Search NASA⌕ Search

SEARCH · Search NASA

Results for “conditional random fields”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

One-dimensional numerical study of charged particle trajectories in turbulent electrostatic wave fields

The paper describes a numerical simulation of electron trajectories in weak random electric fields under conditions that are approximately true for Langmuir waves whose wavelength is much longer than the Debye length. Two types of trajectory calculations were made: (1) the initial particle velocity was made equal to the mean phase velocity of the waves, or (2) it was equal to 0.7419 times the mean velocity of the waves, so that the initial velocity differed substantially from all phase velocities of the wave spectrum. When the autocorrelation time is much greater than the trapping time, the particle motion can change virtually instantaneously from one of three states - high-velocity, low-velocity, or trapped state - to another. The probability of instantaneous transition from a high- or low-velocity state becomes small when the difference between the particle velocity and the mean phase velocity of the waves becomes high in comparison to the trapping velocity. Diffusive motion becomes negligible under these conditions also.

Graham, K. N.↗

Variations of characteristic time scales in rotating stratified turbulence using a large parametric numerical study

In this work, we study rotating stratified turbulence (RST) making use of numerical data stemming from a large parametric study varying the Reynolds, Froude and Rossby numbers, Re, Fr and Ro in a broad range of values. The computations are performed using periodic boundary conditions on grids of 10243 points, with no modeling of the small scales, no forcing and with large-scale random initial conditions for the velocity field only, and there are altogether 65 runs analyzed in this paper. The buoyancy Reynolds number defined as R B = ReFr 2 varies from negligible values to ≈ 105, approaching atmospheric or oceanic regimes. This preliminary analysis deals with the variation of characteristic time scales of RST with dimensionless parameters, focusing on the role played by the partition of energy between the kinetic and potential modes, as a key ingredient for modeling the dynamics of such flows. We find that neither rotation nor the ratio of the Brunt-Väisälä frequency to the inertial frequency seem to play a major role in the absence of forcing in the global dynamics of the small-scale kinetic and potential modes. Specifically, in these computations, mostly in regimes of wave turbulence, characteristic times based on the ratio of energy to dissipation of the velocity and temperature fluctuations, T V and T P , vary substantially with parameters. Their ratio γ=T V /T P follows roughly a bell-shaped curve in terms of Richardson number Ri. It reaches a plateau --on which time scales become comparable, γ≈0.6 -- when the turbulence has significantly strengthened, leading to numerous destabilization events together with a tendency towards an isotropization of the flow.

97 MATHEMATICS AND COMPUTING↗

A Bayesian model for multivariate discrete data using spatial and expert information with application to inferring building attributes

When modeling sparsely observed multivariate data, strong prior information elicited from experts can be used to bolster predictive accuracy and counteract sampling bias. Similarly, modeling autocorrelation in space can help make use of co-occurrence patterns present in many types of spatial data. To make use of both expert prior information and spatial structure, we propose a novel graphical model for a spatial Bayesian network developed specifically to address challenges in inferring the attributes of buildings from geographically sparse observational data. This model is implemented as the sum of a spatial multivariate Gaussian random field and a tabular conditional probability function in real-valued space prior to projection onto the probability simplex. This modeling form is especially suitable for the usage of prior information in the form of sets of atomic rules obtained from experts. To perform inference with missing data, we implement a Markov chain Monte Carlo scheme composed of alternating steps of Gibbs sampling of missing entries and Hamiltonian Monte Carlo for model parameters. A case study in building attribution is presented to highlight the advantages and limitations of this approach.

97 MATHEMATICS AND COMPUTING↗

Influence of visual and motion cues on manual lateral stabilization

The ability of humans to detect and control their own lateral acceleration was measured by means of a closed-loop nulling task. Wide-field moving visual cues enhanced the operator's performance in nulling self-motion, especially at lower frequencies. Even visual cues, fixed relative to the operator, resulted in performance improvement relative to self-motion nulling in the dark. Describing function (frequency response) data was obtained for random acceleration conditions consisting of the visual field fixed relative to the laboratory, fixed relative to the subject, moving at constant velocity relative to the subject, and in the dark. The describing function data was corrected for the dynamics of operator manual control strategy. The resulting frequency responses were used to develop a linear model of self-motion detection which required a lead term of 1.5 rad/s to be added to the existing model in order to match the higher sensitivity at higher frequencies.

Huang, J.-K.↗

Pitch-angle scattering of charged particles in a random magnetic field

A calculation is presented in terms of the pitch angle that determines the conditions under which a Fokker-Planck equation gives a reasonable approximation of the pitch-angle scattering of low rigidity particles to first order in a random magnetic field. The formulation shows that the correlation scale of the fluctuation of the magnetic field about its mean does not enter directly into the approximation. The calculation is carried out for transverse magnetic fluctuations for which the magnetic field magnitude is constant to the order considered.

Jokipii, J. R.↗

Wind-forced variability of the deep eastern north Pacific: Observations of seafloor pressure and abyssal currents

Data from an array of bottom pressure gauges and a string of current meters in the vicinity of 47 deg N, 139 deg W, are used to examine the deep-ocean variability forced by ocean surface wind stress curl from August 1987 to June 1988. Bottom geostrophic currents are computed from the pressure gauge array, and these correspond well to the long-period directly measured currents at 3000 m. The supratidal-period bottom pressure variations are coherent at 95% confidence with the wind stress curl in period bands of 3-4 days and 15-60 days but removed in distances of 400 and 700 km to the northwest and the southeast, respectively. A linear, two-layer hydrodynamic model is used to examine the theoretical forcing produced by random-phased surface wind fields for the conditions of the eastern north Pacific and the 15- to 60-day-period observed response is reproduced credibly. To model 3- to 15-day variations, more realistic models are required.

Niller, P. P.↗

Local structure graph models with higher-order dependence

Local structure graph models (LSGMs) describe random graphs and networks as a Markov random field (MRF)—each graph edge has a specified conditional distribution dependent on explicit neighbourhoods of other graph edges. Centered parameterizations of LSGMs allow for direct control and interpretation of parameters for large- and small-scale structures (e.g., marginal means vs. dependence). Here, we extend this parameterization to account for triples of dependent edges and illustrate the importance of centered parameterizations for incorporating covariates and interpreting parameters. Using a MRF framework, common exponential random graph models are also shown to induce conditional distributions without centered parameterizations and thereby have undesirable features. This work attempts to advance graph models through conditional model specifications with modern parameterizations, covariates and higher-order dependencies.

97 MATHEMATICS AND COMPUTING↗

Polynomial Chaos Surrogate Construction for Random Fields with Parametric Uncertainty

Engineering and applied science rely on computational experiments to rigorously study physical systems. The mathematical models used to probe these systems are highly complex, and sampling-intensive studies often require prohibitively many simulations for acceptable accuracy. Surrogate models provide a means of circumventing the high computational expense of sampling such complex models. In particular, polynomial chaos expansions (PCEs) have been successfully used for uncertainty quantification studies of deterministic models where the dominant source of uncertainty is parametric. We discuss an extension to conventional PCE surrogate modeling to enable surrogate construction for stochastic computational models that have intrinsic noise in addition to parametric uncertainty. We develop a PCE surrogate on a joint space of intrinsic and parametric uncertainty, enabled by Rosenblatt transformations, which are evaluated via kernel density estimation of the associated conditional cumulative distributions. Furthermore, we extend the construction to random field data via the Karhunen–Loève expansion. We then take advantage of closed-form solutions for computing PCE Sobol indices to perform a global sensitivity analysis of the model which quantifies the intrinsic noise contribution to the overall model output variance. Additionally, the resulting joint PCE is generative in the sense that it allows generating random realizations at any input parameter setting that are statistically approximately equivalent to realizations from the underlying stochastic model. The method is demonstrated on a chemical catalysis example model and a synthetic example controlled by a parameter that enables a switch from unimodal to bimodal response distributions.

97 MATHEMATICS AND COMPUTING↗

Augmented Gaussian random field: Theory and computation

We propose the novel augmented Gaussian random field (AGRF), which is a universal framework incorporating the data of observable and derivatives of any order. Rigorous theory is established. We prove that under certain conditions, the observable and its derivatives of any order are governed by a single Gaussian random field, which is the aforementioned AGRF. As a corollary, the statement "the derivative of a Gaussian process remains a Gaussian process" is validated, since the derivative is represented by a part of the AGRF. Moreover, a computational method corresponding to the universal AGRF framework is constructed. Both noiseless and noisy scenarios are considered. Formulas of the posterior distributions are deduced in a nice closed form. A significant advantage of our computational method is that the universal AGRF framework provides a natural way to incorporate arbitrary order derivatives and deal with missing data. We use four numerical examples to demonstrate the effectiveness of the computational method. The numerical examples are composite function, damped harmonic oscillator, Korteweg-De Vries equation, and Burgers' equation.

Mathematics↗

A Predictive Model for Survival of Escherichia coli O157:H7 and Generic E. coli in Soil Amended with Untreated Animal Manure

Abstract This study aimed at developing a predictive model that captures the influences of a variety of agricultural and environmental variables and is able to predict the concentrations of enteric bacteria in soil amended with untreated Biological Soil Amendments of Animal Origin (BSAAO) under dynamic conditions. We developed and validated a Random Forest model using data from a longitudinal field study conducted in mid‐Atlantic United States investigating the survival of Escherichia coli O157:H7 and generic E. coli in soils amended with untreated dairy manure, horse manure, or poultry litter. Amendment type, days of rain since the previous sampling day, and soil moisture content were identified as the most influential agricultural and environmental variables impacting concentrations of viable E. coli O157:H7 and generic E. coli recovered from amended soils. Our model results also indicated that E. coli O157:H7 and generic E. coli declined at similar rates in amended soils under dynamic field conditions.The Random Forest model accurately predicted changes in viable E. coli concentrations over time under different agricultural and environmental conditions. Our model also accurately characterized the variability of E. coli concentration in amended soil over time by providing upper and lower prediction bound estimates. Cross‐validation results indicated that our model can be potentially generalized to other geographic regions and incorporated into a risk assessment for evaluating the risks associated with application of untreated BSAAO. Our model can be validated for other regions and predictive performance also can be enhanced when data sets from additional geographic regions become available.

Pang, Hao↗

Multi-scale dynamics of magnetic flux tubes and inverse magnetic energy transfer

Here, we report on an analytical and numerical study of the dynamics of a three-dimensional array of identical magnetic flux tubes in the reduced-magnetohydrodynamic description of the plasma. We propose that the long-time evolution of this system is dictated by flux-tube mergers, and that such mergers are dynamically constrained by the conservation of the pertinent (ideal) invariants, viz. the magnetic potential and axial fluxes of each tube. We also propose that in the direction perpendicular to the merging plane, flux tubes evolve in a critically balanced fashion. These notions allow us to construct an analytical model for how quantities such as the magnetic energy and the energy-containing scale evolve as functions of time. Of particular importance is the conclusion that, like its two-dimensional counterpart, this system exhibits an inverse transfer of magnetic energy that terminates only at the system scale. We perform direct numerical simulations that confirm these predictions and reveal other interesting aspects of the evolution of the system. We find, for example, that the early time evolution is characterized by a sharp decay of the initial magnetic energy, which we attribute to the ubiquitous formation of current sheets. We also show that a quantitatively similar inverse transfer of magnetic energy is observed when the initial condition is a random, small-scale magnetic seed field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Detection of correlated fragments in a sequence of images by superimposed Fourier holograms

The problem of detecting correlated fragments in a sequence of images recorded by the superimposing holograms within the Fourier holography scheme with angular multiplication of a spatially modulated reference beam is considered. The approach to the solution of this problem is based on the properties of the variance of the image sum. It is shown that this problem can be solved by providing a constant distance between the signal and reference images when recording superimposed holograms and a partial mutual correlatedness of reference images. The detection efficiency is analysed from the point of view of estimated image data capacity, the degree of mutual correlation of reference images, and the hologram recording conditions. The results of a numerical experiment under the most complicated conditions (representation of images by realisations of homogeneous random fields) confirm the theoretical conclusions. (holographic memory)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Simulation of the velocity diffusion of charged particles in turbulent magnetic fields

Numerical simulation experiments have been performed in order to study the velocity diffusion of charged particles in a static turbulent magnetic field. By following orbits of particles moving in a large ensemble of random magnetic field realizations with suitably-chosen statistical properties, a pitch-angle diffusion coefficient is derived. Results are presented for a variety of particle rigidities and r.m.s. random field strengths and a power spectrum typical of conditions found in interplanetary space.

Kaiser, T. B.↗

Spatial Factors in the Integration of Speed Information

We reported that, for a 21FC task with multiple Gabor patches in each interval, thresholds for speed discrimination decreased with the number of patches, while simply increasing the area of a single patch produced no such effect. This result could be explained by multiple patches reducing spatial uncertainty. However, the fact that thresholds decrease with number even when the patches are in fixed positions argues against this explanation. We therefore performed additional experiments to explore the lack of an area effect. Three observers did a 21FC speed discrimination task with 6 Gabor patches in each interval, and were asked to pick the interval in which the gratings moved faster. The 50% contrast patches were placed on a circle at 4 deg. eccentricity, either equally spaced and maximally separated (hexagonal array), or closely-spaced, in consecutive positions (string of pearls). For the string-of-pearls condition, the grating phases were either random, or consistent with a full-field grating viewed through multiple Gaussian windows. When grating phases were random, the thresholds for the hexagonal and string-of-pearls layouts were indistinguishable. For the string-of-pearls layout, thresholds in the consistent-phase condition were higher by 15 +/- 6% than in the random-phase condition. (Thresholds increased by 57 +/- 7% in going from 6 patches to a single patch of equivalent area.). For random-phase patches, the lower thresholds for 6 patches does not depend on a specific spacing or spatial layout. Multiple, closely-spaced, consistent-phase patches that can be interpreted as a single grating, result in thresholds closer to that produced by a single patch. Together, our results suggest that object segmentation may play a role in the integration of speed information.

Verghese, P.↗

Evaluation of residual gas fraction estimation methods for cycle-to-cycle combustion variability analysis and modeling

Cycle-to-cycle combustion variability in spark-ignition engines during normal operation is mainly caused by random perturbations of the in-cylinder conditions such as the flow velocity field, homogeneity of the air-fuel distribution, spark energy discharge, and turbulence intensity of the flame front. Such perturbations translate into the variability of the energy released observed at the end of the combustion process. During normal operating conditions, the cycle-to-cycle variability (CCV) of the energy release behaves as random uncorrelated noise. However, during diluted combustion, in either the form of exhaust gas recirculation (EGR) or excess air (lean operation), the CCV tends to increase as dilution increases. Moreover, when the ignition limit is reached at high dilution levels, the combustion CCV is exacerbated by sporadic occurrences of incomplete combustion events, and the uncorrelation assumption no longer holds. The low or null energy released by partial burns and misfires has an impact on the following combustion event due to the residual gas that carries burned and unburned gases, which contributes to the deterministic coupling between engine cycles. Many residual gas fraction estimation methods, however, only address the nominal case where complete combustion occurs and combustion events are uncorrelated. Here we evaluate the efficacy of such methods on capturing the effects of partial burns and misfires on the residual gas estimate for high-EGR operation. The advantages and disadvantages of each method are discussed based on their ability to generate cycle-to-cycle estimates. Finally, a comparison between the different estimation techniques is presented based on their usefulness for control-oriented modeling.

42 ENGINEERING↗

Test particle study of minor ions in solar wind turbulence

We perform a parameter study of the temporal evolution of a test particle distribution function in MHD turbulence. The turbulent fields are calculated using a pseudo-spectral method and periodic boundary conditions on a regular grid of 180(exp 3) points, appropriate for incompressible, homogeneous and isotropic turbulence. Initially, the kinetic and the magnetic energy are equal on the average. Both, deterministic and random initial conditions are used, in the former case with zeros of the magnetic field located at grid points, in the latter case located by interpolation between grid points. The evolution of the minor ion distribution function is studied in detail as these turbulent fields evolve, developing strong current and vorticity sheets. Using the full collisionless equation of motion for the test particles, the efficiency of nonlinear interactions can be studied. The results are compared to theoretical predictions and are then discussed in connection with the observations of the dynamical properties of solar wind minor ions derived from in situ observations.

Zurbuchen, Th.↗

Acceleration of charged particles to extremely large energies by a sub-Dreicer electric field

Acceleration of a fraction of initially low-energy electrons in a cold, collisional plasma to energies orders of magnitude larger than thermal is shown to be possible with a sub-Dreicer electric field. Because such an electric field does not satisfy the runaway condition, any acceleration will be statistical. Random scattering collisions are probabilistic such that there is 63% chance that a particle collides after traveling one mean free path and a 37% chance of not colliding. If one considers only the electrons that do not collide on traversing a mean free path and also considers that the collisional mean free path scales quadratically with particle kinetic energy, one realizes that there will be a small fraction of electrons that never collide and are accelerated to increasingly high energy. Because the mean free path scales quadratically with kinetic energy, after each successfully traveled mean free path, continued acceleration becomes more likely. This model is applied to an MHD-driven plasma jet experiment at Caltech and it is shown that electrons are accelerated by an electric field associated with a fast magnetic reconnection event occurring as the jet breaks apart. This statistical acceleration model indicates that a fraction ~1.3 × 10 -7 of electrons with initial energy distributed according to a Maxwellian with T = 2 eV will be accelerated to 6 keV in the Caltech experiment and then collide to produce the observed X-ray signal. It is demonstrated that the statistical acceleration model provides a credible explanation for the production of solar energetic electrons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electromagnetic Scattering by Discrete Random Media. I: The Dispersion Equation and the Configuration-Averaged Exciting Field

We consider the scattering of a plane electromagnetic wave obliquely incident on a plane-parallel layer of discrete random medium with non-scattering boundaries. We solve the Lax integral equation for the conditional configuration-averaged exciting field coefficients by assuming a special-form solution, that is, by representing the conditional configuration-averaged exciting field coefficients as a linear combination of the coefficients corresponding to an up-going and a down-going wave. This solution representation is supposed to be valid within the whole domain occupied by the particles, even in the close proximity of the boundaries. By balancing the waves with different propagation directions and wavenumbers we derive two homogeneous systems of equations corresponding to the generalized Lorenz–Lorentz law and two inhomogeneous systems of equations corresponding to the generalized Ewald–Oseen extinction theorem. It is shown that (i) the two homogeneous systems of equations of the generalized Lorenz–Lorentz law reduce to a single homogeneous system of equations corresponding to a semi-infinite discrete random medium at normal incidence; (ii) the dispersion equation is direction and polarization independent; and (iii) the two inhomogeneous systems of equations of the generalized Ewald–Oseen extinction theorem can be reduced to two scalar equations by means of the addition theorem for vector spherical harmonics. It is also shown that the same dispersion equation can be obtained without assuming a special-form solution representation in the proximity of the boundaries.

Adrian Doicu↗