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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Efficient high-fidelity TRISO statistical failure analysis using Bison: Applications to AGR-2 irradiation testing

The ability of tri-structural isotropic (TRISO) fuel to contain fission products is largely dictated by the quality of the manufacturing process, since most of the fission product release is expected to occur due to coating layer failure in a small number of particles containing defects. The Bison fuel performance code has capabilities to predict failure in individual particles, accounting for the presence of defects, and to apply statistical analysis methods to compute the probability of failure in a set of fuel particles. Bison has recently undergone significant development both to improve its physical representations of fuel particle behavior and to improve the efficiency of its statistical failure calculations. Physical model improvements include new capabilities to account for the pressure generated by fission gases on inner pyrolytic carbon (IPyC) crack surfaces and to use local material coordinate orientation to accurately incorporate the anisotropy in the material properties in aspherical particles. To improve statistical modeling efficiency, a direct integration approach which involves directly integrating the failure probability function associated with statistically varying parameters has been developed. The direct integration approach is much more efficient than the Monte Carlo (MC) schemes commonly employed, and allows Bison to directly run high-dimensional fuel performance models, which improves the accuracy of failure probability calculations. Finally, a set of benchmark problems is considered here to compare the MC and direct integration approaches, and a statistical failure analysis of compacts in the Advanced Gas Reactor (AGR)-2 experiments is performed using the direct integration approach.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Accelerated statistical failure analysis of multifidelity TRISO fuel models

Statistical nuclear fuel failure analysis is critical for the design and development of advanced reactor technologies. Although Monte Carlo Sampling (MCS) is a standard method of statistical failure analysis for fuels, the low failure probabilities of some advanced fuel forms and the correspondingly large number of required model evaluations limit its application to low-fidelity (e.g., 1-D) fuel models. In this paper, we present four other statistical methods for fuel failure analysis in Bison, considering tri-structural isotropic (TRISO)-coated particle fuel as a case study. The statistical methods considered are Latin hypercube sampling (LHS), adaptive importance sampling (AIS), subset simulation (SS), and the Weibull theory. Using these methods, we analyzed both 1-D and 2-D representations of TRISO models to compute failure probabilities and the distributions of fuel properties that result in failures. The results of these methods compare well across all TRISO models considered. Overall, SS and the Weibull theory were deemed the most efficient, and can be applied to both 1-D and 2-D TRISO models to compute failure probabilities. Moreover, since SS also characterizes the distribution of parameters that cause TRISO failures, and can consider failure modes not described by the Weibull criterion, it may be preferred over the other methods. Finally, a discussion on the efficacy of different statistical methods of assessing nuclear fuel safety is provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Spatiotemporal and Statistical Mapping of Transition Metal Equilibria in Alkaline Media

Transition metal dissolution and redeposition (D/R) kinetics in alkaline media play a critical role in various chemical and electrochemical processes. Competitive reaction kinetics between different transition metals can modulate individual metal behavior in these processes. To date, these phenomena have remained largely unmeasured, and even when captured, they are difficult to statistically characterize due to their dynamic nature, simultaneous occurrence, and spatially heterogeneous nature. Here, in this study, we develop a statistical analysis framework based on in situ and operando X-ray fluorescence microscopy (XFM) to investigate the relative D/R kinetics of multiple transition metals in alkaline media. By employing statistical analysis, we quantify the spatial distribution of D/R species and assess the rate at which the system reaches equilibrium under varying reaction conditions. We show that pH does not simply change the rate of dissolution and redeposition, but reorganizes the cross-element kinetic correlations among Ni, Fe, and Mn and accelerates the spatial equilibration of D/R events, as quantified through correlation analysis, reaction-rate estimation, probability function distributions, and texture-based monitoring statistics. Additionally, we demonstrate how modifying the solvent environment can influence D/R kinetics, providing a pathway for tuning materials synthesis and process optimization. Our study offers valuable insights into the complex interplay between different transition metals and provides a reliable statistical framework for spatial analysis of diverse imaging data sets, enabling deeper extraction of latent information across multiple modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Alternating Conditional Expectations: Introducing a Non‐Parametric Statistical Method to Interpret Long‐Term Greenhouse Gas Flux Measurements Over Semi‐Arid and Wetland Ecosystems

Abstract We explore the potential of using a non‐parametric statistical method called Alternating Conditional Expectations, ACE, to quantify functional relationships in biogeosciences. Here, ACE is used to quantify the non‐linear and multi‐faceted responses of greenhouse gas fluxes to a set of biophysical forcings, when the shapes of those response surfaces are unknown. We evaluated the statistical method over two contrasting ecosystems and two contrasting time steps. One case involved quantifying the biophysical controls of water vapor and carbon dioxide (CO 2 ) fluxes over a semi‐arid oak savanna using daily integrated fluxes. The other case evaluated the responses of CO 2 and methane (CH 4 ) flux measurements to a set of biophysical forcings at a restored tidal wetland using thirty‐minute averages. The statistical model, based on 4 independent variables, explained up over 90% of the variation in daily integrated flux densities of water vapor and net carbon dioxide exchange at the savanna site. This fit was defined by distinct non‐linear responses to such drivers as gross primary production, photosynthetically active radiation, air temperature, vapor pressure deficit and soil moisture. At the tidal wetland site, we evaluated net carbon dioxide and methane fluxes with short‐term measurements to capture the influence of rising and falling tides and seasonality in biological activity. The statistical model defined the shape of the forcing of fluxes due to the roles of carbon exudates, water table depth, oxygen level in the water column, temperature and vegetation status. The statistical fits of the greenhouse gas fluxes were less precise than the savanna case. The fetch varies on a run‐to‐run basis as it is comprised of a heterogeneous mosaic of open water and vegetation. Furthermore, it is difficult to monitor the environmental conditions of the archaea and bacteria in the sediments that produce methane and carbon dioxide.

Environmental Sciences & Ecology↗
DOE OSTI2026

Quantum statistical plasmonic metacrystals

Engineering materials that control quantum many-body dynamics remains challenging, as multiparticle interactions typically produce complex emergent behaviour that is difficult to predict. Here we introduce quantum statistical plasmonic metacrystals, structures in which the multiparticle dynamics mediated by optical near fields produce forbidden quantum statistical bands that enable selective transmission of different types of light. This functionality arises from a plasmonic structure composed of nanoantennas acting as meta-atoms. Multiphoton fields with statistics within the allowed bands propagate without distortion, whereas fields in forbidden bands are suppressed or driven towards the nearest accessible statistical state. We show that these bands are determined by the geometry and collective arrangement of the meta-atoms, providing a deterministic route to engineering quantum statistical transport. This platform establishes a room-temperature quantum material intrinsically sensitive to the quantum coherence of many-body photonic systems, enabling their robust manipulation and transport. Our results have implications for coherence-sensitive photonic materials for energy harvesting and scalable many-body quantum technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Detection of the significant impact of source clustering on higher order statistics with DES Year 3 weak gravitational lensing data

We measure the impact of source galaxy clustering on higher order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show that this effect can exceed measurement uncertainties for common higher order statistics for certain analysis choices. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey (DES) Year 3 (Y3) data, we construct null tests for the source-clustering-free case, finding a p-value of p = 4 × 10 −3 (2.6σ) using third-order map moments and p = 3 × 10 −11 (6.5σ) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either included in the model or minimized through ad hoc procedures (e.g. scale cuts). We verify that the procedures adopted in existing DES Y3 cosmological analyses were sufficient to render this effect negligible. Failing to account for source clustering can significantly impact cosmological inference from higher order gravitational lensing statistics, e.g. higher order N-point functions, wavelet-moment observables, and deep learning or field-level summary statistics of weak lensing maps.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution

Integrated computational materials engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and significantly accelerating the materials design process. However, ICME models are also computationally expensive, particularly with respect to time integration for dynamics, which hinders the ability to study statistical ensembles and thermodynamic properties of large systems for long time scales. To alleviate the computational bottleneck, we propose to model the evolution of statistical microstructure descriptors as a continuous-time stochastic process using a non-linear Langevin equation, where the probability density function (PDF) of the statistical microstructure descriptors, which are also the quantities of interests (QoIs), is modeled by the Fokker–Planck equation. In this work, we discuss how to calibrate the drift and diffusion terms of the Fokker–Planck equation from the theoretical and computational perspectives. The calibrated Fokker–Planck equation can be used as a stochastic reduced-order model to simulate the microstructure evolution of statistical microstructure descriptors PDF. Considering statistical microstructure descriptors in the microstructure evolution as QoIs, we demonstrate our proposed methodology in three integrated computational materials engineering (ICME) models: kinetic Monte Carlo, phase field, and molecular dynamics simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Significant DBSCAN+: Statistically Robust Density-based Clustering

Cluster detection is important and widely used in a variety of applications, including public health, public safety, transportation, and so on. Given a collection of data points, we aim to detect density-connected spatial clusters with varying geometric shapes and densities, under the constraint that the clusters are statistically significant. The problem is challenging, because many societal applications and domain science studies have low tolerance for spurious results, and clusters may have arbitrary shapes and varying densities. As a classical topic in data mining and learning, a myriad of techniques have been developed to detect clusters with both varying shapes and densities (e.g., density-based, hierarchical, spectral, or deep clustering methods). However, the vast majority of these techniques do not consider statistical rigor and are susceptible to detecting spurious clusters formed as a result of natural randomness. On the other hand, scan statistic approaches explicitly control the rate of spurious results, but they typically assume a single “hotspot” of over-density and many rely on further assumptions such as a tessellated input space. To unite the strengths of both lines of work, we propose a statistically robust formulation of a multi-scale DBSCAN, namely Significant DBSCAN+, to identify significant clusters that are density connected. As we will show, incorporation of statistical rigor is a powerful mechanism that allows the new Significant DBSCAN+ to outperform state-of-the-art clustering techniques in various scenarios. We also propose computational enhancements to speed-up the proposed approach. Experiment results show that Significant DBSCAN+ can simultaneously improve the success rate of true cluster detection (e.g., 10–20% increases in absolute F1 scores) and substantially reduce the rate of spurious results (e.g., from thousands/hundreds of spurious detections to none or just a few across 100 datasets), and the acceleration methods can improve the efficiency for both clustered and non-clustered data.

Computer Science↗
DOE OSTI2024

Extreme-value statistics in nonlinear optics

We show that, although nonlinear optics may give rise to a vast multitude of statistics, all these statistics converge, in their extreme-value limit, to one of a few universal extreme-value statistics. Specifically, in the class of polynomial nonlinearities, such as those found in the Kerr effect, weak-field harmonic generation, and multiphoton ionization, the statistics of the nonlinear-optical output converges, in the extreme-value limit, to the exponentially tailed, Gumbel distribution. Exponentially growing nonlinear signals, on the other hand, such as those induced by parametric instabilities and stimulated scattering, are shown to reach their extreme-value limits in the class of the Fréchet statistics, giving rise to extreme-value distributions (EVDs) with heavy, manifestly nonexponential tails, thus favoring extreme-event outcomes and rogue-wave buildup.

Zheltikov, Aleksei M. (ORCID:0000000291380576)↗
DOE OSTI2020

Benchmark Solutions for Radiation Transport in Stochastic Media with Inhomogeneous Material Statistics

Accurately solving implicit Monte Carlo (IMC) thermal photon transport problems with mixed material cells is important in realistic applications. The production IMC package at LLNL treats mixed material cells arising from ALE remap and hydrodynamics using the same approximate model. The new Imp IMC thermal photon transport package currently under development has both a material interface reconstruction (MIR) algorithm and a Levermore-Pomraning (LP) stochastic medium algorithm for treating mixed material cells. Existing stochastic medium algorithms for treating mixed material cells in IMC lack a complete theoretical basis. The IMC LP algorithm implementation has been demonstrated to reproduce published deterministic LP solutions for the particular case of spatially homogeneous material statistics. Realistic simulations will include spatially inhomogeneous material statistics (material mean chord lengths). In a previous investigation, the LP-model for transport in binary stochastic media in rod geometry was generalized to accommodate spatially varying material chord lengths, i.e., the mixing statistics were allowed to be nonhomogeneous. Analytical solutions were obtained and used to produce a verifi cation suite for the Imp IMC Levermore-Pomraning implementation for different spatial variations of the chord lengths. However, the accuracy of the LP model when the mixing statistics are nonhomogeneous has not been assessed and leaves open the question of whether local accuracy is improved or further degraded when chord lengths are not uniform. This shortcoming is rectifi ed here by developing benchmark analytic solutions for transport in binary Markovian stochastic mixtures in rod geometry with nonhomogeneous mixing statistics, using spatially varying chord lengths considered in the previous investigation based on the LP model. Methods for sampling a nonhomogeneous Poisson process (NHPP) are first described and used to construct individual realizations of the binary mixtures in rod geometry. Analytic solutions are then obtained for the forward and backward directed fluxes on a given realization, now viewed as a deterministic medium with alternating layers of the two materials with known interface locations. Finally, material averaged scalar fluxes are obtained using these sampling schemes with spatially linear and quadratic chord lengths and used to assess the accuracy of the previously obtained LP-model results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Does a Free Electron Laser Exhibit Non-Standard Statistics? [Slides and Report]

The originally proposed work under this award sought to develop a theoretical basis for previous experimental observations in free-electron laser (FEL) physics involving certain non-classical effects in the light produced by these devices. A sound and valid theoretical interpretation of these experiments would represent a transformational understanding of free-electron lasers, and of electron-photon interactions in general. The specific objective of the completed work, as described in the attached progress report by Jeongwan Park, was to perform a detailed analysis of an experiment by Chen and Madey (Physical Review Letters; volume 86 number 26, 2001) concerning the purported sub-Poissonian photon statistics in an FEL. Since that published work contradicted FEL theory as presently understood, the purpose of the work under the present subcontract was to obtain a better understanding of the quantum nature of the FEL, to investigate the possibility of theoretical and experimental evidence for the non-standard photon statistics of the FEL, and to critically examine the experimental evidence through a re-evaluation of the data analysis of Chen and Madey. The results of this study showed that there were numerous experimental conditions under which the observed photon statistics could be explained by combining both the photon clustering property and the dead-time effect, and consequently, that the observed photon statistics in the Chen-Madey experiment did not require sub-Poissonian photon statistics for their explanation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Entropy and its Relationship with Statistics

The purpose of our report is to discuss the notion of entropy and its relationship with statistics. Our goal is to provide a manner in which you can think about entropy, its central role within information theory and relationship with statistics. We review various relationships between information theory and statistics—nearly all are well-known but unfortunately are often not recognized. Entropy quantities the "average amount of surprise" in a random variable and lies at the heart of information theory, which studies the transmission, processing, extraction, and utilization of information. For us, data is information. What is the distinction between information theory and statistics? Information theorists work with probability distributions. Instead, statisticians work with samples. In so many words, information theory using samples is the practice of statistics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

On the Statistical Uncertainty of Monte Carlo-Calculated Scattering Sensitivities

Sensitivity coefficients calculated with Monte Carlo codes are widely used for nuclear data uncertainty quantification in the modeling and simulation of complex 3D reactor systems. This study systematically compares sensitivity coefficients and associated statistical uncertainties for the multiplication factor and fuel temperature reactivity across multiple Monte Carlo codes (SCALE/KENO, SCALE/Shift, MCNP, and Serpent) using simple models representing light-water reactors and advanced reactor concepts. For multiplication factor sensitivities, statistical uncertainties are generally acceptable, although scattering sensitivities show significantly larger statistical uncertainties than, for example, fission and capture reactions. Fuel temperature reactivity sensitivities show significantly larger statistical uncertainties across all reactions. Elastic scattering sensitivities are the most problematic: all Monte Carlo codes fail to resolve energy-dependent coefficients, and they produce dramatically different energy-collapsed values. Critically, the use of these sensitivity coefficients in nuclear data uncertainty propagation leads to reduced statistical uncertainties in individual uncertainty contributions. This can lead to the masking of unusable sensitivity coefficients and producing misleading uncertainty results. The findings of this study show that new or enhanced methods are needed to improve Monte Carlo elastic scattering sensitivity calculations. Additionally, this study shows the relevance of verifying sensitivity coefficients through direct perturbation calculations for individual nuclide reactions, instead of only for total cross sections as commonly done.

Bostelmann, Rike [ORNL] (ORCID:0000000165968088)↗
NASA NTRS1974

Statistical modeling of scintillation effects

Scintillation produces fluctuation of the complex envelope of a modulated signal. A useful way to characterize scintillation effects is to describe the signal statistics that result when a CW wave is transmitted through a random medium. Many theoretical treatments describe the signal statistics in a manner identical with the noise theory of Rice. These theories, however, predict Rice statistics only at a very great distance from the perturbing medium, and it has been suspected that generalization to permit the quadrature components of the scattered signal to be partially correlated Gaussian variates might better match the observed signal statistics. Recent tests of signals observed through three types of structured plasma have consistently confirmed this speculation and have revealed a surprising consistency in parameters describing the first-order signal statistics.

Fremouw, E. J.↗
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.↗
NASA NTRS1982

Statistics of Delta v magnitude for a trajectory correction maneuver containing deterministic and random components

A number of interplanetary missions now being planned involve placing deterministic maneuvers along the flight path to alter the trajectory. Lee and Boain (1973) examined the statistics of trajectory correction maneuver (TCM) magnitude with no deterministic ('bias') component. The Delta v vector magnitude statistics were generated for several values of random Delta v standard deviations using expansions in terms of infinite hypergeometric series. The present investigation uses a different technique (Monte Carlo simulation) to generate Delta v magnitude statistics for a wider selection of random Delta v standard deviations and also extends the analysis to the case of nonzero deterministic Delta v's. These Delta v magnitude statistics are plotted parametrically. The plots are useful in assisting the analyst in quickly answering questions about the statistics of Delta v magnitude for single TCM's consisting of both a deterministic and a random component. The plots provide quick insight into the nature of the Delta v magnitude distribution for the TCM.

Bollman, W. E.↗
NASA NTRS1987

Statistical aspects of solar flares

A survey of the statistical properties of 850 H alpha solar flares during 1975 is presented. Comparison of the results found here with those reported elsewhere for different epochs is accomplished. Distributions of rise time, decay time, and duration are given, as are the mean, mode, median, and 90th percentile values. Proportions by selected groupings are also determined. For flares in general, mean values for rise time, decay time, and duration are 5.2 + or - 0.4 min, and 18.1 + or 1.1 min, respectively. Subflares, accounting for nearly 90 percent of the flares, had mean values lower than those found for flares of H alpha importance greater than 1, and the differences are statistically significant. Likewise, flares of bright and normal relative brightness have mean values of decay time and duration that are significantly longer than those computed for faint flares, and mass-motion related flares are significantly longer than non-mass-motion related flares. Seventy-three percent of the mass-motion related flares are categorized as being a two-ribbon flare and/or being accompanied by a high-speed dark filament. Slow rise time flares (rise time greater than 5 min) have a mean value for duration that is significantly longer than that computed for fast rise time flares, and long-lived duration flares (duration greater than 18 min) have a mean value for rise time that is significantly longer than that computed for short-lived duration flares, suggesting a positive linear relationship between rise time and duration for flares. Monthly occurrence rates for flares in general and by group are found to be linearly related in a positive sense to monthly sunspot number. Statistical testing reveals the association between sunspot number and numbers of flares to be significant at the 95 percent level of confidence, and the t statistic for slope is significant at greater than 99 percent level of confidence. Dependent upon the specific fit, between 58 percent and 94 percent of the variation can be accounted for with the linear fits. A statistically significant Northern Hemisphere flare excess (P less than 1 percent) was found, as was a Western Hemisphere excess (P approx 3 percent). Subflares were more prolific within 45 deg of central meridian (P less than 1 percent), while flares of H alpha importance or = 1 were more prolific near the limbs greater than 45 deg from central meridian; P approx 2 percent). Two-ribbon flares were more frequent within 45 deg of central meridian (P less than 1 percent). Slow rise time flares occurred more frequently in the western hemisphere (P approx 2 percent), as did short-lived duration flares (P approx 9 percent), but fast rise time flares were not preferentially distributed (in terms of east-west or limb-disk). Long-lived duration flares occurred more often within 45 deg 0 central meridian (P approx 7 percent). Mean durations for subflares and flares of H alpha importance or + 1, found within 45 deg of central meridian, are 14 percent and 70 percent, respectively, longer than those found for flares closer to the limb. As compared to flares occurring near cycle maximum, the flares of 1975 (near solar minimum) have mean values of rise time, decay time, and duration that are significantly shorter. A flare near solar maximum, on average, is about 1.6 times longer than one occurring near solar minimum.

Wilson, Robert M.↗
NASA NTRS1993

NASA thesaurus combined file postings statistics

The NASA Thesaurus Combined File Postings Statistics is published semiannually (January and July). This alphabetical listing of postable subject terms contained in the NASA Thesaurus is used to display the number of postings (documents) indexed by each subject term from 1968 to date. The postings totals per item are separated by announcement of other media into STAR, IAA, COSMIC, and OTHER, columnar entries covering the NASA document collection (1968 to date). This is a cumulative publication, and except for special cases, no reference is needed to previous issuances. Retention of the January 1992 issue could be helpful for book information. With the July 1992 issue, NALNET book statistics have been replaced by COSMIC statistics for NASA funded software. File postings statistics for the Alternate Data Base covering NASA collection from 1962 through 1967 were published on a one-time basis in September 1975. Subject terms for the Alternate Data Base are derived from the subject Authority List, reprinted 1985, which is available upon request. The distribution of 19,697,748 postings among the 17,446 NASA Thesaurus terms is tabulated on the last page of the NASA Thesaurus Combined File Postings Statistics.

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