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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 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↗
DOE OSTI2017

Aggregation-fragmentation-diffusion model for trail dynamics

We investigate statistical properties of trails formed by a random process incorporating aggregation, fragmentation, and diffusion. In this stochastic process, which takes place in one spatial dimension, two neighboring trails may combine to form a larger one, and also one trail may split into two. In addition, trails move diffusively. The model is defined by two parameters which quantify the fragmentation rate and the fragment size. In the long-time limit, the system reaches a steady state, and our focus is the limiting distribution of trail weights. We find that the density of trail weight has power-law tail P(w)~w –γ for small weight w. We obtain the exponent γ analytically and find that it varies continuously with the two model parameters. In conclusion, the exponent γ can be positive or negative, so that in one range of parameters small-weight trails are abundant and in the complementary range they are rare.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Stochastic Reductions for Inertial Fluid-Structure Interactions Subject to Thermal Fluctuations

We explore the dynamics of elastic microstructures within a fluid that are subjected to thermal fluctuations. We perform analysis to obtain systematically simplified descriptions of the mechanics in the limiting regimes when (i) the coupling forces that transfer momentum between the fluid and microstructures are strong, (ii) the mass of the microstructures is small relative to the displaced mass of the fluid, and (iii) the response to stresses results in hydrodynamics that relax rapidly to a quasi-steady-state relative to the motions of the microstructure. Furthermore, we derive effective equations using a singular perturbation analysis of the backward Kolmogorov equations of the stochastic process. Our continuum mechanics description is based on the stochastic Eulerian--Lagrangian method which provides a framework for approximation of the fluid-structure interactions when subject to thermal fluctuations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

A simulation of remote sensor systems and data processing algorithms for spectral feature classification

A computational model of the deterministic and stochastic processes involved in multispectral remote sensing was designed to evaluate the performance of sensor systems and data processing algorithms for spectral feature classification. Accuracy in distinguishing between categories of surfaces or between specific types is developed as a means to compare sensor systems and data processing algorithms. The model allows studies to be made of the effects of variability of the atmosphere and of surface reflectance, as well as the effects of channel selection and sensor noise. Examples of these effects are shown.

Arduini, R. F.↗
DOE OSTI2016

The star cluster mass–galactocentric radius relation: Implications for cluster formation

Whether or not the initial star cluster mass function is established through a universal, galactocentric-distance-independent stochastic process, on the scales of individual galaxies, remains an unsolved problem. This debate has recently gained new impetus through the publication of a study that concluded that the maximum cluster mass in a given population is not solely determined by size-of-sample effects. Here, we revisit the evidence in favor and against stochastic cluster formation by examining the young (≲ a few ×10{sup 8} year old) star cluster mass–galactocentric radius relation in M33, M51, M83, and the Large Magellanic Cloud. To eliminate size-of-sample effects, we first adopt radial bin sizes containing constant numbers of clusters, which we use to quantify the radial distribution of the first- to fifth-ranked most massive clusters using ordinary least-squares fitting. We supplement this analysis with an application of quantile regression, a binless approach to rank-based regression taking an absolute-value-distance penalty. Both methods yield, within the 1σ to 3σ uncertainties, near-zero slopes in the diagnostic plane, largely irrespective of the maximum age or minimum mass imposed on our sample selection, or of the radial bin size adopted. We conclude that, at least in our four well-studied sample galaxies, star cluster formation does not necessarily require an environment-dependent cluster formation scenario, which thus supports the notion of stochastic star cluster formation as the dominant star cluster-formation process within a given galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Random walks on jammed networks: Spectral properties

Using random walk analyses we explore diffusive transport on networks obtained from contacts between isotropically compressed, monodisperse, frictionless sphere packings generated over a range of pressures in the vicinity of the jamming transition p → 0 . For conductive particles in an insulating medium, conduction is determined by the particle contact network with nodes representing particle centers and edges contacts between particles. The transition rate is not homogeneous, but is distributed inhomogeneously due to the randomness of packing and concomitant disorder of the contact network, e.g., the distribution of the coordination number. A narrow escape time scale is used to write a Markov process for random walks on the particle contact network. This stochastic process is analyzed in terms of spectral density of the random, sparse, Euclidean and real, symmetric, positive, semidefinite transition rate matrix. Findings reveal network structures derived from jammed particles have properties similar to ordered, euclidean lattices but also some unique properties that distinguish them from other structures that are in some sense more homogeneous. Specifically, the distribution of eigenvalues of the transition rate matrix follow a power law with spectral dimension 3. Yet, quantitative details of the statistics of the eigenvectors show subtle differences with homogeneous lattices and allow us to distinguish between topological and geometric sources of disorder in the network.

42 ENGINEERING↗
DOE OSTI2019

Analytic Estimation Method of Forced Oscillation Amplitude Under Stochastic Continuous Disturbances

This paper proposes an analytic method for the amplitude estimation of the forced oscillation under stochastic continuous disturbances (SCDs). There is considerable interest in the integration of intermittent renewable energy resources into a power system, which leads to the power system in an environment with SCDs. Thus, the forced oscillation issues under SCDs are of concern. In this paper, the SCDs are described as continuous-time stochastic processes, and then the systems under SCDs are modeled by stochastic differential algebraic equations. Furthermore, by employing stochastic theory, an efficient analytic method for calculating the statistics of system states during the forced oscillation is proposed. Moreover, a novel forced oscillation phenomenon, which presents system states oscillate with stationary distributions under SCDs, is clearly characterized and theoretically explained. Based on the proposed analytic method, a scheme is put forth to estimate amplitudes of system states during forced oscillation under SCDs. Finally, compared to Monte Carlo simulation, the proposed scheme has two significant advantages. First, the proposed scheme offers a fast and effective solution for engineering applications. Second, the impact mechanism of SCDs on forced oscillation in power system is clearer, by the proposed scheme.

42 ENGINEERING↗
NASA NTRS1984

Energy release in solar flares

On the basis of observations of energy release in solar flares, it is proposed that different processes may operate on four different time scales; (1) the subsecond scale of subbursts that prominently figure in mm-wave records; (2) the few-seconds scale of elementary bursts featured in hard X-ray records; (3) the few-minutes scale of the impulsive phase; and (4) the longer than tens-of-minutes scale of the gradual phase. It is proposed that the magnetic field concentration into 'magnetic knots' at the photosphere is of consequence to coronal magnetic field structure, so that magnetic fields in this region may be seen as an array of elementary flux tubes. It is further proposed that the gradual phase of energy release involves a steady process of reconnection, while the impulsive phase involves a more stochastic process of reconnection due to mode interaction.

Sturrock, P. A.↗
NASA NTRS1988

Precise orbit determination for NASA's earth observing system using GPS (Global Positioning System)

An application of a precision orbit determination technique for NASA's Earth Observing System (EOS) using the Global Positioning System (GPS) is described. This technique allows the geometric information from measurements of GPS carrier phase and P-code pseudo-range to be exploited while minimizing requirements for precision dynamical modeling. The method combines geometric and dynamic information to determine the spacecraft trajectory; the weight on the dynamic information is controlled by adjusting fictitious spacecraft accelerations in three dimensions which are treated as first order exponentially time correlated stochastic processes. By varying the time correlation and uncertainty of the stochastic accelerations, the technique can range from purely geometric to purely dynamic. Performance estimates for this technique as applied to the orbit geometry planned for the EOS platforms indicate that decimeter accuracies for EOS orbit position may be obtainable. The sensitivity of the predicted orbit uncertainties to model errors for station locations, nongravitational platform accelerations, and Earth gravity is also presented.

Williams, B. G.↗
NASA NTRS1993

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that the authors' techniques allow more accurate estimation of the global system loading, resulting in fewer object migrations than local methods. The authors' method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive load-balancing methods. Results from a preliminary analysis of another system and from simulation with a synthetic load provide some evidence of more general applicability.

LOAD CONTROL↗
NASA NTRS1993

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that our techniques allow more accurate estimation of the global system load ing, resulting in fewer object migration than local methods. Our method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive methods.

REAL TIME↗