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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Anomalous Transport of High Energy Cosmic Rays in Galactic Superbubbles

High-energy cosmic rays may exhibit anomalous transport as they traverse and are accelerated by a collection of supernovae explosions in a galactic superbubble. Signatures of this anomalous transport can show up in the particles' evolution and their spectra. In a continuous-time-random- walk (CTRW) model assuming standard diffusive shock acceleration theory (DSA) for each shock encounter, and where the superbubble (an OB stars association) is idealized as a heterogeneous region of particle sources and sinks, acceleration and transport in the superbubble can be shown to be sub-diffusive. While the sub-diffusive transport can be attributed to the stochastic nature of the acceleration time according to DSA theory, the spectral break appears to be an artifact of transport in a finite medium. These CTRW simulations point to a new and intriguing phenomenon associated with the statistical nature of collective acceleration of high energy cosmic rays in galactic superbubbles.

Barghouty, Nasser F.↗
DOE OSTI2019

Continuous-Time Multidimensional Walks as an Integrable Model

We consider continuous-time random walks on multidimensional symplectic lattices. It is shown that the generating functions of random walks and the transition amplitudes of continuous-time quantum walks can be expressed through dynamical correlation functions of an exactly solvable model describing strongly correlated bosons on a chain, the so-called phase model. The number of random lattice paths with a fixed number of steps connecting the starting and ending points on the multidimensional lattice is expressed through solutions of the Bethe equations of the phase model. Its asymptotics is obtained in the limit of a large number of steps.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Searching for quasar candidates with periodic variations from the Zwicky Transient Facility: results and implications

ABSTRACT We conduct a systematic search for quasars with periodic variations from the archival photometric data of the Zwicky Transient Facility by cross-matching with the quasar catalogues of the Sloan Digital Sky Survey and Véron-Cetty and Véron. We first select out 184 primitive periodic candidates using the generalized Lomb–Scargle periodogram and autocorrelation function and then estimate their statistical significance of periodicity based on two red-noise models, i.e. damped random walk (DRW) and single power-law (SPL) models. As such, we finally identify 106 (DRW) and 86 (SPL) candidates with the most significant periodic variations out of 143 700 quasars. We further compare DRW and SPL models using Bayes factors, which indicate a relative preference of the SPL model for our primitive sample. We thus adopt the candidates identified with SPL as the final sample and summarize its basic properties. We extend the light curves of the selected candidates by supplying other archival survey data to verify their periodicity. However, only three candidates (with 6–8 cycles of periods) meet the selection criteria. This result clearly implies that, instead of being strictly periodic, the variability must be quasi-periodic or caused by stochastic red-noise. This exerts a challenge to the existing search approaches and calls for developing new effective methods.

Chen, Yong-Jie (ORCID:0000000342807673)↗
NASA NTRS1996

A test of the deadline model for speed-accuracy tradeoffs

Two experiments were conducted to evaluate the deadline model for speed-accuracy tradeoffs. According to the deadline model, participants in speeded-response tasks terminate stimulus discrimination as soon as it has run to completion or as soon as a predetermined time deadline has arrived, whichever comes first. Speed is traded for accuracy by varying the time deadlines; short deadlines yield fast but sometimes inaccurate responses, whereas long deadlines allow for slow, accurate responses. A new prediction of this model, based on a comparison of reaction time distributions, was derived and tested in experiments involving the joint manipulation of speed stress and stimulus discriminability. Clear violations of this prediction were observed when participants made relative brightness judgments (Experiment 1) and when they made lexical decisions (Experiment 2), rejecting both the deadline model and the fast-guess model. Several alternative models for speed-accuracy tradeoffs, including random-walk and accumulator models, are compatible with the results.

Discrimination (Psychology)↗
DOE OSTI2014

Connecting the dots: Semi-analytical and random walk numerical solutions of the diffusion–reaction equation with stochastic initial conditions

We study a system with bimolecular irreversible kinetic reaction A+B→∅ where the underlying transport of reactants is governed by diffusion, and the local reaction term is given by the law of mass action. We consider the case where the initial concentrations are given in terms of an average and a white noise perturbation. Our goal is to solve the diffusion–reaction equation which governs the system, and we tackle it with both analytical and numerical approaches. To obtain an analytical solution, we develop the equations of moments and solve them approximately. To obtain a numerical solution, we develop a grid-less Monte Carlo particle tracking approach, where diffusion is modeled by a random walk of the particles, and reaction is modeled by annihilation of particles. The probability of annihilation is derived analytically from the particles' co-location probability. We rigorously derive the relationship between the initial number of particles in the system and the amplitude of white noise represented by that number. This enables us to compare the particle simulations and the approximate analytical solution and offer an explanation of the late time discrepancies. - Graphical abstract:.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Quantum information approach to the implementation of a neutron cavity

Abstract Using the quantum information model of dynamical diffraction we consider a neutron cavity composed of two perfect crystal silicon blades capable of containing the neutron wavefunction. We show that the internal confinement of the neutrons through Bragg diffraction can be modelled by a quantum random walk. Furthermore, we introduce a toolbox for modelling crystal imperfections such as surface roughness and defects. Good agreement is found between the simulation and the experimental implementation, where leakage beams are present, modelling of which is impractical with the conventional theory of dynamical diffraction. Analysis of the standing neutron waves is presented in regards to the crystal geometry and parameters; and the conditions required for well-defined bounces are derived. The presented results enable new approaches to studying the setups utilizing neutron confinement, such as the experiments to measure neutron magnetic and electric dipole moments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2000

Comparison of On-Orbit Performance of Rate Sensing Gyroscopes

This work presents results from the study of a large volume of spacecraft flight data pertaining to gyroscope performance. We have examined long and short term trends of gyroscope biase of first, an exact solution for the time-dependence of the attitude part of the state error covariance, averaged over the three spacecraft axes, is given. This solution is more complete than the usual cubic polynomial for the variance in that it includes coupling among the three gyroscope axes and includes an important term arising from the initial correlations. Second, several continuous 24-hour spans of gyroscope data are examined to verify the short-term statistical model. This analysis demonstrates that in-flight data can be used to determine the strength of the white noise driving the random walk of the gyroscope bias. This may be useful for postlaunch improvement to the noise model and for diagnosing the health of the gyroscope. Third, the long-term trends in gyroscope biases show a nearly linear systematic variation over time scales of years. This has been found on three different missions. While the random walk model is adequate as a basis for onboard Kalman filters or for state estimation using relatively short time spans, these trends indicate that some applications could benefit by accounting for the secular changes in the biases. One example is a new gyroscope calibration method that is under development that allows for multi-epoch bias solutions.

Sedlak, Joseph↗
DOE OSTI2015

Comparison of Two Models for Damage Accumulation in Simulations of System Performance

A comprehensive simulation study of system performance needs to address variations in component behavior, variations in phenomenology, and the coupling between phenomenology and component failure. This paper discusses two models of this: 1. damage accumulation is modeled as a random walk process in each time history, with component failure occurring when damage accumulation reaches a specified threshold; or 2. damage accumulation is modeled mechanistically within each time history, but failure occurs when damage reaches a time-history-specific threshold, sampled at time zero from each component’s distribution of damage tolerance. A limiting case of the latter is classical discrete-event simulation, with component failure times sampled a priori from failure time distributions; but in such models, the failure times are not typically adjusted for operating conditions varying within a time history. Nowadays, as discussed below, it is practical to account for this. The paper compares the interpretations and computational aspects of the two models mentioned above.

42 ENGINEERING↗
DOE OSTI2016

A one-dimensional stochastic approach to the study of cyclic voltammetry with adsorption effects

In this study, a one-dimensional stochastic model based on the random walk approach is used to simulate cyclic voltammetry. The model takes into account mass transport, kinetics of the redox reactions, adsorption effects and changes in the morphology of the electrode. The model is shown to display the expected behavior. Furthermore, the model shows consistent qualitative agreement with a finite difference solution. This approach allows for an understanding of phenomena on a microscopic level and may be useful for analyzing qualitative features observed in experimentally recorded signals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

SU-E-J-115: Using Markov Chain Modeling to Elucidate Patterns in Breast Cancer Metastasis Over Time and Space

Purpose: Traditionally, breast cancer metastasis is described as a process wherein cancer cells spread from the breast to multiple organ systems via hematogenous and lymphatic routes. Mapping organ specific patterns of cancer spread over time is essential to understanding metastatic progression. In order to better predict sites of metastases, here we demonstrate modeling of the patterned migration of metastasis. Methods: We reviewed the clinical history of 453 breast cancer patients from Memorial Sloan Kettering Cancer Center who were non-metastatic at diagnosis but developed metastasis over time. We used the variables of organ site of metastases as well as time to create a Markov chain model of metastasis. We illustrate the probabilities of metastasis occurring at a given anatomic site together with the probability of spread to additional sites. Results: Based on the clinical histories of 453 breast cancer patients who developed metastasis, we have learned (i) how to create the Markov transition matrix governing the probabilities of cancer progression from site to site; (ii) how to create a systemic network diagram governing disease progression modeled as a random walk on a directed graph; (iii) how to classify metastatic sites as ‘sponges’ that tend to only receive cancer cells or ‘spreaders’ that receive and release them; (iv) how to model the time-scales of disease progression as a Weibull probability distribution function; (v) how to perform Monte Carlo simulations of disease progression; and (vi) how to interpret disease progression as an entropy-increasing stochastic process. Conclusion: Based on our modeling, metastatic spread may follow predictable pathways. Mapping metastasis not simply by organ site, but by function as either a ‘spreader’ or ‘sponge’ fundamentally reframes our understanding of metastatic processes. This model serves as a novel platform from which we may integrate the evolving genomic landscape that drives cancer metastasis. PS-OC Trans-Network Project Grant Award for “Data Assimilation and ensemble statistical forecasting methods applied to the MSKCC longitudinal metastatic breast cancer cohort.”.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Cascade annealing simulations of bcc iron using object kinetic Monte Carlo

Simulations of displacement cascade annealing were carried out using object kinetic Monte Carlo based on an extensive MD database including various primary knock-on atom energies and directions. The sensitivity of the results to a broad range of material and model parameters was examined. The diffusion mechanism of interstitial clusters has been identified to have the most significant impact on the fraction of stable interstitials that escape the cascade region. The maximum level of recombination was observed for the limiting case in which all interstitial clusters exhibit 3D random walk diffusion. The OKMC model was parameterized using two alternative sets of defect migration and binding energies, one from ab initio calculations and the second from an empirical potential. The two sets of data predict essentially the same fraction of surviving defects but different times associated with the defect escape processes. This study provides a comprehensive picture of the first phase of long-term defect evolution in bcc iron and generates information that can be used as input data for mean field rate theory (MFRT) to predict the microstructure evolution of materials under irradiation. In addition, the limitations of the current OKMC model are discussed and a potential way to overcome these limitations is outlined.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SDSS J14584479+3720215: A BENCHMARK JHK{sub S} BLAZAR LIGHT CURVE FROM THE 2MASS CALIBRATION SCANS

Active galactic nuclei (AGNs) are well-known to exhibit flux variability across a wide range of wavelength regimes, but the precise origin of the variability at different wavelengths remains unclear. To investigate the relatively unexplored near-IR (NIR) variability of the most luminous AGNs, we conduct a search for variability using well sampled JHK{sub s}-band light curves from the Two Micron All Sky Survey (2MASS) calibration fields. Our sample includes 27 known quasars with an average of 924 epochs of observation over three years, as well as one spectroscopically confirmed blazar (SDSS J14584479+3720215) with 1972 epochs of data. This is the best-sampled NIR photometric blazar light curve to date, and it exhibits correlated, stochastic variability that we characterize with continuous auto-regressive moving average (CARMA) models. None of the other 26 known quasars had detectable variability in the 2MASS bands above the photometric uncertainty. A blind search of the 2MASS calibration field light curves for active galactic nucleus (AGN) candidates based on fitting CARMA(1,0) models (damped-random walk) uncovered only seven candidates. All seven were young stellar objects within the ρ Ophiuchus star forming region, five with previous X-ray detections. A significant γ-ray detection (5σ) for the known blazar using 4.5 yr of Fermi photon data is also found. We suggest that strong NIR variability of blazars, such as seen for SDSS J14584479+3720215, can be used as an efficient method of identifying previously unidentified γ-ray blazars, with low contamination from other AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

The Ehrlich–Schwoebel barrier on an oxide surface: a combined Monte-Carlo and in situ scanning tunneling microscopy approach

The controlled growth of epitaxial films of complex oxides requires an atomistic understanding of key parameters determining final film morphology, such as termination dependence on adatom diffusion, and height of the Ehrlich–Schwoebel (ES) barrier. In this study, through an in situ scanning tunneling microscopy study of mixed-terminated La 5/8 Ca 3/8 MnO 3 (LCMO) films, we image adatoms and observe pile-up at island edges. Image analysis allows determination of the population of adatoms at the edge of islands and fractions on A-site and B-site terminations. A simple Monte-Carlo model, simulating the random walk of adatoms on a sinusoidal potential landscape using Boltzmann statistics is used to reproduce the experimental data, and provides an estimate of the ES barrier as ~0.18 ± 0.04 eV at T = 1023 K, similar to those of metal adatoms on metallic surfaces. In conclusion, these studies highlight the utility of in situ imaging, in combination with basic Monte-Carlo methods, in elucidating the factors which control the final film growth in complex oxides.

36 MATERIALS SCIENCE↗
NASA NTRS1983

Numerical solution of the problem of flame propagation by the use of the random element method

A numerical, grid-free algorithm is presented for one-dimensional reaction-diffusion model of laminar flame propagation in premixed gases. It is based on the random element method we developed for the analysis of diffusional processes. The effect of combustion is taken into account by applying the principle of fractional steps to separate the process of diffusion, modeled by the random walk of computational elements, from the exothermic effects of chemical reaction, monitoring their strength. The validity of the algorithm is demonstrated by application to flame propagation problems for which exact solutions exist. The flame speed evaluated by its use oscillates around the exact value at a relatively small amplitude, while the temperature and species concentration profiles are self-correcting in their convergence to the exact solution. A satisfactory resolution is obtained by the use of quite a small number of computational elements which automatically adjust their distribution of fit sharp gradients.

Ghoniem, A. F.↗
NASA NTRS2017

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

manual control↗
DOE OSTI2021

A Computational Information Criterion for Particle-Tracking with Sparse or Noisy Data

Traditional probabilistic methods for the simulation of advection-diffusion equations (ADEs) often overlook the entropic contribution of the discretization, e.g., the number of particles, within associated numerical methods. Many times, the gain in accuracy of a highly discretized numerical model is outweighed by its associated computational costs or the noise within the data. Herein, we address the question of how many particles are needed in a simulation to best approximate and estimate parameters in one-dimensional advective-diffusive transport. To do so, we use the well-known Akaike Information Criterion (AIC) and a recently-developed correction called the Computational Information Criterion (COMIC) to guide the model selection process. Random-walk and mass-transfer particle tracking methods are employed to solve the model equations at various levels of discretization. Numerical results demonstrate that the COMIC provides an optimal number of particles that can describe a more efficient model in terms of parameter estimation and model prediction compared to the model selected by the AIC even when the data is sparse or noisy, the sampling volume is not uniform throughout the physical domain, or the error distribution of the data is non-IID Gaussian.

97 MATHEMATICS AND COMPUTING↗