator, and a median estimator. It also compares the performance of two Spherical Error Probable (SEP) estimators. The performance of each estimator is assessed in terms of bias, uncertainty, robustness, and computational complexity. Robustness is evaluated with respect to outliers, variations in the underlying statistical distribution characterizing munition impact positions, and impact-position measurement errors. The performance assessments indicate the radial-integration and Grubbs-Patnaik estimators perform nearly identically providing the statistical distribution of impact-position coordinates is jointly normal with zero means. In that case, both estimators outperform the median estimator by about 2% relative to the true CEP in terms of estimator uncertainty. The bias performance of the radial-integration and median estimators is close to zero for jointly normal impacts, however, the Grubbs-Patnaik estimator can be significantly biased for jointly normal impacts with non-zero means. When the statistical distribution characterizing impact positions is known, but not jointly normal, the radial-integration estimator is superior. In this case, the median estimator also outperforms the Grubbs-Patnaik estimator but is not quite as good as the radial-integration estimator. If the statistical distribution characterizing impacts is unknown and not jointly normal, or if distribution parameters are difficult or impractical to estimate, or if test data is corrupted with outliers, then the median estimator dramatically outperforms the other estimators, especially in terms of estimation bias. Unexpectedly, measurement noise did not significantly degrade the performance of any of the estimators, except for cases with signal to noise ratios less than five. Although the Grubbs-Patnaik estimator has remained the gold standard for CEP estimation for over half a century, the performance assessments indicate the new, non-iterative, radial-integration estimator and the median estimator offer significant advantages and, in most practical real-world conditions, are superior estimators. These estimators are also useful for SEP estimation whereas the Grubbs-Patnaik estimator does not extend to three dimensions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

How large is the gluon polarization in the statistical parton distributions approach?

We review the theoretical foundations of the quantum statistical approach to parton distributions and we show that by using some recent experimental results from Deep Inelastic Scattering, we are able to improve the description of the data by means of a new determination of the parton distributions. We will see that a large gluon polarization emerges, giving a significant contribution to the proton spin.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Multifield stochastic particle production: beyond a maximum entropy ansatz

In this work, we explore non-adiabatic particle production for N f coupled scalar fields in a time-dependent background with stochastically varying effective masses, cross-couplings and intervals between interactions. Under the assumption of weak scattering per interaction, we provide a framework for calculating the typical particle production rates after a large number of interactions. After setting up the framework, for analytic tractability, we consider interactions (effective masses and cross couplings) characterized by series of Dirac-delta functions in time with amplitudes and locations drawn from different distributions. Without assuming that the fields are statistically equivalent, we present closed form results (up to quadratures) for the asymptotic particle production rates for the N f =1 and N f =2 cases. We also present results for the general N f >2 case, but with more restrictive assumptions. We find agreement between our analytic results and direct numerical calculations of the total occupation number of the produced particles, with departures that can be explained in terms of violation of our assumptions. We elucidate the precise connection between the maximum entropy ansatz (MEA) used in Amin & Baumann (2015) and the underlying statistical distribution of the self and cross couplings. We provide and justify a simple to use (MEA-inspired) expression for the particle production rate, which agrees with our more detailed treatment when the parameters characterizing the effective mass and cross-couplings between fields are all comparable to each other. However, deviations are seen when some parameters differ significantly from others. We show that such deviations become negligible for a broad range of parameters when N f >> 1.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

Joint aircraft loading/structure response statistics of time to service crack initiation

A reliability analysis for predicting the statistical distribution of time to fatigue crack initiation for aircraft structures in service is presented. The present analysis utilizes the statistical data of the specimen fatigue tests, the full-scale structure tests, and the statistical dispersion of aircraft service loads. The statistical distribution of the time to fatigue crack initiation of the full-scale structure under laboratory loading spectrum is assumed to be Weibull. The service loads for gust turbulences are modeled as Poisson processes for transport-type aircraft, while the maneuver loads are modeled as compound Poisson processes for fighter and training aircraft. It is found that the statistical distribution of time to fatigue crack initiation for aircraft structures in service is not Weibull and that the prediction on the basis of the Weibull distribution is unconservative, in particular in the early service time.

Yang, J.-N.↗
DOE OSTI2020

Nearest neighbour distributions: New statistical measures for cosmological clustering

ABSTRACT The use of summary statistics beyond the two-point correlation function to analyse the non-Gaussian clustering on small scales, and thereby, increasing the sensitivity to the underlying cosmological parameters, is an active field of research in cosmology. In this paper, we explore a set of new summary statistics – the k-Nearest Neighbour Cumulative Distribution Functions (kNN-CDF). This is the empirical cumulative distribution function of distances from a set of volume-filling, Poisson distributed random points to the k-nearest data points, and is sensitive to all connected N-point correlations in the data. The kNN-CDF can be used to measure counts in cell, void probability distributions, and higher N-point correlation functions, all using the same formalism exploiting fast searches with spatial tree data structures. We demonstrate how it can be computed efficiently from various data sets – both discrete points, and the generalization for continuous fields. We use data from a large suite of N-body simulations to explore the sensitivity of this new statistic to various cosmological parameters, compared to the two-point correlation function, while using the same range of scales. We demonstrate that the use of kNN-CDF improves the constraints on the cosmological parameters by more than a factor of 2 when applied to the clustering of dark matter in the range of scales between 10 and $40\, h^{-1}\, {\rm Mpc}$. We also show that relative improvement is even greater when applied on the same scales to the clustering of haloes in the simulations at a fixed number density, both in real space, as well as in redshift space. Since the kNN-CDF are sensitive to all higher order connected correlation functions in the data, the gains over traditional two-point analyses are expected to grow as progressively smaller scales are included in the analysis of cosmological data, provided the higher order correlation functions are sensitive to cosmology on the scales of interest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Statistical charge distribution over dust particles in a non-Maxwellian Lorentzian plasma

On the basis of statistical mechanics and charging kinetics, the charge distribution over uniform size spherical dust particles in a non-Maxwellian Lorentzian plasma is investigated. Two specific situations, viz., (i) the plasma in thermal equilibrium and (ii) non-equilibrium state where the plasma is dark (no emission) or irradiated by laser light (including photoemission) are taken into account. The formulation includes the population balance equation for the charged particles along with number and energy balance of the complex plasma constituents. The departure of the results for the Lorentzian plasma, from that in case of Maxwellian plasma, is graphically illustrated and discussed; it is shown that the charge distribution tends to results corresponding to Maxwellian plasma for large spectral index. The charge distribution predicts the opposite charging of the dust particles in certain cases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Digital noise generators using one-dimensional chaotic maps

This work shows how to improve the statistical distribution of signals produced by digital noise generators designed with one-dimensional (1-D) chaotic maps. It also shows that in a digital electronic design the piecewise linear chaotic maps (PWLCM) should be considered because they do not have stability islands in its chaotic behavior region, as it occurs in the case of the logistic map, which is commonly used to build noise generators. The design and implementation problems of the digital noise generators are analyzed and a solution is proposed. This solution relates the output of PWLCM, usually defined in the real numbers' domain, with a codebook of S elements, previously defined. The proposed solution scheme produces digital noise signals with a statistical distribution close to a uniform distribution. Finally, this work shows that it is possible to have control over the statistical distribution of the noise signal by selecting the control parameter of the PWLCM and using, as a design criterion, the bifurcation diagram.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1977

Bayesian estimation of crack initiation times from service data

Lockheed C-130 Hercules aircraft have during their service life been periodically inspected and growing cracks around rivet holes were recorded. This record has recently been used to determine the statistical distributions of crack initiation times and the distribution of initial crack sizes. When crack initiation times are calculated from such cracks, by backward extrapolation of the growth relation, the resulting distribution of crack initiation times will indicate a preponderance of short times to crack initiation. If however, such distributions are combined with the reliability of the inspection procedure, the statistical distribution of missed initiation times can be estimated. The method used is based on Bayes theorem which permits the calculation of the 'prior' distribution (initiation times before inspection) from a knowledge of the 'posterior' distribution (initiation times obtained from the inspection) and a 'likelihood function' (reliability of the inspection) procedure. The results indicate that during an early inspection a large percentage of initiation times will be missed and that the fraction of located initiation times increases during later inspections.

Heller, R. A.↗
DOE OSTI2020

Joint Estimation of Topology and Injection Statistics in Distribution Grids with Missing Nodes

Optimal operation of distribution grid resources relies on accurate estimation of its state and topology. Practical estimation of such quantities is complicated by the limited presence of real-time meters. This article discusses a theoretical framework to jointly estimate the operational topology and statistics of injections in radial distribution grids under limited availability of nodal voltage measurements. In particular, we show that our proposed algorithms are able to provably learn the exact grid topology and injection statistics at all unobserved nodes as long as they are not adjacent. The algorithm design is based on novel ordered trends in voltage magnitude fluctuations at node groups, that are independently of interest for radial physical flow networks. The complexity of the designed algorithms is theoretically analyzed and their performance is validated using both linearized and nonlinear ac power flow samples in test distribution grids.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Imaging ion-molecule reactions: Charge transfer and C-N bond formation in the C{sup +}+ NH{sub 3} system

The velocity mapping ion imaging method is applied to the ion-molecule reactions occurring between C{sup +} and NH{sub 3}. The velocity space images are collected over the relative collision energy range from 1.5 to 3.3 eV, allowing both product kinetic energy distributions and angular distributions to be obtained from the data. The charge transfer process appears to be direct, dominated by long-range electron transfer that results in minimal deflection of the products. The product kinetic energy distributions are consistent with a process dominated by energy resonance. The kinetic energy distributions for C-N bond formation appear to scale with the total available energy, providing strong evidence that energy in the [CNH{sub 3}]{sup +} precursor to products is distributed statistically. The angular distributions for C-N bond formation show pronounced forward-backward symmetry, as expected for a complex that resembles a prolate symmetric top decaying along its symmetry axis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Quantifying Graph Uncertainty from Communication Data

Graphs are a widely used abstraction for representing a variety of important real-world problems including emulating cyber networks for situational awareness, or studying social networks to understand human interactions or pandemic spread. Communication data is often converted into graphs to help understand social and technical patterns in the underlying communication data. However, prior to this project, little work had been performed analyzing how best to develop graphs from such data. Thus, many critical, national security problems were being performed against graph representations of questionable quality. Herein, we describe our analyses that were precursors to our final statistically grounded technique for creating static graph snapshots from a stream of communication events. The first analyzes the statistical distribution properties of a variety of real-world communication datasets generally fit best by Pareto, log normal, and extreme value distributions. The second derives graph properties that can be estimated given the expected statistical distribution for communication events and the communication interval to be viewed node observability, edge observability, and expected accuracy of node degree. Unfortunately, as that final process is under review for publication, we can't publish it here at this time.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Calculating Statistical Orbit Distributions Using GEO Optical Observations with the Michigan Orbital Debris Survey Telescope (MODEST)

NASA's Orbital Debris measurements program has a goal to characterize the small debris environment in the geosynchronous Earth-orbit (GEO) region using optical telescopes ("small" refers to objects too small to catalog and track with current systems). Traditionally, observations of GEO and near-GEO objects involve following the object with the telescope long enough to obtain an orbit suitable for tracking purposes. Telescopes operating in survey mode, however, randomly observe objects that pass through their field of view. Typically, these short-arc observation are inadequate to obtain detailed orbits, but can be used to estimate approximate circular orbit elements (semimajor axis, inclination, and ascending node). From this information, it should be possible to make statistical inferences about the orbital distributions of the GEO population bright enough to be observed by the system. The Michigan Orbital Debris Survey Telescope (MODEST) has been making such statistical surveys of the GEO region for four years. During that time, the telescope has made enough observations in enough areas of the GEO belt to have had nearly complete coverage. That means that almost all objects in all possible orbits in the GEO and near- GEO region had a non-zero chance of being observed. Some regions (such as those near zero inclination) have had good coverage, while others are poorly covered. Nevertheless, it is possible to remove these statistical biases and reconstruct the orbit populations within the limits of sampling error. In this paper, these statistical techniques and assumptions are described, and the techniques are applied to the current MODEST data set to arrive at our best estimate of the GEO orbit population distribution.

Matney, M.↗
NASA NTRSDate not supplied

Evaluation Marcelling in Composites using Ultrasonic Guided Wave

Thermoplastic composite (TPC) material seldom manifests in-plane fiber waviness during manufacturing. In-plane fiber waviness is called marcelling. Marcelling com-promises the composite strength and performance. When present in a structure, marcelling is not only a surface defect but can extend partially along the thickness of the composite. There is no established nondestructive evaluation (NDE) method to detect and quantify marcelling in composite. Ultrasonic guided waves can saturate the complete thickness of a composite structure. Thus, physics of guided wave creates an opportunity to detect and quantify the marcelling in composites. Before guided waves could be used to detect marcelling, it is necessary to quantify the marcelling in the structure and identify the marcelling affected zones (MAZE). In this research first, high frequency scanning acoustic microscopy (SAM) was performed to quantify the marcelling and statistical distribution of the defects at different MAZE was obtained. Next the MAZE with known statistical distribution of quantified marcelling (marcelling wavelength and marcelling amplitude) was inspected using ultrasonic guided wave setup. The method quantified the guided wave feature as a function of quantitative degree of marcelling. The overarching objective of this research is to implement post process NDE inspection of TPC large structures where in plane fiber waviness or marcelling can be detected and MAZEs could be identified. Primary fining is that the reduction of wave velocity and amplitude of ultrasonic guided wave could be good indicators of MAZE. However, more rigorous calibration is necessary where inspection direction is carefully devised with respect to the marcelling.

HiCAM↗