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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Trending in Probability of Collision Measurements via a Bayesian Zero-Inflated Beta Mixed Model

We investigate the performance of a generalized linear mixed model in predicting the Probabilities of Collision (Pc) for conjunction events. Specifically, we apply this model to the log(sub 10) transformation of these probabilities and argue that this transformation yields values that can be considered bounded in practice. Additionally, this bounded random variable, after scaling, is zero-inflated. Consequently, we model these values using the zero-inflated Beta distribution, and utilize the Bayesian paradigm and the mixed model framework to borrow information from past and current events. This provides a natural way to model the data and provides a basis for answering questions of interest, such as what is the likelihood of observing a probability of collision equal to the effective value of zero on a subsequent observation.

Conjuction Assessment↗
DOE OSTI2014

Neutron star masses and radii from quiescent low-mass x-ray binaries

We perform a systematic analysis of neutron star radius constraints from five quiescent low-mass X-ray binaries and examine how they depend on measurements of their distances and amounts of intervening absorbing material, as well as their assumed atmospheric compositions. We construct and calibrate to published results a semi-analytic model of the neutron star atmosphere which approximates these effects for the predicted masses and radii. Starting from mass and radius probability distributions established from hydrogen-atmosphere spectral fits of quiescent sources, we apply this model to compute alternate sets of probability distributions. We perform Bayesian analyses to estimate neutron star mass-radius curves and equation of state (EOS) parameters that best-fit each set of distributions, assuming the existence of a known low-density neutron star crustal EOS, a simple model for the high-density EOS, causality, and the observation that the neutron star maximum mass exceeds 2 M {sub ☉}. We compute the posterior probabilities for each set of distance measurements and assumptions about absorption and composition. We find that, within the context of our assumptions and our parameterized EOS models, some absorption models are disfavored. We find that neutron stars composed of hadrons are favored relative to those with exotic matter with strong phase transitions. In addition, models in which all five stars have hydrogen atmospheres are found to be weakly disfavored. Our most likely models predict neutron star radii that are consistent with current experimental results concerning the nature of the nucleon-nucleon interaction near the nuclear saturation density.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Intent Modeling and Intent Conflict Probability Calculation for Operations in Upper Class E Airspace

This work presents probabilistic intent models for two typical vehicles in ETM operational environment. Several methods, including analytical methods for approximated solutions and a numerical method for exact solution, are presented and applied to compute the intent conflict probability for ETM operations. A comparison of these methods will be conducted in the final paper. Furthermore, simulations will be performed to verify the probabilistic intent model and verify the results of intent conflict probability from different methods.

Operational intent↗
DOE OSTI2015

Small-Noise Analysis and Symmetrization of Implicit Monte Carlo Samplers

Implicit samplers are algorithms for producing independent, weighted samples from multivariate probability distributions. These are often applied in Bayesian data assimilation algorithms. We use Laplace asymptotic expansions to analyze two implicit samplers in the small noise regime. Our analysis suggests a symmetrization of the algorithms that leads to improved implicit sampling schemes at a relatively small additional cost. Here, computational experiments confirm the theory and show that symmetrization is effective for small noise sampling problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A note on the logistic equation subject to uncertainties in parameters

This paper discusses the logistic equation subject to uncertainties in the intrinsic growth rate, α, in the initial population density, N{sub 0}, and in the environmental carrying capacity, K. These parameters are treated as independent random variables. The random variable transformation method is applied to compute the first probability density function of the time–population density, N(t), and of its inflection point, t{sup ∗}. Results for the density functions of N(t), for a fixed t>0, and t{sup ∗} are also provided for α, N{sub 0} and K uniformly distributed. Finally, numerical experiments illustrate the proposed theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A computationally efficient ductile damage model accounting for nucleation and micro-inertia at high triaxialities

The computational formulation of a micro-mechanical material model for the dynamic failure of ductile metals is presented in this paper. The statistical nature of porosity initiation is accounted for by introducing an arbitrary probability density function which describes the pores nucleation pressures. Each micropore within the representative volume element is modeled as a thick spherical shell made of plastically incompressible material. The treatment of porosity by a distribution of thick-walled spheres also allows for the inclusion of micro-inertia effects under conditions of shock and dynamic loading. The second order ordinary differential equation governing the microscopic porosity evolution is solved with a robust implicit procedure. A new Chebyshev collocation method is employed to approximate the porosity distribution and remapping is used to optimize memory usage. The adaptive approximation of the porosity distribution leads to a reduction of computational time and memory usage of up to two orders of magnitude. Moreover, the proposed model affords consistent performance: changing the nucleation pressure probability density function and/or the applied strain rate does not reduce accuracy or computational efficiency of the material model. The numerical performance of the model and algorithms presented is tested against three problems for high density tantalum: single void, one-dimensional uniaxial strain, and two-dimensional plate impact. Here, the results using the integration and algorithmic advances suggest a significant improvement in computational efficiency and accuracy over previous treatments for dynamic loading conditions.

42 ENGINEERING↗
DOE OSTI2015

Mixed valence and metamagnetism in a metal flux grown compound Eu{sub 2}Pt{sub 3}Si{sub 5}

A new compound Eu{sub 2}Pt{sub 3}Si{sub 5} with plate shaped morphology has been grown from excess In flux. The compound crystallizes in the orthorhombic U{sub 2}Co{sub 3}Si{sub 5} structure type, Ibam space group and the lattice parameters are a=10.007(2) Å, b=11.666(2) Å and c=6.0011(12) Å. The crystal structure of this compound can be conceived as inter-twinned chains of [Pt{sub 2}Si{sub 2}] and [PtSi{sub 3}] tetrahedra connected along [100] direction to give rise to a complex three dimensional [Pt{sub 3}Si{sub 5}] network. Temperature dependent magnetic susceptibility data suggests that Eu{sub 2}Pt{sub 3}Si{sub 5} undergoes a strong antiferromagnetic ordering (T{sub N}=19 K) followed by a weak ferromagnetic transition (T{sub C}=5.5 K). The effective magnetic moment/Eu obtained from susceptibility data is 6.78 μ{sub B} accounts mixed valent Eu with almost 85% divalent Eu, which is supported by X-ray absorption near edge spectroscopy. The compound undergoes a metamagnetic transition under applied magnetic field through a probable spin flop mechanism. - Graphical abstract: Eu{sub 2}Pt{sub 3}Si{sub 5}, a new member in the U{sub 2}Co{sub 3}Si{sub 5} (Ibam) family undergoes metamagnetic transition at high magnetic field and Eu is in mixed valence state. - Highlights: • A new compound Eu{sub 2}Pt{sub 3}Si{sub 5} has been synthesized using indium as an inactive metal flux. • The compound undergoes metamagnetic transition at higher field. • Eu in this compound resides in a mixed valence state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Ubiquity of Benford's law and emergence of the reciprocal distribution

In this paper, we apply the Law of Total Probability to the construction of scale-invariant probability distribution functions (pdf's), and require that probability measures be dimensionless and unitless under a continuous change of scales. If the scale-change distribution function is scale invariant then the constructed distribution will also be scale invariant. Repeated application of this construction on an arbitrary set of (normalizable) pdf's results again in scale-invariant distributions. The invariant function of this procedure is given uniquely by the reciprocal distribution, suggesting a kind of universality. Finally, we separately demonstrate that the reciprocal distribution results uniquely from requiring maximum entropy for size-class distributions with uniform bin sizes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Dynamics of ultra-intense circularly polarized solitons under inhomogeneous plasmas

The dynamics of the ultra-intense circularly polarized solitons under inhomogeneous plasmas are examined. The interaction is modeled by the Maxwell and relativistic hydrodynamic equations and is solved with fully implicit energy-conserving numerical scheme. The soliton is self-consistently generated by the interaction between laser and plasma on the vacuum-plasma interface, and the generation mechanism is well confirmed by two dimensional particle-in-cell simulation. It is shown that a propagating weak soliton can be decreased and reflected by increasing plasma background, which is consistent with the existing studies based on hypothesis of weak density response. However, it is found that ultra-intense soliton is well trapped and kept still when encountering increasing background. Probably, this founding can be applied for trapping and amplifying high-intensity laser-fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Radial distribution of charged particles in a magnetic field

The radial spread of charged particles emitted from a point source in a magnetic field is a potential source of systematic error for any experiment where magnetic fields guide charged particles to detectors with finite size. Assuming uniform probability as a function of the phase along the particle’s helical trajectory, an analytic solution for the radial probability distribution function follows which applies to experiments in which particles are generated throughout a volume that spans a sufficient length along the axis of a homogeneous magnetic field. This approach leads to the same result as a different derivation given by Dubbers et al., Nucl. Instrum. Methods Phys. Res., Sect. A 763, 112–119 (2014). But the constant phase approximation does not strictly apply to finite source volumes or fixed positions, which lead to local maxima in the radial distribution of emitted particles at the plane of the detector. A simple method is given to calculate such distributions, then the effect is demonstrated with data from a {sup 207}Bi electron-conversion source in the superconducting solenoid magnet spectrometer of the Ultracold Neutron facility at the Los Alamos Neutron Science Center. Implications for neutron beta decay spectroscopy are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Resilience Metrics for Building-Level Electrical Distribution Systems with Energy Storage

The energy system infrastructure that delivers power to a building's loads needs to be resilient to withstand and recover from extreme outages (e.g., grid faults that leave millions of people without power during severe weather events). Building-level electrical distribution systems (BEDSs) distribute power from a building's energy sources - including the grid, solar photovoltaic (PV) panels, and batteries - to its loads, including lighting, HVAC, and plug loads. BEDS with storage can provide resilience by distributing local electricity supply to critical loads during an outage. Quantitative metrics are needed to assess the resilience improvements associated with new BEDS and storage system technologies. In this paper, we apply an existing metric, the probability of outage survival curve (POSC), to BEDS with storage and propose novel metrics that improve upon POSC. Through a simulation-based case study, we demonstrate how these metrics are impacted by the BEDS design and how they can be used to design a resilient system.

buildings↗
DOE OSTI2022

Bayesian Optimization Framework for Imperfect Data or Models

Conventional Bayesian optimization methods implicitly assume that the data and model being optimized are “perfect.” This assumption leads to inaccurate posterior probability distribution functions (PDFs) when applied to “imperfect” data or models. The new Bayesian optimization framework presented in this report provides a way to parameterize the effect of imperfections usually encountered in a prior PDF of generalized data or a model on the posterior PDF. The effects of imperfections are parameterized by a set of constraints imposed on the posterior expectation values of deviations between the data and the model and on their covariance matrix elements. A particular set of values for these constraints conveys an evaluator’s best estimate of the effect of imperfections on the corresponding posterior expectation values. When a prior PDF of generalized data is assumed to be normal, an expression for a posterior PDF satisfying an arbitrary set of constraints is derived analytically for linear models. An analogous iterative algorithm is given for nonlinear models. The corresponding posterior PDF should be used to estimate any posterior expectation values in the presence of imperfections parameterized by that set of constraints. A posterior PDF of a conventional Bayesian optimization method is recovered analytically when all evaluator-specified constraints are set to zero (i.e., in the absence of any imperfections). The analytical expressions derived in this report for normal PDFs and linear models were verified numerically by a Metropolis–Hastings Monte Carlo method. The methods presented herein could be applied to any kind of data or models, including differential cross-section data or integral benchmark experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Artificial Intelligence and Machine Learning Support for Probabilistic Fracture Mechanics

In this research, artificial intelligence and machine learning (ML) methods are used to search an uncertain parameter space more efficiently for the most important inputs with respect to response sensitivities. These methods are applied to the Extremely Low Probability of Rupture (xLPR) probabilistic fracture mechanics code used at the U.S. Nuclear Regulatory Commission (NRC) in support of nuclear regulatory research. This report documents two separate but related sub-tasks: (1) ranking important uncertain input features with respect to target outputs, determined by convergence in confidence intervals for increasing sample sizes using simple random sampling; and (2) implementation of a reduced-order surrogate model for fast, approximate sample generation. Unoptimized readily available off-the-shelf ML models were used in both sub-tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A New Framework for Interstellar Medium Emission Line Models: Connecting Multiscale Simulations across Cosmological Volumes

The James Webb Space Telescope (JWST) and Atacama Large Millimeter/submillimeter Array have detected emission lines from the ionized interstellar medium (ISM) in some of the first galaxies at z ≳ 6. These measurements present an opportunity to better understand galaxy assembly histories and may allow important tests of state-of-the-art galaxy formation simulations. It is challenging, however, to model these lines in their proper cosmological context. In order to meet this challenge, we introduce a novel subgrid line emission modeling framework. The framework uses the high-z zoom-in simulation suite from the Feedback in Realistic Environments (FIRE) collaboration. The line emission signals from H II regions within each simulated FIRE galaxy are modeled using the semianalytic HIIL INES code. A machine learning approach is then used to determine the conditional probability distribution for the line luminosity to stellar-mass ratio from the H II regions around each simulated stellar particle. This conditional probability distribution can then be applied to predict the line luminosities around stellar particles in lower-resolution, yet larger volume cosmological simulations. As an example, we apply this approach to the IllustrisTNG simulations at z = 6. The resulting predictions for the [O II ], [O III ], and Balmer line luminosities as a function of star formation rate agree well with current observations. Our predictions differ, however, from related works in the literature, which lack detailed subgrid ISM models. This highlights the importance of our multiscale simulation modeling framework. Finally, we provide forecasts for future line luminosity function measurements from the JWST and quantify the cosmic variance in such surveys.

(ISM:) H II regions↗
NASA NTRS1975

Modeling transient faults in TMR computer systems

In this paper we report the development of a technique for modeling transient faults in redundant computer systems. Transient faults are characterized by their arrival rate and their duration. Fault detection, transient recovery, and the effect of permanent faults are included. A fault occurrence/recovery status state diagram is drawn to illustrate the operational status of the system while undergoing faults. The state diagram is used to formulate the equations for the mission failure probability. The techniques are then applied to a triple modular redundant computer system.

Merryman, P. M.↗
NASA NTRS1976

Multiplicity dependence of transverse momentum in hadronic collisions

The process of secondary-particle emission in hadron-hadron collisions is analytically studied using a simple model of hadron structure. The model neglects the 'size' of the hadron constituents, considering a hadron as a continuous distribution of matter according to a step function of radius R. A version of the eikonal approximation is applied to derive the relative probability for interaction and emission of secondaries when the impact parameter b is smaller than 2R. On the basis of these assumptions, and using the uncertainty relation, an empirical parameterization is obtained for the dependence of the transverse momentum of charged secondaries on their multiplicity in the case of high-energy proton-proton collisions. Comparison with experimental data at 28 GeV/c yields agreement to within about 3%. The analysis shows that at a fixed beam momentum, the transverse momentum decreases with increasing multiplicity, and that for a given multiplicity, the transverse momentum exhibits a slow increase with beam momentum.

Saint Amand, J.↗
NASA NTRS1983

FUNSTAT and statistical image representations

General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.

Parzen, E.↗