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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

THE EVOLUTION OF ACTIVE GALACTIC NUCLEI AND THEIR SPINS

Massive black holes (MBHs), in contrast to stellar mass black holes, are expected to substantially change their properties over their lifetime. MBH masses increase by several orders of magnitude over a Hubble time, as illustrated by Sołtan's argument. MBH spins also must evolve through the series of accretion and mergers events that increase the masses of MBHs. We present a simple model that traces the joint evolution of MBH masses and spins across cosmic time. Our model includes MBH-MBH mergers, merger-driven gas accretion, stochastic fueling of MBHs through molecular cloud capture, and a basic implementation of accretion of recycled gas. This approach aims at improving the modeling of low-redshift MBHs and active galactic nuclei (AGNs), whose properties can be more easily estimated observationally. Despite the simplicity of the model, it does a good job capturing the global evolution of the MBH population from z ∼ 6 to today. Under our assumptions, we find that the typical spin and radiative efficiency of MBHs decrease with cosmic time because of the increased incidence of stochastic processes in gas-rich galaxies and MBH-MBH mergers in gas-poor galaxies. At z = 0, the spin distribution in gas-poor galaxies peaks at spins 0.4-0.8 and is not strongly mass dependent. MBHs in gas-rich galaxies have a more complex evolution, with low-mass MBHs at low redshift having low spins and spins increasing at larger masses and redshifts. We also find that at z > 1 MBH spins are on average the highest in high luminosity AGNs, while at lower redshifts these differences disappear.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Lagrangian velocity and acceleration correlations of large inertial particles in a closed turbulent flow

We investigate the response of large inertial particle to turbulent fluctuations in an inhomogeneous and anisotropic flow. We conduct a Lagrangian study using particles both heavier and lighter than the surrounding fluid, and whose diameters are comparable to the flow integral scale. Both velocity and acceleration correlation functions are analyzed to compute the Lagrangian integral time and the acceleration time scale of such particles. The knowledge of how size and density affect these time scales is crucial in understanding particle dynamics and may permit stochastic process modelization using two-time models (for instance, Sawford’s). As particles are tracked over long times in the quasi-totality of a closed flow, the mean flow influences their behaviour and also biases the velocity time statistics, in particular the velocity correlation functions. By using a method that allows for the computation of turbulent velocity trajectories, we can obtain unbiased Lagrangian integral time. This is particularly useful in accessing the scale separation for such particles and to comparing it to the case of fluid particles in a similar configuration.

42 ENGINEERING↗
DOE OSTI2014

Resonant activation in a colored multiplicative thermal noise driven closed system

In this paper, we have demonstrated that resonant activation (RA) is possible even in a thermodynamically closed system where the particle experiences a random force and a spatio-temporal frictional coefficient from the thermal bath. For this stochastic process, we have observed a hallmark of RA phenomena in terms of a turnover behavior of the barrier-crossing rate as a function of noise correlation time at a fixed noise variance. Variance can be fixed either by changing temperature or damping strength as a function of noise correlation time. Our another observation is that the barrier crossing rate passes through a maximum with increase in coupling strength of the multiplicative noise. If the damping strength is appreciably large, then the maximum may disappear. Finally, we compare simulation results with the analytical calculation. It shows that there is a good agreement between analytical and numerical results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Communication: Memory effects and active Brownian diffusion

A self-propelled artificial microswimmer is often modeled as a ballistic Brownian particle moving with constant speed aligned along one of its axis, but changing direction due to random collisions with the environment. Similarly to thermal noise, its angular randomization is described as a memoryless stochastic process. Here, we speculate that finite-time correlations in the orientational dynamics can affect the swimmer’s diffusivity. To this purpose, we propose and solve two alternative models. In the first one, we simply assume that the environmental fluctuations governing the swimmer’s propulsion are exponentially correlated in time, whereas in the second one, we account for possible damped fluctuations of the propulsion velocity around the swimmer’s axis. The corresponding swimmer’s diffusion constants are predicted to get, respectively, enhanced or suppressed upon increasing the model memory time. Possible consequences of this effect on the interpretation of the experimental data are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

ON THE STRENGTH OF THE HEMISPHERIC RULE AND THE ORIGIN OF ACTIVE-REGION HELICITY

Vector magnetograph and morphological observations have shown that the solar magnetic field tends to have negative (positive) helicity in the northern (southern) hemisphere, although only ∼60%-70% of active regions appear to obey this 'hemispheric rule'. In contrast, at least ∼80% of quiescent filaments and filament channels that form during the decay of active regions follow the rule. We attribute this discrepancy to the difficulty in determining the helicity sign of newly emerged active regions, which are dominated by their current-free component; as the transverse field is canceled at the polarity inversion lines, however, the axial component becomes dominant there, allowing a more reliable determination of the original active-region chirality. We thus deduce that the hemispheric rule is far stronger than generally assumed, and cannot be explained by stochastic processes. Earlier studies have shown that the twist associated with the axial tilt of active regions is too small to account for the observed helicity; here, both tilt and twist are induced by the Coriolis force acting on the diverging flow in the emerging flux tube. However, in addition to this east-west expansion about the apex of the loop, each of its legs must expand continually in cross section during its rise through the convection zone, thereby acquiring a further twist through the Coriolis force. Since this transverse pressure effect is not limited by drag or tension forces, the final twist depends mainly on the rise time, and may be large enough to explain the observed active-region helicity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Experimental sloshing pressure impacts in ensemble domain: Transient and stationary statistical characteristics

The present paper focuses on the analysis of impact pressure registrations from repeated model scale sloshing experiments under harmonic rotational excitation. A series of more than 100 experiments, each one encompassing more than 100 impact events, has been conducted seeking the highest feasible repeatability. Different excitation periods, that cover the main features of the impact dynamics, have been considered in a preliminary screening, describing the main features of the impact dynamics. Since, even under a nominally deterministic excitation, the pressure at each impact is characterized by a high variability, a statistical approach is used treating the impact pressure as a stochastic process. For one selected excitation period, the statistical analysis focuses on the ensemble distribution of the maximum pressure during each impact event. Particular attention is given to the evolution of such distributions, in order to detect the variations in the statistical characteristics of the process. This is achieved by, first, identifying the presence and the length of the transient phase and, second, by characterizing the process at stationary state. The statistics of impact pressure for different peaks are discussed mostly in the ensemble domain. Linking the latter with the time domain analysis is made by checking that the problem can be considered “practically ergodic.” The “practical ergodicity” of the process is dealt with by checking to what extent steady state ensemble statistical information can be obtained from a single long run experiment. Statistical checks for correlation and independence of maximum impact pressures are also carried out to test the hypothesis of independent identically distributed random variables. The method of analysis presented in this paper through the considered example case is general in nature and is considered to be highly portable. In particular, it is considered to allow for a more thorough understanding of non-deterministic events such as those considered herein, by looking at them from a sound statistical perspective. The thorough description of the whole experimental setup makes the presented data suitable for comparison purposes and for validation of theoretical/numerical approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Parallel Fokker–Planck-DSMC algorithm for rarefied gas flow simulation in complex domains at all Knudsen numbers

A major challenge for the conventional Direct Simulation Monte Carlo (DSMC) technique lies in the fact that its computational cost becomes prohibitive in the near continuum regime, where the Knudsen number (Kn)—characterizing the degree of rarefaction—becomes small. In contrast, the Fokker–Planck (FP) based particle Monte Carlo scheme allows for computationally efficient simulations of rarefied gas flows in the low and intermediate Kn regime. The Fokker–Planck collision operator—instead of performing binary collisions employed by the DSMC method—integrates continuous stochastic processes for the phase space evolution in time. This allows for time step and grid cell sizes larger than the respective collisional scales required by DSMC. Dynamically switching between the FP and the DSMC collision operators in each computational cell is the basis of the combined FP-DSMC method, which has been proven successful in simulating flows covering the whole Kn range. Until recently, this algorithm had only been applied to two-dimensional test cases. In this contribution, we present the first general purpose implementation of the combined FP-DSMC method. Utilizing both shared- and distributed-memory parallelization, this implementation provides the capability for simulations involving many particles and complex geometries by exploiting state of the art computer cluster technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Mixed Spin (1, 5/2) Ising Ferromagnetic Blume-Capel Model Under Time-Dependent Sinusoidal Magnetic Field: an Effective-Field Theory Analysis

Non-equilibrium magnetic properties are studied in a two-dimensional mixed spin (1, 5/2) Blume-Capel Ising system under the influence sinusoidal magnetic fields using the effective-field theory based on a decoupling approximation. A dynamic equation of motion has been solved for a square lattice by utilizing a Glauber-type stochastic process. Dynamic phase diagrams are presented in the reduced magnetic field amplitude and reduced temperature plane (h,T) and reduced crystal-field and reduced temperature plane (Δ,T). We observe that the system exhibits dynamic tricritical behaviors. Phase diagrams contain the paramagnetic (p), ferrimagnetic (i), and coexistence or mixed-phase regions, namely the i,p, and i + p, which strongly depend on the crystal-field interaction parameter and oscillating magnetic field frequency. We have found that the system only exhibits a second-order transition line in the higher-frequency region. We have also compared our result with the mean-field prediction in order to indicate the effects of correlations and found that some of the dynamic first-order phase lines disappeared.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Analysis of the correlation dimension for inertial particles

We obtain an implicit equation for the correlation dimension which describes clustering of inertial particles in a complex flow onto a fractal measure. Our general equation involves a propagator of a nonlinear stochastic process in which the velocity gradient of the fluid appears as additive noise. When the long-time limit of the propagator is considered our equation reduces to an existing large-deviation formalism from which it is difficult to extract concrete results. In the short-time limit, however, our equation reduces to a solvability condition on a partial differential equation. In the case where the inertial particles are much denser than the fluid, we show how this approach leads to a perturbative expansion of the correlation dimension, for which the coefficients can be obtained exactly and in principle to any order. We derive the perturbation series for the correlation dimension of inertial particles suspended in three-dimensional spatially smooth random flows with white-noise time correlations, obtaining the first 33 non-zero coefficients exactly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

THE CORRELATED FORMATION HISTORIES OF MASSIVE GALAXIES AND THEIR DARK MATTER HALOS

Using observations in the COSMOS field, we report an intriguing correlation between the star formation activity of massive ({approx}10{sup 11.4} M{sub Sun }) central galaxies, their stellar masses, and the large-scale ({approx}10 Mpc) environments of their group-mass ({approx}10{sup 13.6} M{sub Sun }) dark matter halos. Probing the redshift range z = [0.2, 1.0], our measurements come from two independent sources: an X-ray-detected group catalog and constraints on the stellar-to-halo mass relation derived from a combination of clustering and weak lensing statistics. At z = 1, we find that the stellar mass in star-forming (SF) centrals is a factor of two less than in passive centrals at the same halo mass. This implies that the presence or lack of star formation in group-scale centrals cannot be a stochastic process. By z = 0, the offset reverses, probably as a result of the different growth rates of these objects. A similar but weaker trend is observed when dividing the sample by morphology rather than star formation. Remarkably, we find that SF centrals at z {approx} 1 live in groups that are significantly more clustered on 10 Mpc scales than similar mass groups hosting passive centrals. We discuss this signal in the context of halo assembly and recent simulations, suggesting that SF centrals prefer halos with higher angular momentum and/or formation histories with more recent growth; such halos are known to evolve in denser large-scale environments. If confirmed, this would be evidence of an early established link between the assembly history of halos on large scales and the future properties of the galaxies that form inside them.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A new Green's function Monte Carlo algorithm for the solution of the two-dimensional nonlinear Poisson–Boltzmann equation: Application to the modeling of the communication breakdown problem in space vehicles during re-entry

The objective of this paper is the exposition of a recently-developed, novel Green's function Monte Carlo (GFMC) algorithm for the solution of nonlinear partial differential equations and its application to the modeling of the plasma sheath region around a cylindrical conducting object, carrying a potential and moving at low speeds through an otherwise neutral medium. The plasma sheath is modeled in equilibrium through the GFMC solution of the nonlinear Poisson–Boltzmann (NPB) equation. The traditional Monte Carlo based approaches for the solution of nonlinear equations are iterative in nature, involving branching stochastic processes which are used to calculate linear functionals of the solution of nonlinear integral equations. Over the last several years, one of the authors of this paper, K. Chatterjee has been developing a philosophically-different approach, where the linearization of the equation of interest is not required and hence there is no need for iteration and the simulation of branching processes. Instead, an approximate expression for the Green's function is obtained using perturbation theory, which is used to formulate the random walk equations within the problem sub-domains where the random walker makes its walks. However, as a trade-off, the dimensions of these sub-domains have to be restricted by the limitations imposed by perturbation theory. The greatest advantage of this approach is the ease and simplicity of parallelization stemming from the lack of the need for iteration, as a result of which the parallelization procedure is identical to the parallelization procedure for the GFMC solution of a linear problem. The application area of interest is in the modeling of the communication breakdown problem during a space vehicle's re-entry into the atmosphere. However, additional application areas are being explored in the modeling of electromagnetic propagation through the atmosphere/ionosphere in UHF/GPS applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Lattice Monte Carlo simulation of Galilei variant anomalous diffusion

The observation of an increasing number of anomalous diffusion phenomena motivates the study to reveal the actual reason for such stochastic processes. When it is difficult to get analytical solutions or necessary to track the trajectory of particles, lattice Monte Carlo (LMC) simulation has been shown to be particularly useful. To develop such an LMC simulation algorithm for the Galilei variant anomalous diffusion, we derive explicit solutions for the conditional and unconditional first passage time (FPT) distributions with double absorbing barriers. According to the theory of random walks on lattices and the FPT distributions, we propose an LMC simulation algorithm and prove that such LMC simulation can reproduce both the mean and the mean square displacement exactly in the long-time limit. However, the error introduced in the second moment of the displacement diverges according to a power law as the simulation time progresses. We give an explicit criterion for choosing a small enough lattice step to limit the error within the specified tolerance. We further validate the LMC simulation algorithm and confirm the theoretical error analysis through numerical simulations. The numerical results agree with our theoretical predictions very well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Revisiting stochastic variability of AGNs with structure functions

Discrepancies between reported structure function (SF) slopes and their overall flatness as compared to the expectations from the damped random walk (DRW) model, which generally well describes the variability of active galactic nuclei (AGNs), have triggered us to study this problem in detail. We review common AGN variability observables and identify their most common problems. Equipped with this knowledge, we study ∼9000 r-band AGN light curves from Stripe 82 of the Sloan Digital Sky Survey, using SFs described by stochastic processes with the power exponential covariance matrix of the signal. We model the “subensemble” SFs in the redshift–absolute magnitude bins with the full SF equation (including the turnover and the noise part) and a single power law (SPL; in the “red noise regime” after subtracting the noise term). The distribution of full-equation SF (SPL) slopes peaks at γ=0.55±0.08 (0.52 ± 0.06) and is consistent with the DRW model. There is a hint of a weak correlation of γ with the luminosity and a lack of correlation with the black hole mass. The typical decorrelation timescale in the optical is τ=0.97±0.46 year. The SF amplitude at one year obtained from the SPL fitting is SF{sub 0}=0.22±0.06 mag and is overestimated because the SF is already at the turnover part, so the true value is SF{sub 0}=0.20±0.06 mag. The asymptotic variability is SF{sub ∞}=0.25±0.06 mag. It is strongly anticorrelated with both the luminosity and the Eddington ratio and is correlated with the black hole mass. The reliability of these results is fortified with Monte Carlo simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The NANOGrav nine-year data set: Noise budget for pulsar arrival times on intraday timescales

The use of pulsars as astrophysical clocks for gravitational wave (GW) experiments demands the highest possible timing precision. Pulse times of arrival (TOAs) are limited by stochastic processes that occur in the pulsar itself, along the line of sight through the interstellar medium, and in the measurement process. On timescales of seconds to hours, the TOA variance exceeds that from template-fitting errors due to additive noise. We assess contributions to the total variance from two additional effects: amplitude and phase jitter intrinsic to single pulses and changes in the interstellar impulse response from scattering. The three effects have different dependencies on time, frequency, and pulse signal-to-noise ratio. We use data on 37 pulsars from the North American Nanohertz Observatory for GWs to assess the individual contributions to the overall intraday noise budget for each pulsar. We detect jitter in 22 pulsars and estimate the average value of rms jitter in our pulsars to be ∼1% of pulse phase. We examine how jitter evolves as a function of frequency and find evidence for evolution. Finally, we compare our measurements with previous noise parameter estimates and discuss methods to improve GW detection pipelines.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

INFLUENCE OF THE GALACTIC GRAVITATIONAL FIELD ON THE POSITIONAL ACCURACY OF EXTRAGALACTIC SOURCES

We investigate the influence of random variations of the Galactic gravitational field on the apparent celestial positions of extragalactic sources. The basic statistical characteristics of a stochastic process (first-order moments, an autocorrelation function and a power spectral density) are used to describe a light ray deflection in a gravitational field of randomly moving point masses as a function of the source coordinates. We map a 2D distribution of the standard deviation of the angular shifts in positions of distant sources (including reference sources of the International Celestial Reference Frame) with respect to their true positions. For different Galactic matter distributions the standard deviation of the offset angle can reach several tens of μ as (microarcsecond) toward the Galactic center, decreasing down to 4–6 μ as at high galactic latitudes. The conditional standard deviation (“jitter”) of 2.5 μ as is reached within 10 years at high galactic latitudes and within a few months toward the inner part of the Galaxy. The photometric microlensing events are not expected to be disturbed by astrometric random variations anywhere except the inner part of the Galaxy as the Einstein–Chvolson times are typically much shorter than the jittering timescale. While a jitter of a single reference source can be up to dozens of μ as over some reasonable observational time, using a sample of reference sources would reduce the error in relative astrometry. The obtained results can be used for estimating the physical upper limits on the time-dependent accuracy of astrometric measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Multistage Stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty

The uncertainties resulting from the escalating penetration of renewable energy resources pose severe challenges to the efficient operation of modern power systems. Hydroelectricity is characterized by its flexibility, controllability, and reliability, and thus becomes one of the most ideal energy resources to hedge against such uncertainties. This paper studies the mid-term integrated generation and maintenance scheduling of a cascaded hydroelectric system (CHS) consisting of multiple cascaded reservoirs and hydroelectric units. To precisely describe the mid-term water regulation policies, the hydraulic coupling relationship and water-energy nexus of CHS are incorporated into the proposed optimization model. The uncertainties of natural water inflow and the power outputs of wind/solar energy generation are taken into consideration and captured via a stochastic process modeled by a scenario tree. A multistage stochastic optimization (MSO) approach is developed to coordinate the complementary operations of multiple energy resources, by optimizing the mid-term water resource management, generation scheduling, and maintenance scheduling of CHS. The proposed MSO model is formulated as a large-scale mixed-integer linear program that presents significant computational intractability. To address this issue, a tailored Benders decomposition algorithm is developed. Two real-world case studies are conducted to demonstrate the capability and characteristics of the proposed model and algorithm. The computational results show that the proposed MSO model can exploit the flexibility of hydroelectricity to efficiently respond to variable wind and solar power, and reserve water resources for the generation in peak months to reduce the consumption of fossil fuel. Furthermore, the proposed solution approach also exhibits promising computational efficiency when handling large-scale models.

13 HYDRO ENERGY↗
DOE OSTI2020

Probabilistic analysis of masked loads with aggregated photovoltaic production

In this paper we present a probabilistic analysis framework to estimate behind-the-meter photovoltaic generation in real time. We develop a forward model consisting of a spatiotemporal stochastic process that represents the photovoltaic generation and a stochastic differential equation with jumps that represents the demand. Here, we employ this model to disaggregate the behind-the-meter photovoltaic generation using net load and irradiance measurements.

14 SOLAR ENERGY↗
DOE OSTI2014

Unveiling the hidden structure of complex stochastic biochemical networks

Complex Markov models are widely used and powerful predictive tools to analyze stochastic biochemical processes. However, when the network of states is unknown, it is necessary to extract information from the data to partially build the network and estimate the values of the rates. The short-time behavior of the first-passage time distributions between two states in linear chains has been shown recently to behave as a power of time with an exponent equal to the number of intermediate states. For a general Markov model we derive the complete Taylor expansion of the first-passage time distribution between two arbitrary states. By combining algebraic methods and graph theory approaches it is shown that the first term of the Taylor expansion is determined by the shortest path from the initial state to the final state. When this path is unique, we prove that the coefficient of the first term can be written in terms of the product of the transition rates along the path. It is argued that the application of our results to first-return times may be used to estimate the dependence of rates on external parameters in experimentally measured time distributions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗