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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

A Method to Estimate the Probability That Any Individual Lightning Stroke Contacted the Surface Within Any Radius of Any Point

A technique has been developed to calculate the probability that any nearby lightning stroke is within any radius of any point of interest. In practice, this provides the probability that a nearby lightning stroke was within a key distance of a facility, rather than the error ellipses centered on the stroke. This process takes the current bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to get the probability that the stroke is inside any specified radius. This new facility-centric technique will be much more useful to the space launch customers and may supersede the lightning error ellipse approach discussed in [5], [6].

Huddleston, Lisa L.↗
DOE OSTI2024

Estimating the Contributions to Human Error Probability from the Convolution of the Distribution of Time Available and Time Required

As part of their duties, Human Reliability Analysis must often evaluate if crews in nuclear power plants (NPPs) can complete tasks associated with a human-failure event within time limits. For example, the time required in NPP scenarios is determined by systematic and structured walkthroughs, feasibility studies, recorded times from training exercises, and interviews with experienced operators and experts. Typically, a point estimate is derived for the estimate (mean, maximum, or 95th percentile of time required). Using point-estimate values can mask the risk associated with variability among crews, plant conditions and set-up, environmental conditions, and other impact factors under which these actions are executed. While point estimates for time required and time available have served the industry well, without considering the uncertainty they could lead to biased understanding about the risk. The Integrated Human Event Analysis System - General Methodology (IDHEAS-G) model (developed by the US Nuclear Regulatory Commission, NRC) for human error probability calculates human error probability by summing two probabilities: insufficient time and cognitive error. As such, the model takes a more holistic approach by considering the full distributions for time required and time available to calculate the human error probability because the time available to complete the task is insufficient. In this study, we expand on the work of the NRC and discuss methods for estimating these time considerations. For example, for the time required, the impact of Performance Influencing Factors (PIFs) on the distribution was divided into impacts that are aleatory in nature, such as crew-to-crew variability, and those that are epistemic (i.e., the PIFs). Starting with the factors that introduce aleatory uncertainty, a first-order distribution was developed from a large set of time required (i.e., NPP task completion times) data for the range of operator actions that occur in the NPP control room under simulated accident conditions. The first-order distribution can then be adjusted to account for epistemic uncertainty using research associated with the impact of applicable PIFs on the time required. We also develop guidance for analysts to address the probability distributions for the time available. The guidance we developed on how to estimate time required and time available distributions is based on the identification of pertinent research and data, data analyses, and expert knowledge elicitation.

human error probability, human performance, time e↗
DOE OSTI2022

Retrieval of the molecular orientation distribution from atom-pair angular distributions

Imaging laser-induced rotational dynamics is an important and active field due to its applications in capturing reactions in the molecular frame and in molecular imaging. Experimental measurement of the molecular orientation distribution, as a function of the Euler angles, has only been demonstrated for special cases when the detectable signal is generated along the molecular symmetry axis. Here we developed the general theory that maps the probability density distribution of the molecular orientation to the atom-pair angular distributions for nonlinear molecules. With the theory, the molecular orientation distribution can be retrieved from the measured atom-pair angular distribution, which we demonstrate experimentally using ultrafast electron diffractive imaging of impulsively aligned trifluoro-iodomethane molecules. Here, the retrieved molecular orientation distribution is in good agreement with direct numerical simulations of the time-dependent Schrodinger equation using the experimental conditions. Unlike the existing retrieval methods, the retrieval method does not require solving Schrodinger equation, works for any alignment method, and is in principle applicable to asymmetric top molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2007

Chromosome Model reveals Dynamic Redistribution of DNA Damage into Nuclear Sub-domains

Several proteins involved in the response to DNA double strand breaks (DSB) form microscopically visible nuclear domains, or foci, after exposure to ionizing radiation. Radiation-induced foci (RIF) are believed to be located where DNA damage is induced. To test this assumption, we analyzed the spatial distribution of 53BP1, phosphorylated ATM and gammaH2AX RIF in cells irradiated with high linear energy transfer (LET) radiation. Since energy is randomly deposited along high-LET particle paths, RIF along these paths should also be randomly distributed. The probability to induce DSB can be derived from DNA fragment data measured experimentally by pulsed-field gel electrophoresis. We used this probability in Monte Carlo simulations to predict DSB locations in synthetic nuclei geometrically described by a complete set of human chromosomes, taking into account microscope optics from real experiments. As expected, simulations produced DNA-weighted random (Poisson) distributions. In contrast, the distributions of RIF obtained as early as 5 min after exposure to high LET (1 GeV/amu Fe) were non-random. This deviation from the expected DNA-weighted random pattern can be further characterized by relative DNA image measurements. This novel imaging approach shows that RIF were located preferentially at the interface between high and low DNA density regions, and were more frequent in regions with lower density DNA than predicted. This deviation from random behavior was more pronounced within the first 5 min following irradiation for phosphorylated ATM RIF, while gammaH2AX and 53BP1 RIF showed very pronounced deviation up to 30 min after exposure. These data suggest the existence of repair centers in mammalian epithelial cells. These centers would be nuclear sub-domains where DNA lesions would be collected for more efficient repair.

Costes, Sylvain V.↗
NASA NTRS1996

The calculation of radial dose from heavy ions: predictions of biological action cross sections

The track structure model of heavy ion cross sections was developed by Katz and co-workers in the 1960s. In this model the action cross section is evaluated by mapping the dose-response of a detector to gamma rays (modeled from biological target theory) onto the radial dose distribution from delta rays about the path of the ion. This is taken to yield the radial distribution of probability for a "hit" (an interaction leading to an observable end-point). Radial integration of the probability yields the cross section. When different response from ions of different Z having the same stopping power is observed this model may be indicated. Since the 1960s there have been several developments in the computation of the radial dose distribution, in the measurement of these distributions, and in new radiobiological data against which to test the model. The earliest model, by Butts and Katz made use of simplified delta ray distribution functions, of simplified electron range-energy relations, and neglected angular distributions. Nevertheless it made possible the calculation of cross sections for the inactivation of enzymes and viruses, and allowed extension to tracks in nuclear emulsions and other detectors and to biological cells. It set the pattern for models of observable effects in the matter through which the ion passed. Here we outline subsequent calculations of radial dose which make use of improved knowledge of the electron emission spectrum, the electron range-energy relation, the angular distribution, and some considerations of molecular excitation, of particular interest both close to the path of the ion and the outer limits of electron penetration. These are applied to the modeling of action cross sections for the inactivation of several strains of E-coli and B. subtilis spores where extensive measurements in the "thin-down" region have been made with heavy ion beams. Such calculations serve to test the radial dose calculations at the outer limit of electron penetration. We lack data from which to test these calculations in regions close to the path of the ion aside from our earliest work on latent tracks in plastics, though it appears that the criterion then suggested for the threshold of track formation, of a minimal dose at a minimal distance (of about 20 angstroms, in plastics), remains valid.

NASA Discipline Radiation Health↗
NASA NTRS1993

On the probability of magnification by cosmologically distributed gravitational lenses

An analytical method for calculating the statistical properties of source magnification caused by gravitational lenses randomly distributed throughout the universe is presented. Two lenses are considered at different redshifts to show that such an assumption is a statistically adequate approximation. The derived general formulas are applied to point-mass lenses with both point and extended sources. Analytical results of the magnification probability for point sources are accurate to within 10 percent in comparison with the available numerical simulations to moderate redshifts of less than about 2. In terms of the flux conservation, the results are accurate to within 18 percent at a redshift of 6 with respect to the Dyer-Roeder model of a clumpy universe. It is concluded that the present formulas are adequate for statistical studies of magnification by random gravitational lenses on cosmological scales.

Pei, Yichuan C.↗
DOE OSTI2021

Machine Learning Predictions of Transition Probabilities in Atomic Spectra

Forward modeling of optical spectra with absolute radiometric intensities requires knowledge of the individual transition probabilities for every transition in the spectrum. In many cases, these transition probabilities, or Einstein A-coefficients, quickly become practically impossible to obtain through either theoretical or experimental methods. Complicated electronic orbitals with higher order effects will reduce the accuracy of theoretical models. Experimental measurements can be prohibitively expensive and are rarely comprehensive due to physical constraints and sheer volume of required measurements. Due to these limitations, spectral predictions for many element transitions are not attainable. In this work, we investigate the efficacy of using machine learning models, specifically fully connected neural networks (FCNN), to predict Einstein A-coefficients using data from the NIST Atomic Spectra Database. For simple elements where closed form quantum calculations are possible, the data-driven modeling workflow performs well but can still have lower precision than theoretical calculations. For more complicated nuclei, deep learning emerged more comparable to theoretical predictions, such as Hartree–Fock. Unlike experiment or theory, the deep learning approach scales favorably with the number of transitions in a spectrum, especially if the transition probabilities are distributed across a wide range of values. It is also capable of being trained on both theoretical and experimental values simultaneously. In addition, the model performance improves when training on multiple elements prior to testing. The scalability of the machine learning approach makes it a potentially promising technique for estimating transition probabilities in previously inaccessible regions of the spectral and thermal domains on a significantly reduced timeline.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2003

Probability of Detecting Planets with Microlensing

The proposed research to determine the probability of detecting extra solar planets from the ground with microlensing was completely accomplished during the grant period. A summary of the publications and their abstracts follow below. The publications include: 1) On microlensing rates and optical depth toward the Galactic center; 2) Newly discovered brown dwarfs not seen in microlensing timescale frequency distribution? 3) Probability of detecting a planetary companion during a microlensing event; 4) Comparison of a ground-based microlensing search for planets with a search from space; 5) Secular evolution of hierarchical planetary systems.

Peale, S. J.↗
NASA NTRS1973

Uranium concentration and distribution in six peridotite inclusions of probable mantle origin

Fission-track activation was used to investigate uranium concentration and distribution in peridotite inclusions in alkali basalt from six localities. Whole-rock uranium concentrations range from 24 to 82 ng/g. Most of the uranium is uniformly distributed in the major silicate phases - olivine, orthopyroxene, and clinopyroxene. Chromian spinels may be classified into two groups on the basis of their uranium content - those which have less than 10 ng/g and those which have 100 to 150 ng/g U. In one sample accessory hydrous phases, phlogopite and hornblende, contain 130 and 300 ng/g U, respectively. The contact between the inclusion and the host basalt is usually quite sharp. Glassy or microcrystalline veinlets found in some samples contain more than 1 microgram/g. Very little uranium is associated with microcrystals of apatite. These results agree with some earlier investigators, who have concluded that suboceanic peridotites contain too little uranium to account for normal oceanic heat flow by conduction alone.

Haines, E. L.↗
DOE OSTI2025

Bayesian inference of nuclear-matter density from proton scattering

Background: Proton elastic scattering at intermediate energy is widely employed as a tool for determining the matter radius of atomic nuclei. Here, the sensitivity of the approach relies on high-resolution measurements at small scattering angles and low-momentum transfer. Under these conditions, the Glauber multiple scattering theory accurately describes the proton-nucleus elastic cross section. Purpose: Investigate the sensitivity of the Glauber multiple scattering theory to uncertainties associated with input parameters such as the nuclear-matter density distribution and nucleon-nucleon data. Method: A joint Bayesian inference was performed using 12 angular distributions of elastic scattering at different energies on 58 Ni, 90 Zr, and 208 Pb targets. A Metropolis-Hastings algorithm was implemented to make an uncertainty quantification analysis for the input parameters used in the Glauber multiple scattering theory. Results: The experimental cross sections were fitted simultaneously using a joint Bayesian inference approach. Posterior probability density distributions of 42 input parameters were obtained from the analysis. A moderate correlation between the nuclear density parameters and the nucleon-nucleon cross sections was found. This correlation impacts the extraction of the nuclear-matter radius. Conclusions: The present analysis provided a consistent method for extracting the nuclear-matter density distribution of 58 Ni, 90 Zr, and 208 Pb from data across different incident energies. Due to the correlation of the nucleon-nucleon cross sections with the other input parameters, a constrained Bayesian inference using free nucleon-nucleon cross section data was performed. The nuclear-matter radii obtained from the analysis are in good agreement with multiple results reported in the literature.

190 ≤ A ≤ 219↗
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↗
NASA NTRS1979

Viking magnetic properties experiment - Extended mission results

The backhoe magnets on Viking Lander (VL) 2 were successfully cleaned, followed by a test involving successive insertions of the cleaned backhoe into the surface. Rapid saturation of the magnets confirmed evidence from primary mission results that the magnetic mineral in the Martian surface is widely distributed, most probably in the form of composite particles of magnetic and nonmagnetic minerals. An image of the VL 2 backhoe taken via the X4 magnifying mirror demonstrates the fine-grained nature of the attracted magnetic material. The presence of maghemite and its occurrence as a pigment in, or a thin coating on, all mineral particles or as discrete, finely divided and widely distributed crystallites, are consistent with data from the inorganic analysis experiments and with laboratory simulations of results of the biology experiments on Mars.

Hargraves, R. B.↗
NASA NTRS1987

Stochastic estimation of organized structures in turbulent channel flow

Linear stochastic estimation is used to approximate the conditional vector fields associated with high Reynolds stress producing events in numerically simulated turbulent channel flow. Joint probability density distributions of u-v are presented for y(+) between 1.35 and 180, and at each position the u-v values that make the greatest contributions to the average uv3 are used to define conditional ejection- and sweep-type events. In the y-z plane the conditional fields appear to be pairs of counter-rotating vortices. When the conditional event defined by the weighted probability density function is specified at a point close to the wall, the spacing and size of these eddies are consistent with the accepted wall streak spacing. As this point moves outwards, the eddy size increases significantly. An abrupt change in the flow angle occurs in the buffer layer and may indicate transition from streamwise oriented wall layer structures to hairpin vortices characterizing the outer layer.

Moin, P.↗
DOE OSTI2022

Statistical perspective on embrittling potency for intergranular fracture

Embrittling potency is a thermodynamic metric that assesses the influence of solute segregation to a grain boundary (GB) on intergranular fracture. Historically, authors of studies have reported embrittling potency as a single scalar value, assuming a single segregation site of importance at a GB and a particular cleavage plane. However, the topography of intergranular fracture surfaces is not generally known a priori. Accordingly, we, in this study, present a statistical ensemble approach to compute embrittling potency, where many free surface (FS) permutations are systematically considered to model fracture of a GB. The result is a statistical description of the thermodynamics of GB embrittlement. As a specific example, embrittling potency distributions are presented for Cr segregation to sites at two Ni $\langle 111 \rangle$ symmetric tilt GBs using atomistic simulations. We show that the average embrittling potency for a particular GB site, considering an ensemble of FS permutations, is not equal to the embrittling potency computed using the lowest energy pair of FSs. A mean GB embrittlement is proposed, considering both the likelihood of formation of a particular FS and the probability of solute occupancy at each GB site, to compare the relative embrittling behavior of two distinct GBs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Kinetic theory of particle-in-cell simulation plasma and the ensemble averaging technique

Abstract We derive the kinetic theory of fluctuations in physically and numerically stable particle-in-cell (PIC) simulations of electrostatic plasmas. The starting point is the single-time correlation at the start of the simulation between the statistical fluctuations of the weighted densities of macroparticle centers in the plasma particle phase-space. The fluctuations are associated with different initial conditions, typically due to the random initial conditions (in velocity space) of the macroparticles/simulation plasma, assigned according to their initial distribution of probability. The single-time correlations at all time steps and in each spatial grid cell are then determined from the Laplace–Fourier transforms of the discretized Klimontovich-like equation for the macroparticles and Maxwell’s equations for the fields, as computed by modern PIC codes. We recover the expressions for the electrostatic field and the plasma particle density fluctuation autocorrelation spectra as well as the kinetic equations describing the average evolution of PIC-simulated plasma particles, first derived by Langdon (1970b Proc. 4th Conf. Numerical Simulation of Plasmas ) using a test macroparticle approach perturbing a discretized Vlasovian plasma and then averaging the obtained physical quantity over the initial macroparticle velocity distribution. We generalize and extend these results to the modern algorithms in PIC codes using arbitrary macroparticle weights. Analytical estimates of statistical fluctuation amplitudes are derived as a function of the plasma simulation parameters, using the central limit theorem in the limit of a large number of macroparticles per cell. The theory is then used to analyze the ensemble averaging technique of PIC simulations where statistical averages are performed over ensembles of PIC simulations, modeling the same plasma physics problem but using different statistical realizations of the initial distribution functions of the macroparticles. This method is illustrated by linear Landau damping uncovering (from noise, which is usually considered numerical) the physical fluctuations driven by a single small amplitude electrostatic wave perturbing a PIC simulation plasma in equilibrium.

fluctuations correlations↗
DOE OSTI2021

Improving probabilistic infectious disease forecasting through coherence

With an estimated $10.4 billion in medical costs and 31.4 million outpatient visits each year, influenza poses a serious burden of disease in the United States. To provide insights and advance warning into the spread of influenza, the U.S. Centers for Disease Control and Prevention (CDC) runs a challenge for forecasting weighted influenza-like illness (wILI) at the national and regional level. Many models produce independent forecasts for each geographical unit, ignoring the constraint that the national wILI is a weighted sum of regional wILI, where the weights correspond to the population size of the region. We propose a novel algorithm that transforms a set of independent forecast distributions to obey this constraint, which we refer to as probabilistically coherent. Enforcing probabilistic coherence led to an increase in forecast skill for 79% of the models we tested over multiple flu seasons, highlighting the importance of respecting the forecasting system’s geographical hierarchy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Stochastic microstructural analysis of ceramic matrix composites using a high-fidelity multiscale framework

This paper presents a high-fidelity multiscale framework to simulate the mechanical behavior of ceramic matrix composites (CMCs), accounting for the complex micromorphology captured using detailed material characterization. First, high-resolution micrographs are obtained for the specific carbon fiber silicon-carbide-nitride matrix (C/SiNC) CMC to characterize the variability of the architectural features and manufacturing-induced defects at the microscale. An image processing algorithm is then used to precisely estimate the size and distribution of all subscale features and defects from the micrographs. The information is then used to generate a three-dimensional stochastic representative volume element (SRVE) to reconstruct microscale constituents accounting for the variability. As a result, the generated SRVEs are simulated using the high-fidelity generalized method of cells (HFGMC) micromechanics theory to investigate the effects of defects on the elastic properties of C/SiNC CMCs.

Ceramic Matrix Composites↗