Effects of the scatter in sunspot group tilt angles on the large-scale magnetic field at the solar surface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, J.; Cameron, R. H.; Schüssler, M., E-mail: jiejiang@nao.cas.cn

The tilt angles of sunspot groups represent the poloidal field source in Babcock-Leighton-type models of the solar dynamo and are crucial for the build-up and reversals of the polar fields in surface flux transport (SFT) simulations. The evolution of the polar field is a consequence of Hale's polarity rules, together with the tilt angle distribution which has a systematic component (Joy's law) and a random component (tilt-angle scatter). We determine the scatter using the observed tilt angle data and study the effects of this scatter on the evolution of the solar surface field using SFT simulations with flux input basedmore » upon the recorded sunspot groups. The tilt angle scatter is described in our simulations by a random component according to the observed distributions for different ranges of sunspot group size (total umbral area). By performing simulations with a number of different realizations of the scatter we study the effect of the tilt angle scatter on the global magnetic field, especially on the evolution of the axial dipole moment. The average axial dipole moment at the end of cycle 17 (a medium-amplitude cycle) from our simulations was 2.73 G. The tilt angle scatter leads to an uncertainty of 0.78 G (standard deviation). We also considered cycle 14 (a weak cycle) and cycle 19 (a strong cycle) and show that the standard deviation of the axial dipole moment is similar for all three cycles. The uncertainty mainly results from the big sunspot groups which emerge near the equator. In the framework of Babcock-Leighton dynamo models, the tilt angle scatter therefore constitutes a significant random factor in the cycle-to-cycle amplitude variability, which strongly limits the predictability of solar activity.« less

Random-field-induced disordering mechanism in a disordered ferromagnet: Between the Imry-Ma and the standard disordering mechanism

NASA Astrophysics Data System (ADS)

Andresen, Juan Carlos; Katzgraber, Helmut G.; Schechter, Moshe

2017-12-01

Random fields disorder Ising ferromagnets by aligning single spins in the direction of the random field in three space dimensions, or by flipping large ferromagnetic domains at dimensions two and below. While the former requires random fields of typical magnitude similar to the interaction strength, the latter Imry-Ma mechanism only requires infinitesimal random fields. Recently, it has been shown that for dilute anisotropic dipolar systems a third mechanism exists, where the ferromagnetic phase is disordered by finite-size glassy domains at a random field of finite magnitude that is considerably smaller than the typical interaction strength. Using large-scale Monte Carlo simulations and zero-temperature numerical approaches, we show that this mechanism applies to disordered ferromagnets with competing short-range ferromagnetic and antiferromagnetic interactions, suggesting its generality in ferromagnetic systems with competing interactions and an underlying spin-glass phase. A finite-size-scaling analysis of the magnetization distribution suggests that the transition might be first order.

Random field assessment of nanoscopic inhomogeneity of bone.

PubMed

Dong, X Neil; Luo, Qing; Sparkman, Daniel M; Millwater, Harry R; Wang, Xiaodu

2010-12-01

Bone quality is significantly correlated with the inhomogeneous distribution of material and ultrastructural properties (e.g., modulus and mineralization) of the tissue. Current techniques for quantifying inhomogeneity consist of descriptive statistics such as mean, standard deviation and coefficient of variation. However, these parameters do not describe the spatial variations of bone properties. The objective of this study was to develop a novel statistical method to characterize and quantitatively describe the spatial variation of bone properties at ultrastructural levels. To do so, a random field defined by an exponential covariance function was used to represent the spatial uncertainty of elastic modulus by delineating the correlation of the modulus at different locations in bone lamellae. The correlation length, a characteristic parameter of the covariance function, was employed to estimate the fluctuation of the elastic modulus in the random field. Using this approach, two distribution maps of the elastic modulus within bone lamellae were generated using simulation and compared with those obtained experimentally by a combination of atomic force microscopy and nanoindentation techniques. The simulation-generated maps of elastic modulus were in close agreement with the experimental ones, thus validating the random field approach in defining the inhomogeneity of elastic modulus in lamellae of bone. Indeed, generation of such random fields will facilitate multi-scale modeling of bone in more pragmatic details. Copyright © 2010 Elsevier Inc. All rights reserved.

Cosmic Rays in Intermittent Magnetic Fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shukurov, Anvar; Seta, Amit; Bushby, Paul J.

The propagation of cosmic rays in turbulent magnetic fields is a diffusive process driven by the scattering of the charged particles by random magnetic fluctuations. Such fields are usually highly intermittent, consisting of intense magnetic filaments and ribbons surrounded by weaker, unstructured fluctuations. Studies of cosmic-ray propagation have largely overlooked intermittency, instead adopting Gaussian random magnetic fields. Using test particle simulations, we calculate cosmic-ray diffusivity in intermittent, dynamo-generated magnetic fields. The results are compared with those obtained from non-intermittent magnetic fields having identical power spectra. The presence of magnetic intermittency significantly enhances cosmic-ray diffusion over a wide range of particlemore » energies. We demonstrate that the results can be interpreted in terms of a correlated random walk.« less

Phenomenological picture of fluctuations in branching random walks

NASA Astrophysics Data System (ADS)

Mueller, A. H.; Munier, S.

2014-10-01

We propose a picture of the fluctuations in branching random walks, which leads to predictions for the distribution of a random variable that characterizes the position of the bulk of the particles. We also interpret the 1 /√{t } correction to the average position of the rightmost particle of a branching random walk for large times t ≫1 , computed by Ebert and Van Saarloos, as fluctuations on top of the mean-field approximation of this process with a Brunet-Derrida cutoff at the tip that simulates discreteness. Our analytical formulas successfully compare to numerical simulations of a particular model of a branching random walk.

Speckle phase near random surfaces

NASA Astrophysics Data System (ADS)

Chen, Xiaoyi; Cheng, Chuanfu; An, Guoqiang; Han, Yujing; Rong, Zhenyu; Zhang, Li; Zhang, Meina

2018-03-01

Based on Kirchhoff approximation theory, the speckle phase near random surfaces with different roughness is numerically simulated. As expected, the properties of the speckle phase near the random surfaces are different from that in far field. In addition, as scattering distances and roughness increase, the average fluctuations of the speckle phase become larger. Unusually, the speckle phase is somewhat similar to the corresponding surface topography. We have performed experiments to verify the theoretical simulation results. Studies in this paper contribute to understanding the evolution of speckle phase near a random surface and provide a possible way to identify a random surface structure based on its speckle phase.

Comments on ``Use of conditional simulation in nuclear waste site performance assessment`` by Carol Gotway

DOE Office of Scientific and Technical Information (OSTI.GOV)

Downing, D.J.

1993-10-01

This paper discusses Carol Gotway`s paper, ``The Use of Conditional Simulation in Nuclear Waste Site Performance Assessment.`` The paper centers on the use of conditional simulation and the use of geostatistical methods to simulate an entire field of values for subsequent use in a complex computer model. The issues of sampling designs for geostatistics, semivariogram estimation and anisotropy, turning bands method for random field generation, and estimation of the comulative distribution function are brought out.

A fast random walk algorithm for computing the pulsed-gradient spin-echo signal in multiscale porous media.

PubMed

Grebenkov, Denis S

2011-02-01

A new method for computing the signal attenuation due to restricted diffusion in a linear magnetic field gradient is proposed. A fast random walk (FRW) algorithm for simulating random trajectories of diffusing spin-bearing particles is combined with gradient encoding. As random moves of a FRW are continuously adapted to local geometrical length scales, the method is efficient for simulating pulsed-gradient spin-echo experiments in hierarchical or multiscale porous media such as concrete, sandstones, sedimentary rocks and, potentially, brain or lungs. Copyright © 2010 Elsevier Inc. All rights reserved.

Automated parameterization of intermolecular pair potentials using global optimization techniques

NASA Astrophysics Data System (ADS)

Krämer, Andreas; Hülsmann, Marco; Köddermann, Thorsten; Reith, Dirk

2014-12-01

In this work, different global optimization techniques are assessed for the automated development of molecular force fields, as used in molecular dynamics and Monte Carlo simulations. The quest of finding suitable force field parameters is treated as a mathematical minimization problem. Intricate problem characteristics such as extremely costly and even abortive simulations, noisy simulation results, and especially multiple local minima naturally lead to the use of sophisticated global optimization algorithms. Five diverse algorithms (pure random search, recursive random search, CMA-ES, differential evolution, and taboo search) are compared to our own tailor-made solution named CoSMoS. CoSMoS is an automated workflow. It models the parameters' influence on the simulation observables to detect a globally optimal set of parameters. It is shown how and why this approach is superior to other algorithms. Applied to suitable test functions and simulations for phosgene, CoSMoS effectively reduces the number of required simulations and real time for the optimization task.

Towards a high-speed quantum random number generator

NASA Astrophysics Data System (ADS)

Stucki, Damien; Burri, Samuel; Charbon, Edoardo; Chunnilall, Christopher; Meneghetti, Alessio; Regazzoni, Francesco

2013-10-01

Randomness is of fundamental importance in various fields, such as cryptography, numerical simulations, or the gaming industry. Quantum physics, which is fundamentally probabilistic, is the best option for a physical random number generator. In this article, we will present the work carried out in various projects in the context of the development of a commercial and certified high speed random number generator.

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

NASA Technical Reports Server (NTRS)

Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.

1992-01-01

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

Simulation of multivariate stationary stochastic processes using dimension-reduction representation methods

NASA Astrophysics Data System (ADS)

Liu, Zhangjun; Liu, Zenghui; Peng, Yongbo

2018-03-01

In view of the Fourier-Stieltjes integral formula of multivariate stationary stochastic processes, a unified formulation accommodating spectral representation method (SRM) and proper orthogonal decomposition (POD) is deduced. By introducing random functions as constraints correlating the orthogonal random variables involved in the unified formulation, the dimension-reduction spectral representation method (DR-SRM) and the dimension-reduction proper orthogonal decomposition (DR-POD) are addressed. The proposed schemes are capable of representing the multivariate stationary stochastic process with a few elementary random variables, bypassing the challenges of high-dimensional random variables inherent in the conventional Monte Carlo methods. In order to accelerate the numerical simulation, the technique of Fast Fourier Transform (FFT) is integrated with the proposed schemes. For illustrative purposes, the simulation of horizontal wind velocity field along the deck of a large-span bridge is proceeded using the proposed methods containing 2 and 3 elementary random variables. Numerical simulation reveals the usefulness of the dimension-reduction representation methods.

Game of Life on the Equal Degree Random Lattice

NASA Astrophysics Data System (ADS)

Shao, Zhi-Gang; Chen, Tao

2010-12-01

An effective matrix method is performed to build the equal degree random (EDR) lattice, and then a cellular automaton game of life on the EDR lattice is studied by Monte Carlo (MC) simulation. The standard mean field approximation (MFA) is applied, and then the density of live cells is given ρ=0.37017 by MFA, which is consistent with the result ρ=0.37±0.003 by MC simulation.

Cosmicflows Constrained Local UniversE Simulations

NASA Astrophysics Data System (ADS)

Sorce, Jenny G.; Gottlöber, Stefan; Yepes, Gustavo; Hoffman, Yehuda; Courtois, Helene M.; Steinmetz, Matthias; Tully, R. Brent; Pomarède, Daniel; Carlesi, Edoardo

2016-01-01

This paper combines observational data sets and cosmological simulations to generate realistic numerical replicas of the nearby Universe. The latter are excellent laboratories for studies of the non-linear process of structure formation in our neighbourhood. With measurements of radial peculiar velocities in the local Universe (cosmicflows-2) and a newly developed technique, we produce Constrained Local UniversE Simulations (CLUES). To assess the quality of these constrained simulations, we compare them with random simulations as well as with local observations. The cosmic variance, defined as the mean one-sigma scatter of cell-to-cell comparison between two fields, is significantly smaller for the constrained simulations than for the random simulations. Within the inner part of the box where most of the constraints are, the scatter is smaller by a factor of 2 to 3 on a 5 h-1 Mpc scale with respect to that found for random simulations. This one-sigma scatter obtained when comparing the simulated and the observation-reconstructed velocity fields is only 104 ± 4 km s-1, I.e. the linear theory threshold. These two results demonstrate that these simulations are in agreement with each other and with the observations of our neighbourhood. For the first time, simulations constrained with observational radial peculiar velocities resemble the local Universe up to a distance of 150 h-1 Mpc on a scale of a few tens of megaparsecs. When focusing on the inner part of the box, the resemblance with our cosmic neighbourhood extends to a few megaparsecs (<5 h-1 Mpc). The simulations provide a proper large-scale environment for studies of the formation of nearby objects.

Real-time fast physical random number generator with a photonic integrated circuit.

PubMed

Ugajin, Kazusa; Terashima, Yuta; Iwakawa, Kento; Uchida, Atsushi; Harayama, Takahisa; Yoshimura, Kazuyuki; Inubushi, Masanobu

2017-03-20

Random number generators are essential for applications in information security and numerical simulations. Most optical-chaos-based random number generators produce random bit sequences by offline post-processing with large optical components. We demonstrate a real-time hardware implementation of a fast physical random number generator with a photonic integrated circuit and a field programmable gate array (FPGA) electronic board. We generate 1-Tbit random bit sequences and evaluate their statistical randomness using NIST Special Publication 800-22 and TestU01. All of the BigCrush tests in TestU01 are passed using 410-Gbit random bit sequences. A maximum real-time generation rate of 21.1 Gb/s is achieved for random bit sequences in binary format stored in a computer, which can be directly used for applications involving secret keys in cryptography and random seeds in large-scale numerical simulations.

Propagation of finite amplitude sound through turbulence: Modeling with geometrical acoustics and the parabolic approximation

NASA Astrophysics Data System (ADS)

Blanc-Benon, Philippe; Lipkens, Bart; Dallois, Laurent; Hamilton, Mark F.; Blackstock, David T.

2002-01-01

Sonic boom propagation can be affected by atmospheric turbulence. It has been shown that turbulence affects the perceived loudness of sonic booms, mainly by changing its peak pressure and rise time. The models reported here describe the nonlinear propagation of sound through turbulence. Turbulence is modeled as a set of individual realizations of a random temperature or velocity field. In the first model, linear geometrical acoustics is used to trace rays through each realization of the turbulent field. A nonlinear transport equation is then derived along each eigenray connecting the source and receiver. The transport equation is solved by a Pestorius algorithm. In the second model, the KZK equation is modified to account for the effect of a random temperature field and it is then solved numerically. Results from numerical experiments that simulate the propagation of spark-produced N waves through turbulence are presented. It is observed that turbulence decreases, on average, the peak pressure of the N waves and increases the rise time. Nonlinear distortion is less when turbulence is present than without it. The effects of random vector fields are stronger than those of random temperature fields. The location of the caustics and the deformation of the wave front are also presented. These observations confirm the results from the model experiment in which spark-produced N waves are used to simulate sonic boom propagation through a turbulent atmosphere.

Propagation of finite amplitude sound through turbulence: modeling with geometrical acoustics and the parabolic approximation.

PubMed

Blanc-Benon, Philippe; Lipkens, Bart; Dallois, Laurent; Hamilton, Mark F; Blackstock, David T

2002-01-01

Sonic boom propagation can be affected by atmospheric turbulence. It has been shown that turbulence affects the perceived loudness of sonic booms, mainly by changing its peak pressure and rise time. The models reported here describe the nonlinear propagation of sound through turbulence. Turbulence is modeled as a set of individual realizations of a random temperature or velocity field. In the first model, linear geometrical acoustics is used to trace rays through each realization of the turbulent field. A nonlinear transport equation is then derived along each eigenray connecting the source and receiver. The transport equation is solved by a Pestorius algorithm. In the second model, the KZK equation is modified to account for the effect of a random temperature field and it is then solved numerically. Results from numerical experiments that simulate the propagation of spark-produced N waves through turbulence are presented. It is observed that turbulence decreases, on average, the peak pressure of the N waves and increases the rise time. Nonlinear distortion is less when turbulence is present than without it. The effects of random vector fields are stronger than those of random temperature fields. The location of the caustics and the deformation of the wave front are also presented. These observations confirm the results from the model experiment in which spark-produced N waves are used to simulate sonic boom propagation through a turbulent atmosphere.

Parallelization of a spatial random field characterization process using the Method of Anchored Distributions and the HTCondor high throughput computing system

NASA Astrophysics Data System (ADS)

Osorio-Murillo, C. A.; Over, M. W.; Frystacky, H.; Ames, D. P.; Rubin, Y.

2013-12-01

A new software application called MAD# has been coupled with the HTCondor high throughput computing system to aid scientists and educators with the characterization of spatial random fields and enable understanding the spatial distribution of parameters used in hydrogeologic and related modeling. MAD# is an open source desktop software application used to characterize spatial random fields using direct and indirect information through Bayesian inverse modeling technique called the Method of Anchored Distributions (MAD). MAD relates indirect information with a target spatial random field via a forward simulation model. MAD# executes inverse process running the forward model multiple times to transfer information from indirect information to the target variable. MAD# uses two parallelization profiles according to computational resources available: one computer with multiple cores and multiple computers - multiple cores through HTCondor. HTCondor is a system that manages a cluster of desktop computers for submits serial or parallel jobs using scheduling policies, resources monitoring, job queuing mechanism. This poster will show how MAD# reduces the time execution of the characterization of random fields using these two parallel approaches in different case studies. A test of the approach was conducted using 1D problem with 400 cells to characterize saturated conductivity, residual water content, and shape parameters of the Mualem-van Genuchten model in four materials via the HYDRUS model. The number of simulations evaluated in the inversion was 10 million. Using the one computer approach (eight cores) were evaluated 100,000 simulations in 12 hours (10 million - 1200 hours approximately). In the evaluation on HTCondor, 32 desktop computers (132 cores) were used, with a processing time of 60 hours non-continuous in five days. HTCondor reduced the processing time for uncertainty characterization by a factor of 20 (1200 hours reduced to 60 hours.)

Dispersion Analysis Using Particle Tracking Simulations Through Heterogeneity Based on Outcrop Lidar Imagery

NASA Astrophysics Data System (ADS)

Klise, K. A.; Weissmann, G. S.; McKenna, S. A.; Tidwell, V. C.; Frechette, J. D.; Wawrzyniec, T. F.

2007-12-01

Solute plumes are believed to disperse in a non-Fickian manner due to small-scale heterogeneity and variable velocities that create preferential pathways. In order to accurately predict dispersion in naturally complex geologic media, the connection between heterogeneity and dispersion must be better understood. Since aquifer properties can not be measured at every location, it is common to simulate small-scale heterogeneity with random field generators based on a two-point covariance (e.g., through use of sequential simulation algorithms). While these random fields can produce preferential flow pathways, it is unknown how well the results simulate solute dispersion through natural heterogeneous media. To evaluate the influence that complex heterogeneity has on dispersion, we utilize high-resolution terrestrial lidar to identify and model lithofacies from outcrop for application in particle tracking solute transport simulations using RWHet. The lidar scan data are used to produce a lab (meter) scale two-dimensional model that captures 2-8 mm scale natural heterogeneity. Numerical simulations utilize various methods to populate the outcrop structure captured by the lidar-based image with reasonable hydraulic conductivity values. The particle tracking simulations result in residence time distributions used to evaluate the nature of dispersion through complex media. Particle tracking simulations through conductivity fields produced from the lidar images are then compared to particle tracking simulations through hydraulic conductivity fields produced from sequential simulation algorithms. Based on this comparison, the study aims to quantify the difference in dispersion when using realistic and simplified representations of aquifer heterogeneity. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

SYNTHETIC OBSERVATIONS OF MAGNETIC FIELDS IN PROTOSTELLAR CORES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Joyce W. Y.; Hull, Charles L. H.; Offner, Stella S. R., E-mail: chat.hull@cfa.harvard.edu, E-mail: jwyl1g12@soton.ac.uk

The role of magnetic fields in the early stages of star formation is not well constrained. In order to discriminate between different star formation models, we analyze 3D magnetohydrodynamic simulations of low-mass cores and explore the correlation between magnetic field orientation and outflow orientation over time. We produce synthetic observations of dust polarization at resolutions comparable to millimeter-wave dust polarization maps observed by the Combined Array for Research in Millimeter-wave Astronomy and compare these with 2D visualizations of projected magnetic field and column density. Cumulative distribution functions of the projected angle between the magnetic field and outflow show different degreesmore » of alignment in simulations with differing mass-to-flux ratios. The distribution function for the less magnetized core agrees with observations finding random alignment between outflow and field orientations, while the more magnetized core exhibits stronger alignment. We find that fractional polarization increases when the system is viewed such that the magnetic field is close to the plane of the sky, and the values of fractional polarization are consistent with observational measurements. The simulation outflow, which reflects the underlying angular momentum of the accreted gas, changes direction significantly over over the first ∼0.1 Myr of evolution. This movement could lead to the observed random alignment between outflows and the magnetic fields in protostellar cores.« less

Effect of alignment of easy axes on dynamic magnetization of immobilized magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Yoshida, Takashi; Matsugi, Yuki; Tsujimura, Naotaka; Sasayama, Teruyoshi; Enpuku, Keiji; Viereck, Thilo; Schilling, Meinhard; Ludwig, Frank

2017-04-01

In some biomedical applications of magnetic nanoparticles (MNPs), the particles are physically immobilized. In this study, we explore the effect of the alignment of the magnetic easy axes on the dynamic magnetization of immobilized MNPs under an AC excitation field. We prepared three immobilized MNP samples: (1) a sample in which easy axes are randomly oriented, (2) a parallel-aligned sample in which easy axes are parallel to the AC field, and (3) an orthogonally aligned sample in which easy axes are perpendicular to the AC field. First, we show that the parallel-aligned sample has the largest hysteresis in the magnetization curve and the largest harmonic magnetization spectra, followed by the randomly oriented and orthogonally aligned samples. For example, 1.6-fold increase was observed in the area of the hysteresis loop of the parallel-aligned sample compared to that of the randomly oriented sample. To quantitatively discuss the experimental results, we perform a numerical simulation based on a Fokker-Planck equation, in which probability distributions for the directions of the easy axes are taken into account in simulating the prepared MNP samples. We obtained quantitative agreement between experiment and simulation. These results indicate that the dynamic magnetization of immobilized MNPs is significantly affected by the alignment of the easy axes.

A model for characterizing residential ground current and magnetic field fluctuations.

PubMed

Mader, D L; Peralta, S B; Sherar, M D

1994-01-01

The current through the residential grounding circuit is an important source for magnetic fields; field variations near the grounding circuit accurately track fluctuations in this ground current. In this paper, a model is presented which permits calculation of the range of these fluctuations. A discrete network model is used to simulate a local distribution system for a single street, and a statistical model to simulate unbalanced currents in the system. Simulations of three-house and ten-house networks show that random appliance operation leads to ground current fluctuations which can be quite large, on the order of 600%. This is consistent with measured fluctuations in an actual house.

The ability of healthy volunteers to simulate a neurologic field defect on automated perimetry.

PubMed

Ghate, Deepta; Bodnarchuk, Brian; Sanders, Sheila; Deokule, Sunil; Kedar, Sachin

2014-03-01

To determine if volunteers can simulate and reproduce 3 types of neurologic field defects: hemianopia, quadrantanopia, and central scotoma. Cross-sectional study. Thirty healthy volunteers new to perimetry (including automated perimetry). After informed consent, volunteers were randomized to 1 of the 3 visual field defects listed above. All visual field testing was performed on the right eye using the Humphrey Field Analyzer (HFA; Carl Zeiss Meditec, Dublin, CA) SITA Fast 24-2 protocol. Each volunteer was provided with standard new patient instructions and was shown a diagram of the defect to be simulated. Two sets of visual fields were performed on the right eye with 10 minutes between tests. Three experts used the Ocular Hypertension Treatment Study reading center criteria and determined if the simulation was successful. Proportion of volunteers able to simulate the assigned visual field. All 10 volunteers (100%) successfully simulated a hemianopia on the first and second fields. All 10 volunteers (100%) simulated a quadrantanopia on the first field and 9 (90%) did so on the second field. Eight volunteers (80%) successfully simulated a central scotoma in the first field and all 10 (100%) did so on in the second field. Reliability criteria were excellent. Forty-seven fields (78%) had 0 fixation losses, 48 (80%) had 0 false-positive results, and 44 (73%) had 0 false-negative results. It is easy to simulate reproducible and reliable neurologic field defects on automated perimetry using HFA. Copyright © 2014 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Gaps between avalanches in one-dimensional random-field Ising models

NASA Astrophysics Data System (ADS)

Nampoothiri, Jishnu N.; Ramola, Kabir; Sabhapandit, Sanjib; Chakraborty, Bulbul

2017-09-01

We analyze the statistics of gaps (Δ H ) between successive avalanches in one-dimensional random-field Ising models (RFIMs) in an external field H at zero temperature. In the first part of the paper we study the nearest-neighbor ferromagnetic RFIM. We map the sequence of avalanches in this system to a nonhomogeneous Poisson process with an H -dependent rate ρ (H ) . We use this to analytically compute the distribution of gaps P (Δ H ) between avalanches as the field is increased monotonically from -∞ to +∞ . We show that P (Δ H ) tends to a constant C (R ) as Δ H →0+ , which displays a nontrivial behavior with the strength of disorder R . We verify our predictions with numerical simulations. In the second part of the paper, motivated by avalanche gap distributions in driven disordered amorphous solids, we study a long-range antiferromagnetic RFIM. This model displays a gapped behavior P (Δ H )=0 up to a system size dependent offset value Δ Hoff , and P (Δ H ) ˜(ΔH -Δ Hoff) θ as Δ H →Hoff+ . We perform numerical simulations on this model and determine θ ≈0.95 (5 ) . We also discuss mechanisms which would lead to a nonzero exponent θ for general spin models with quenched random fields.

Markov random field model-based edge-directed image interpolation.

PubMed

Li, Min; Nguyen, Truong Q

2008-07-01

This paper presents an edge-directed image interpolation algorithm. In the proposed algorithm, the edge directions are implicitly estimated with a statistical-based approach. In opposite to explicit edge directions, the local edge directions are indicated by length-16 weighting vectors. Implicitly, the weighting vectors are used to formulate geometric regularity (GR) constraint (smoothness along edges and sharpness across edges) and the GR constraint is imposed on the interpolated image through the Markov random field (MRF) model. Furthermore, under the maximum a posteriori-MRF framework, the desired interpolated image corresponds to the minimal energy state of a 2-D random field given the low-resolution image. Simulated annealing methods are used to search for the minimal energy state from the state space. To lower the computational complexity of MRF, a single-pass implementation is designed, which performs nearly as well as the iterative optimization. Simulation results show that the proposed MRF model-based edge-directed interpolation method produces edges with strong geometric regularity. Compared to traditional methods and other edge-directed interpolation methods, the proposed method improves the subjective quality of the interpolated edges while maintaining a high PSNR level.

Influence of the pulsating electric field on the ECR heating in a nonuniform magnetic field

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balmashnov, A. A., E-mail: abalmashnov@sci.pfu.edu.ru; Umnov, A. M.

2011-12-15

According to a computer simulation, the randomized pulsating electric field can strongly influence the ECR plasma heating in a nonuniform magnetic field. It has been found out that the electron energy spectrum is shifted to the high energy region. The obtained effect is intended to be used in the ECR sources for effective X-ray generation.

Field Line Random Walk in Isotropic Magnetic Turbulence up to Infinite Kubo Number

NASA Astrophysics Data System (ADS)

Sonsrettee, W.; Wongpan, P.; Ruffolo, D. J.; Matthaeus, W. H.; Chuychai, P.; Rowlands, G.

2013-12-01

In astrophysical plasmas, the magnetic field line random walk (FLRW) plays a key role in the transport of energetic particles. In the present, we consider isotropic magnetic turbulence, which is a reasonable model for interstellar space. Theoretical conceptions of the FLRW have been strongly influenced by studies of the limit of weak fluctuations (or a strong mean field) (e.g, Isichenko 1991a, b). In this case, the behavior of FLRW can be characterized by the Kubo number R = (b/B0)(l_∥ /l_ \\bot ) , where l∥ and l_ \\bot are turbulence coherence scales parallel and perpendicular to the mean field, respectively, and b is the root mean squared fluctuation field. In the 2D limit (R ≫ 1), there has been an apparent conflict between concepts of Bohm diffusion, which is based on the Corrsin's independence hypothesis, and percolative diffusion. Here we have used three non-perturbative analytic techniques based on Corrsin's independence hypothesis for B0 = 0 (R = ∞ ): diffusive decorrelation (DD), random ballistic decorrelation (RBD) and a general ordinary differential equation (ODE), and compared them with direct computer simulations. All the analytical models and computer simulations agree that isotropic turbulence for R = ∞ has a field line diffusion coefficient that is consistent with Bohm diffusion. Partially supported by the Thailand Research Fund, NASA, and NSF.

Criticality of the random field Ising model in and out of equilibrium: A nonperturbative functional renormalization group description

NASA Astrophysics Data System (ADS)

Balog, Ivan; Tarjus, Gilles; Tissier, Matthieu

2018-03-01

We show that, contrary to previous suggestions based on computer simulations or erroneous theoretical treatments, the critical points of the random-field Ising model out of equilibrium, when quasistatically changing the applied source at zero temperature, and in equilibrium are not in the same universality class below some critical dimension dD R≈5.1 . We demonstrate this by implementing a nonperturbative functional renormalization group for the associated dynamical field theory. Above dD R, the avalanches, which characterize the evolution of the system at zero temperature, become irrelevant at large distance, and hysteresis and equilibrium critical points are then controlled by the same fixed point. We explain how to use computer simulation and finite-size scaling to check the correspondence between in and out of equilibrium criticality in a far less ambiguous way than done so far.

Transport of Charged Particles in Turbulent Magnetic Fields

NASA Astrophysics Data System (ADS)

Parashar, T.; Subedi, P.; Sonsrettee, W.; Blasi, P.; Ruffolo, D. J.; Matthaeus, W. H.; Montgomery, D.; Chuychai, P.; Dmitruk, P.; Wan, M.; Chhiber, R.

2017-12-01

Magnetic fields permeate the Universe. They are found in planets, stars, galaxies, and the intergalactic medium. The magnetic field found in these astrophysical systems are usually chaotic, disordered, and turbulent. The investigation of the transport of cosmic rays in magnetic turbulence is a subject of considerable interest. One of the important aspects of cosmic ray transport is to understand their diffusive behavior and to calculate the diffusion coefficient in the presence of these turbulent fields. Research has most frequently concentrated on determining the diffusion coefficient in the presence of a mean magnetic field. Here, we will particularly focus on calculating diffusion coefficients of charged particles and magnetic field lines in a fully three-dimensional isotropic turbulent magnetic field with no mean field, which may be pertinent to many astrophysical situations. For charged particles in isotropic turbulence we identify different ranges of particle energy depending upon the ratio of the Larmor radius of the charged particle to the characteristic outer length scale of the turbulence. Different theoretical models are proposed to calculate the diffusion coefficient, each applicable to a distinct range of particle energies. The theoretical ideas are tested against results of detailed numerical experiments using Monte-Carlo simulations of particle propagation in stochastic magnetic fields. We also discuss two different methods of generating random magnetic field to study charged particle propagation using numerical simulation. One method is the usual way of generating random fields with a specified power law in wavenumber space, using Gaussian random variables. Turbulence, however, is non-Gaussian, with variability that comes in bursts called intermittency. We therefore devise a way to generate synthetic intermittent fields which have many properties of realistic turbulence. Possible applications of such synthetically generated intermittent fields are discussed.

Restoration of dimensional reduction in the random-field Ising model at five dimensions

NASA Astrophysics Data System (ADS)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D <6 to their values in the pure Ising model at D -2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Restoration of dimensional reduction in the random-field Ising model at five dimensions.

PubMed

Fytas, Nikolaos G; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D-2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D=5. We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3≤D<6 to their values in the pure Ising model at D-2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Remote Sensing, Sampling and Simulation Applications in Analyses of Insect Dispersion and Abundance in Cotton

Treesearch

J. L. Willers; J. M. McKinion; J. N. Jenkins

2006-01-01

Simulation was employed to create stratified simple random samples of different sample unit sizes to represent tarnished plant bug abundance at different densities within various habitats of simulated cotton fields. These samples were used to investigate dispersion patterns of this cotton insect. It was found that the assessment of spatial pattern varied as a function...

How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes?

PubMed

Grabska-Barwińska, Agnieszka; Latham, Peter E

2014-06-01

We use mean field techniques to compute the distribution of excitatory and inhibitory firing rates in large networks of randomly connected spiking quadratic integrate and fire neurons. These techniques are based on the assumption that activity is asynchronous and Poisson. For most parameter settings these assumptions are strongly violated; nevertheless, so long as the networks are not too synchronous, we find good agreement between mean field prediction and network simulations. Thus, much of the intuition developed for randomly connected networks in the asynchronous regime applies to mildly synchronous networks.

Random crystal field effect on the magnetic and hysteresis behaviors of a spin-1 cylindrical nanowire

NASA Astrophysics Data System (ADS)

Zaim, N.; Zaim, A.; Kerouad, M.

2017-02-01

In this work, the magnetic behavior of the cylindrical nanowire, consisting of a ferromagnetic core of spin-1 atoms surrounded by a ferromagnetic shell of spin-1 atoms is studied in the presence of a random crystal field interaction. Based on Metropolis algorithm, the Monte Carlo simulation has been used to investigate the effects of the concentration of the random crystal field p, the crystal field D and the shell exchange interaction Js on the phase diagrams and the hysteresis behavior of the system. Some characteristic behaviors have been found, such as the first and second-order phase transitions joined by tricritical point for appropriate values of the system parameters, triple and isolated critical points can be also found. Depending on the Hamiltonian parameters, single, double and para hysteresis regions are explicitly determined.

3D vector distribution of the electro-magnetic fields on a random gold film

NASA Astrophysics Data System (ADS)

Canneson, Damien; Berini, Bruno; Buil, Stéphanie; Hermier, Jean-Pierre; Quélin, Xavier

2018-05-01

The 3D vector distribution of the electro-magnetic fields at the very close vicinity of the surface of a random gold film is studied. Such films are well known for their properties of light confinement and large fluctuations of local density of optical states. Using Finite-Difference Time-Domain simulations, we show that it is possible to determine the local orientation of the electro-magnetic fields. This allows us to obtain a complete characterization of the fields. Large fluctuations of their amplitude are observed as previously shown. Here, we demonstrate large variations of their direction depending both on the position on the random gold film, and on the distance to it. Such characterization could be useful for a better understanding of applications like the coupling of point-like dipoles to such films.

Scattering Models and Basic Experiments in the Microwave Regime

NASA Technical Reports Server (NTRS)

Fung, A. K.; Blanchard, A. J. (Principal Investigator)

1985-01-01

The objectives of research over the next three years are: (1) to develop a randomly rough surface scattering model which is applicable over the entire frequency band; (2) to develop a computer simulation method and algorithm to simulate scattering from known randomly rough surfaces, Z(x,y); (3) to design and perform laboratory experiments to study geometric and physical target parameters of an inhomogeneous layer; (4) to develop scattering models for an inhomogeneous layer which accounts for near field interaction and multiple scattering in both the coherent and the incoherent scattering components; and (5) a comparison between theoretical models and measurements or numerical simulation.

Sample Size Estimation in Cluster Randomized Educational Trials: An Empirical Bayes Approach

ERIC Educational Resources Information Center

Rotondi, Michael A.; Donner, Allan

2009-01-01

The educational field has now accumulated an extensive literature reporting on values of the intraclass correlation coefficient, a parameter essential to determining the required size of a planned cluster randomized trial. We propose here a simple simulation-based approach including all relevant information that can facilitate this task. An…

Microseismic response characteristics modeling and locating of underground water supply pipe leak

NASA Astrophysics Data System (ADS)

Wang, J.; Liu, J.

2015-12-01

In traditional methods of pipeline leak location, geophones must be located on the pipe wall. If the exact location of the pipeline is unknown, the leaks cannot be identified accurately. To solve this problem, taking into account the characteristics of the pipeline leak, we propose a continuous random seismic source model and construct geological models to investigate the proposed method for locating underground pipeline leaks. Based on two dimensional (2D) viscoacoustic equations and the staggered grid finite-difference (FD) algorithm, the microseismic wave field generated by a leaking pipe is modeled. Cross-correlation analysis and the simulated annealing (SA) algorithm were utilized to obtain the time difference and the leak location. We also analyze and discuss the effect of the number of recorded traces, the survey layout, and the offset and interval of the traces on the accuracy of the estimated location. The preliminary results of the simulation and data field experiment indicate that (1) a continuous random source can realistically represent the leak microseismic wave field in a simulation using 2D visco-acoustic equations and a staggered grid FD algorithm. (2) The cross-correlation method is effective for calculating the time difference of the direct wave relative to the reference trace. However, outside the refraction blind zone, the accuracy of the time difference is reduced by the effects of the refracted wave. (3) The acquisition method of time difference based on the microseismic theory and SA algorithm has a great potential for locating leaks from underground pipelines from an array located on the ground surface. Keywords: Viscoacoustic finite-difference simulation; continuous random source; simulated annealing algorithm; pipeline leak location

Simulated near-field mapping of ripple pattern supported metal nanoparticles arrays for SERS optimization

NASA Astrophysics Data System (ADS)

Arya, Mahima; Bhatnagar, Mukul; Ranjan, Mukesh; Mukherjee, Subroto; Nath, Rabinder; Mitra, Anirban

2017-11-01

An analytical model has been developed using a modified Yamaguchi model along with the wavelength dependent plasmon line-width correction. The model has been used to calculate the near-field response of random nanoparticles on the plane surface, elongated and spherical silver nanoparticle arrays supported on ion beam produced ripple patterned templates. The calculated near-field mapping for elongated nanoparticles arrays on the ripple patterned surface shows maximum number of hot-spots with a higher near-field enhancement (NFE) as compared to the spherical nanoparticle arrays and randomly distributed nanoparticles on the plane surface. The results from the simulations show a similar trend for the NFE when compared to the far field reflection spectra. The nature of the wavelength dependent NFE is also found to be in agreement with the observed experimental results from surface enhanced Raman spectroscopy (SERS). The calculated and the measured optical response unambiguously reveal the importance of interparticle gap and ordering, where a high intensity Raman signal is obtained for ordered elongated nanoparticles arrays case as against non-ordered and the aligned configuration of spherical nanoparticles on the rippled surface.

Random number generators for large-scale parallel Monte Carlo simulations on FPGA

NASA Astrophysics Data System (ADS)

Lin, Y.; Wang, F.; Liu, B.

2018-05-01

Through parallelization, field programmable gate array (FPGA) can achieve unprecedented speeds in large-scale parallel Monte Carlo (LPMC) simulations. FPGA presents both new constraints and new opportunities for the implementations of random number generators (RNGs), which are key elements of any Monte Carlo (MC) simulation system. Using empirical and application based tests, this study evaluates all of the four RNGs used in previous FPGA based MC studies and newly proposed FPGA implementations for two well-known high-quality RNGs that are suitable for LPMC studies on FPGA. One of the newly proposed FPGA implementations: a parallel version of additive lagged Fibonacci generator (Parallel ALFG) is found to be the best among the evaluated RNGs in fulfilling the needs of LPMC simulations on FPGA.

Cavity master equation for the continuous time dynamics of discrete-spin models.

PubMed

Aurell, E; Del Ferraro, G; Domínguez, E; Mulet, R

2017-05-01

We present an alternate method to close the master equation representing the continuous time dynamics of interacting Ising spins. The method makes use of the theory of random point processes to derive a master equation for local conditional probabilities. We analytically test our solution studying two known cases, the dynamics of the mean-field ferromagnet and the dynamics of the one-dimensional Ising system. We present numerical results comparing our predictions with Monte Carlo simulations in three different models on random graphs with finite connectivity: the Ising ferromagnet, the random field Ising model, and the Viana-Bray spin-glass model.

Cavity master equation for the continuous time dynamics of discrete-spin models

NASA Astrophysics Data System (ADS)

Aurell, E.; Del Ferraro, G.; Domínguez, E.; Mulet, R.

2017-05-01

We present an alternate method to close the master equation representing the continuous time dynamics of interacting Ising spins. The method makes use of the theory of random point processes to derive a master equation for local conditional probabilities. We analytically test our solution studying two known cases, the dynamics of the mean-field ferromagnet and the dynamics of the one-dimensional Ising system. We present numerical results comparing our predictions with Monte Carlo simulations in three different models on random graphs with finite connectivity: the Ising ferromagnet, the random field Ising model, and the Viana-Bray spin-glass model.

Direct Simulation of Extinction in a Slab of Spherical Particles

NASA Technical Reports Server (NTRS)

Mackowski, D.W.; Mishchenko, Michael I.

2013-01-01

The exact multiple sphere superposition method is used to calculate the coherent and incoherent contributions to the ensemble-averaged electric field amplitude and Poynting vector in systems of randomly positioned nonabsorbing spherical particles. The target systems consist of cylindrical volumes, with radius several times larger than length, containing spheres with positional configurations generated by a Monte Carlo sampling method. Spatially dependent values for coherent electric field amplitude, coherent energy flux, and diffuse energy flux, are calculated by averaging of exact local field and flux values over multiple configurations and over spatially independent directions for fixed target geometry, sphere properties, and sphere volume fraction. Our results reveal exponential attenuation of the coherent field and the coherent energy flux inside the particulate layer and thereby further corroborate the general methodology of the microphysical radiative transfer theory. An effective medium model based on plane wave transmission and reflection by a plane layer is used to model the dependence of the coherent electric field on particle packing density. The effective attenuation coefficient of the random medium, computed from the direct simulations, is found to agree closely with effective medium theories and with measurements. In addition, the simulation results reveal the presence of a counter-propagating component to the coherent field, which arises due to the internal reflection of the main coherent field component by the target boundary. The characteristics of the diffuse flux are compared to, and found to be consistent with, a model based on the diffusion approximation of the radiative transfer theory.

Geostatistical Sampling Methods for Efficient Uncertainty Analysis in Flow and Transport Problems

NASA Astrophysics Data System (ADS)

Liodakis, Stylianos; Kyriakidis, Phaedon; Gaganis, Petros

2015-04-01

In hydrogeological applications involving flow and transport of in heterogeneous porous media the spatial distribution of hydraulic conductivity is often parameterized in terms of a lognormal random field based on a histogram and variogram model inferred from data and/or synthesized from relevant knowledge. Realizations of simulated conductivity fields are then generated using geostatistical simulation involving simple random (SR) sampling and are subsequently used as inputs to physically-based simulators of flow and transport in a Monte Carlo framework for evaluating the uncertainty in the spatial distribution of solute concentration due to the uncertainty in the spatial distribution of hydraulic con- ductivity [1]. Realistic uncertainty analysis, however, calls for a large number of simulated concentration fields; hence, can become expensive in terms of both time and computer re- sources. A more efficient alternative to SR sampling is Latin hypercube (LH) sampling, a special case of stratified random sampling, which yields a more representative distribution of simulated attribute values with fewer realizations [2]. Here, term representative implies realizations spanning efficiently the range of possible conductivity values corresponding to the lognormal random field. In this work we investigate the efficiency of alternative methods to classical LH sampling within the context of simulation of flow and transport in a heterogeneous porous medium. More precisely, we consider the stratified likelihood (SL) sampling method of [3], in which attribute realizations are generated using the polar simulation method by exploring the geometrical properties of the multivariate Gaussian distribution function. In addition, we propose a more efficient version of the above method, here termed minimum energy (ME) sampling, whereby a set of N representative conductivity realizations at M locations is constructed by: (i) generating a representative set of N points distributed on the surface of a M-dimensional, unit radius hyper-sphere, (ii) relocating the N points on a representative set of N hyper-spheres of different radii, and (iii) transforming the coordinates of those points to lie on N different hyper-ellipsoids spanning the multivariate Gaussian distribution. The above method is applied in a dimensionality reduction context by defining flow-controlling points over which representative sampling of hydraulic conductivity is performed, thus also accounting for the sensitivity of the flow and transport model to the input hydraulic conductivity field. The performance of the various stratified sampling methods, LH, SL, and ME, is compared to that of SR sampling in terms of reproduction of ensemble statistics of hydraulic conductivity and solute concentration for different sample sizes N (numbers of realizations). The results indicate that ME sampling constitutes an equally if not more efficient simulation method than LH and SL sampling, as it can reproduce to a similar extent statistics of the conductivity and concentration fields, yet with smaller sampling variability than SR sampling. References [1] Gutjahr A.L. and Bras R.L. Spatial variability in subsurface flow and transport: A review. Reliability Engineering & System Safety, 42, 293-316, (1993). [2] Helton J.C. and Davis F.J. Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering & System Safety, 81, 23-69, (2003). [3] Switzer P. Multiple simulation of spatial fields. In: Heuvelink G, Lemmens M (eds) Proceedings of the 4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Coronet Books Inc., pp 629?635 (2000).

Analysis of speckle and material properties in laider tracer

NASA Astrophysics Data System (ADS)

Ross, Jacob W.; Rigling, Brian D.; Watson, Edward A.

2017-04-01

The SAL simulation tool Laider Tracer models speckle: the random variation in intensity of an incident light beam across a rough surface. Within Laider Tracer, the speckle field is modeled as a 2-D array of jointly Gaussian random variables projected via ray tracing onto the scene of interest. Originally, all materials in Laider Tracer were treated as ideal diffuse scatterers, for which the far-field return computed uses the Lambertian Bidirectional Reflectance Distribution Function (BRDF). As presented here, we implement material properties into Laider Tracer via the Non-conventional Exploitation Factors Data System: a database of properties for thousands of different materials sampled at various wavelengths and incident angles. We verify the intensity behavior as a function of incident angle after material properties are added to the simulation.

Statistical simulations of the dust foreground to cosmic microwave background polarization

NASA Astrophysics Data System (ADS)

Vansyngel, F.; Boulanger, F.; Ghosh, T.; Wandelt, B.; Aumont, J.; Bracco, A.; Levrier, F.; Martin, P. G.; Montier, L.

2017-07-01

The characterization of the dust polarization foreground to the cosmic microwave background (CMB) is a necessary step toward the detection of the B-mode signal associated with primordial gravitational waves. We present a method to simulate maps of polarized dust emission on the sphere that is similar to the approach used for CMB anisotropies. This method builds on the understanding of Galactic polarization stemming from the analysis of Planck data. It relates the dust polarization sky to the structure of the Galactic magnetic field and its coupling with interstellar matter and turbulence. The Galactic magnetic field is modeled as a superposition of a mean uniform field and a Gaussian random (turbulent) component with a power-law power spectrum of exponent αM. The integration along the line of sight carried out to compute Stokes maps is approximated by a sum over a small number of emitting layers with different realizations of the random component of the magnetic field. The model parameters are constrained to fit the power spectra of dust polarization EE, BB, and TE measured using Planck data. We find that the slopes of the E and B power spectra of dust polarization are matched for αM = -2.5, an exponent close to that measured for total dust intensity but larger than the Kolmogorov exponent - 11/3. The model allows us to compute multiple realizations of the Stokes Q and U maps for different realizations of the random component of the magnetic field, and to quantify the variance of dust polarization spectra for any given sky area outside of the Galactic plane. The simulations reproduce the scaling relation between the dust polarization power and the mean total dust intensity including the observed dispersion around the mean relation. We also propose a method to carry out multifrequency simulations, including the decorrelation measured recently by Planck, using a given covariance matrix of the polarization maps. These simulations are well suited to optimize component separation methods and to quantify the confidence with which the dust and CMB B-modes can be separated in present and future experiments. We also provide an astrophysical perspective on our phenomenological modeling of the dust polarization spectra.

Random function representation of stationary stochastic vector processes for probability density evolution analysis of wind-induced structures

NASA Astrophysics Data System (ADS)

Liu, Zhangjun; Liu, Zenghui

2018-06-01

This paper develops a hybrid approach of spectral representation and random function for simulating stationary stochastic vector processes. In the proposed approach, the high-dimensional random variables, included in the original spectral representation (OSR) formula, could be effectively reduced to only two elementary random variables by introducing the random functions that serve as random constraints. Based on this, a satisfactory simulation accuracy can be guaranteed by selecting a small representative point set of the elementary random variables. The probability information of the stochastic excitations can be fully emerged through just several hundred of sample functions generated by the proposed approach. Therefore, combined with the probability density evolution method (PDEM), it could be able to implement dynamic response analysis and reliability assessment of engineering structures. For illustrative purposes, a stochastic turbulence wind velocity field acting on a frame-shear-wall structure is simulated by constructing three types of random functions to demonstrate the accuracy and efficiency of the proposed approach. Careful and in-depth studies concerning the probability density evolution analysis of the wind-induced structure have been conducted so as to better illustrate the application prospects of the proposed approach. Numerical examples also show that the proposed approach possesses a good robustness.

Epidemic spreading in weighted networks: an edge-based mean-field solution.

PubMed

Yang, Zimo; Zhou, Tao

2012-05-01

Weight distribution greatly impacts the epidemic spreading taking place on top of networks. This paper presents a study of a susceptible-infected-susceptible model on regular random networks with different kinds of weight distributions. Simulation results show that the more homogeneous weight distribution leads to higher epidemic prevalence, which, unfortunately, could not be captured by the traditional mean-field approximation. This paper gives an edge-based mean-field solution for general weight distribution, which can quantitatively reproduce the simulation results. This method could be applied to characterize the nonequilibrium steady states of dynamical processes on weighted networks.

It's a Girl! Random Numbers, Simulations, and the Law of Large Numbers

ERIC Educational Resources Information Center

Goodwin, Chris; Ortiz, Enrique

2015-01-01

Modeling using mathematics and making inferences about mathematical situations are becoming more prevalent in most fields of study. Descriptive statistics cannot be used to generalize about a population or make predictions of what can occur. Instead, inference must be used. Simulation and sampling are essential in building a foundation for…

Morphologies of Primary Silicon in Hypereutectic Al-Si Alloys: Phase-Field Simulation Supported by Key Experiments

NASA Astrophysics Data System (ADS)

Wang, Kai; Wei, Ming; Zhang, Lijun; Du, Yong

2016-04-01

We realized a three-dimensional visualization of the morphology evolution and the growth behavior of the octahedral primary silicon in hypereutectic Al-20wtpctSi alloy during solidification in a real length scale by utilizing the phase-field simulation coupled with CALPHAD databases, and supported by key experiments. Moreover, through two-dimensional cut of the octahedral primary silicon at random angles, different morphologies observed in experiments, including triangle, square, trapezoid, rhombic, pentagon, and hexagon, were well reproduced.

Stochastic Resonance and Safe Basin of Single-Walled Carbon Nanotubes with Strongly Nonlinear Stiffness under Random Magnetic Field.

PubMed

Xu, Jia; Li, Chao; Li, Yiran; Lim, Chee Wah; Zhu, Zhiwen

2018-05-04

In this paper, a kind of single-walled carbon nanotube nonlinear model is developed and the strongly nonlinear dynamic characteristics of such carbon nanotubes subjected to random magnetic field are studied. The nonlocal effect of the microstructure is considered based on Eringen’s differential constitutive model. The natural frequency of the strongly nonlinear dynamic system is obtained by the energy function method, the drift coefficient and the diffusion coefficient are verified. The stationary probability density function of the system dynamic response is given and the fractal boundary of the safe basin is provided. Theoretical analysis and numerical simulation show that stochastic resonance occurs when varying the random magnetic field intensity. The boundary of safe basin has fractal characteristics and the area of safe basin decreases when the intensity of the magnetic field permeability increases.

Driving a Superconductor to Insulator Transition with Random Gauge Fields.

PubMed

Nguyen, H Q; Hollen, S M; Shainline, J; Xu, J M; Valles, J M

2016-11-30

Typically the disorder that alters the interference of particle waves to produce Anderson localization is potential scattering from randomly placed impurities. Here we show that disorder in the form of random gauge fields that act directly on particle phases can also drive localization. We present evidence of a superfluid bose glass to insulator transition at a critical level of this gauge field disorder in a nano-patterned array of amorphous Bi islands. This transition shows signs of metallic transport near the critical point characterized by a resistance , indicative of a quantum phase transition. The critical disorder depends on interisland coupling in agreement with recent Quantum Monte Carlo simulations. We discuss how this disorder tuned SIT differs from the common frustration tuned SIT that also occurs in magnetic fields. Its discovery enables new high fidelity comparisons between theoretical and experimental studies of disorder effects on quantum critical systems.

Analysis And Validation of the Field Coupled Through an Aperture in an Avionics Enclosure

NASA Astrophysics Data System (ADS)

Bakore, Rahul

This work focused on accurately predicting the current response of an equipment under test (EUT) to a random electromagnetic field representing a threat source to model radio frequency directed energy weapons (RFDEWs). The modeled EUT consists of a single wire attached to the interior wall of a shielding enclosure that includes an aperture on one face. An in-house computational electromagnetic (CEM) code based on method of moments (MOM) and accelerated by the multi-level fast multipole algorithm (MLFMA), was enhanced through the implementation of first order vector basis functions that approximates the EUT surface current. The electric field integral equation (EFIE) is solved using MOM/MLFMA. Use of first-order basis functions gives a large savings in computational time over the previous implementation with zero-order Rao-Wilton-Glisson basis functions. A sample EUT was fabricated and tested within an anechoic chamber and a reverberation chamber over a wide frequency band. In the anechoic chamber measurements, the current response on the wire within the EUT due to a single uniform plane wave was found and compared with the numerical simulations. In the reverberation chamber measurements, the mean current magnitude excited on the wire within the EUT by a mechanically stirred random field was measured and compared with the numerical simulations. The measured scattering parameter between the source antenna and the EUT measurement port was used to derive the current response on the wire in both chambers. The numerically simulated currents agree very well with the measurements in both the anechoic and reverberation chambers over the measured frequency band, confirming the validity of the numerical approach for calculating EUT response due to a random field. An artificial neural network (ANN) was trained that can rapidly provide the mean induced current response of an EUT due to a random field under different aperture configurations arbitrarily placed on one face of an EUT. However, ANN proved no better than simple linear interpolation in approximating the induced currents on EUTs that give strong resonances and nulls in the response.

Simulating Pre-Asymptotic, Non-Fickian Transport Although Doing Simple Random Walks - Supported By Empirical Pore-Scale Velocity Distributions and Memory Effects

NASA Astrophysics Data System (ADS)

Most, S.; Jia, N.; Bijeljic, B.; Nowak, W.

2016-12-01

Pre-asymptotic characteristics are almost ubiquitous when analyzing solute transport processes in porous media. These pre-asymptotic aspects are caused by spatial coherence in the velocity field and by its heterogeneity. For the Lagrangian perspective of particle displacements, the causes of pre-asymptotic, non-Fickian transport are skewed velocity distribution, statistical dependencies between subsequent increments of particle positions (memory) and dependence between the x, y and z-components of particle increments. Valid simulation frameworks should account for these factors. We propose a particle tracking random walk (PTRW) simulation technique that can use empirical pore-space velocity distributions as input, enforces memory between subsequent random walk steps, and considers cross dependence. Thus, it is able to simulate pre-asymptotic non-Fickian transport phenomena. Our PTRW framework contains an advection/dispersion term plus a diffusion term. The advection/dispersion term produces time-series of particle increments from the velocity CDFs. These time series are equipped with memory by enforcing that the CDF values of subsequent velocities change only slightly. The latter is achieved through a random walk on the axis of CDF values between 0 and 1. The virtual diffusion coefficient for that random walk is our only fitting parameter. Cross-dependence can be enforced by constraining the random walk to certain combinations of CDF values between the three velocity components in x, y and z. We will show that this modelling framework is capable of simulating non-Fickian transport by comparison with a pore-scale transport simulation and we analyze the approach to asymptotic behavior.

Effect of randomness on multi-frequency aeroelastic responses resolved by Unsteady Adaptive Stochastic Finite Elements

NASA Astrophysics Data System (ADS)

Witteveen, Jeroen A. S.; Bijl, Hester

2009-10-01

The Unsteady Adaptive Stochastic Finite Elements (UASFE) method resolves the effect of randomness in numerical simulations of single-mode aeroelastic responses with a constant accuracy in time for a constant number of samples. In this paper, the UASFE framework is extended to multi-frequency responses and continuous structures by employing a wavelet decomposition pre-processing step to decompose the sampled multi-frequency signals into single-frequency components. The effect of the randomness on the multi-frequency response is then obtained by summing the results of the UASFE interpolation at constant phase for the different frequency components. Results for multi-frequency responses and continuous structures show a three orders of magnitude reduction of computational costs compared to crude Monte Carlo simulations in a harmonically forced oscillator, a flutter panel problem, and the three-dimensional transonic AGARD 445.6 wing aeroelastic benchmark subject to random fields and random parameters with various probability distributions.

Discriminative Random Field Models for Subsurface Contamination Uncertainty Quantification

NASA Astrophysics Data System (ADS)

Arshadi, M.; Abriola, L. M.; Miller, E. L.; De Paolis Kaluza, C.

2017-12-01

Application of flow and transport simulators for prediction of the release, entrapment, and persistence of dense non-aqueous phase liquids (DNAPLs) and associated contaminant plumes is a computationally intensive process that requires specification of a large number of material properties and hydrologic/chemical parameters. Given its computational burden, this direct simulation approach is particularly ill-suited for quantifying both the expected performance and uncertainty associated with candidate remediation strategies under real field conditions. Prediction uncertainties primarily arise from limited information about contaminant mass distributions, as well as the spatial distribution of subsurface hydrologic properties. Application of direct simulation to quantify uncertainty would, thus, typically require simulating multiphase flow and transport for a large number of permeability and release scenarios to collect statistics associated with remedial effectiveness, a computationally prohibitive process. The primary objective of this work is to develop and demonstrate a methodology that employs measured field data to produce equi-probable stochastic representations of a subsurface source zone that capture the spatial distribution and uncertainty associated with key features that control remediation performance (i.e., permeability and contamination mass). Here we employ probabilistic models known as discriminative random fields (DRFs) to synthesize stochastic realizations of initial mass distributions consistent with known, and typically limited, site characterization data. Using a limited number of full scale simulations as training data, a statistical model is developed for predicting the distribution of contaminant mass (e.g., DNAPL saturation and aqueous concentration) across a heterogeneous domain. Monte-Carlo sampling methods are then employed, in conjunction with the trained statistical model, to generate realizations conditioned on measured borehole data. Performance of the statistical model is illustrated through comparisons of generated realizations with the `true' numerical simulations. Finally, we demonstrate how these realizations can be used to determine statistically optimal locations for further interrogation of the subsurface.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, Jin AU

1987-01-01

Earth terrain covers were modeled as random media characterized by different dielectric constants and correlation functions. In order to model sea ice with brine inclusions and vegetation with row structures, the random medium is assumed to be anisotropic. A three layer model is used to simulate a vegetation field or a snow covered ice field with the top layer being snow or leaves, the middle layer being ice or trunks, and the bottom layer being sea water or ground. The strong fluctuation theory with the distorted Born approximation is applied to the solution of the radar backscattering coefficients.

Structure of supersonic jet flow and its radiated sound

NASA Technical Reports Server (NTRS)

Mankbadi, Reda R.; Hayer, M. Ehtesham; Povinelli, Louis A.

1994-01-01

The present paper explores the use of large-eddy simulations as a tool for predicting noise from first principles. A high-order numerical scheme is used to perform large-eddy simulations of a supersonic jet flow with emphasis on capturing the time-dependent flow structure representating the sound source. The wavelike nature of this structure under random inflow disturbances is demonstrated. This wavelike structure is then enhanced by taking the inflow disturbances to be purely harmonic. Application of Lighthill's theory to calculate the far-field noise, with the sound source obtained from the calculated time-dependent near field, is demonstrated. Alternative approaches to coupling the near-field sound source to the far-field sound are discussed.

Statistical simulation of ensembles of precipitation fields for data assimilation applications

NASA Astrophysics Data System (ADS)

Haese, Barbara; Hörning, Sebastian; Chwala, Christian; Bárdossy, András; Schalge, Bernd; Kunstmann, Harald

2017-04-01

The simulation of the hydrological cycle by models is an indispensable tool for a variety of environmental challenges such as climate prediction, water resources management, or flood forecasting. One of the crucial variables within the hydrological system, and accordingly one of the main drivers for terrestrial hydrological processes, is precipitation. A correct reproduction of the spatio-temporal distribution of precipitation is crucial for the quality and performance of hydrological applications. In our approach we stochastically generate precipitation fields conditioned on various precipitation observations. Rain gauges provide high-quality information for a specific measurement point, but their spatial representativeness is often rare. Microwave links, e. g. from commercial cellular operators, on the other hand can be used to estimate line integrals of near-surface rainfall information. They provide a very dense observational system compared to rain gauges. A further prevalent source of precipitation information are weather radars, which provide rainfall pattern informations. In our approach we derive precipitation fields, which are conditioned on combinations of these different observation types. As method to generate precipitation fields we use the random mixing method. Following this method a precipitation field is received as a linear combination of unconditional spatial random fields, where the spatial dependence structure is described by copulas. The weights of the linear combination are chosen in the way that the observations and the spatial structure of precipitation are reproduced. One main advantage of the random mixing method is the opportunity to consider linear and non-linear constraints. For a demonstration of the method we use virtual observations generated from a virtual reality of the Neckar catchment. These virtual observations mimic advantages and disadvantages of real observations. This virtual data set allows us to evaluate simulated precipitation fields in a very detailed manner as well as to quantify uncertainties which are conveyed by measurement inaccuracies. In a further step we use real observations as a basis for the generation of precipitation fields. The resulting ensembles of precipitation fields are used for example for data assimilation applications or as input data for hydrological models.

Quantum simulation of an ultrathin body field-effect transistor with channel imperfections

NASA Astrophysics Data System (ADS)

Vyurkov, V.; Semenikhin, I.; Filippov, S.; Orlikovsky, A.

2012-04-01

An efficient program for the all-quantum simulation of nanometer field-effect transistors is elaborated. The model is based on the Landauer-Buttiker approach. Our calculation of transmission coefficients employs a transfer-matrix technique involving the arbitrary precision (multiprecision) arithmetic to cope with evanescent modes. Modified in such way, the transfer-matrix technique turns out to be much faster in practical simulations than that of scattering-matrix. Results of the simulation demonstrate the impact of realistic channel imperfections (random charged centers and wall roughness) on transistor characteristics. The Landauer-Buttiker approach is developed to incorporate calculation of the noise at an arbitrary temperature. We also validate the ballistic Landauer-Buttiker approach for the usual situation when heavily doped contacts are indispensably included into the simulation region.

Sampling Strategies for Evaluating the Rate of Adventitious Transgene Presence in Non-Genetically Modified Crop Fields.

PubMed

Makowski, David; Bancal, Rémi; Bensadoun, Arnaud; Monod, Hervé; Messéan, Antoine

2017-09-01

According to E.U. regulations, the maximum allowable rate of adventitious transgene presence in non-genetically modified (GM) crops is 0.9%. We compared four sampling methods for the detection of transgenic material in agricultural non-GM maize fields: random sampling, stratified sampling, random sampling + ratio reweighting, random sampling + regression reweighting. Random sampling involves simply sampling maize grains from different locations selected at random from the field concerned. The stratified and reweighting sampling methods make use of an auxiliary variable corresponding to the output of a gene-flow model (a zero-inflated Poisson model) simulating cross-pollination as a function of wind speed, wind direction, and distance to the closest GM maize field. With the stratified sampling method, an auxiliary variable is used to define several strata with contrasting transgene presence rates, and grains are then sampled at random from each stratum. With the two methods involving reweighting, grains are first sampled at random from various locations within the field, and the observations are then reweighted according to the auxiliary variable. Data collected from three maize fields were used to compare the four sampling methods, and the results were used to determine the extent to which transgene presence rate estimation was improved by the use of stratified and reweighting sampling methods. We found that transgene rate estimates were more accurate and that substantially smaller samples could be used with sampling strategies based on an auxiliary variable derived from a gene-flow model. © 2017 Society for Risk Analysis.

Poly-Gaussian model of randomly rough surface in rarefied gas flow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aksenova, Olga A.; Khalidov, Iskander A.

2014-12-09

Surface roughness is simulated by the model of non-Gaussian random process. Our results for the scattering of rarefied gas atoms from a rough surface using modified approach to the DSMC calculation of rarefied gas flow near a rough surface are developed and generalized applying the poly-Gaussian model representing probability density as the mixture of Gaussian densities. The transformation of the scattering function due to the roughness is characterized by the roughness operator. Simulating rough surface of the walls by the poly-Gaussian random field expressed as integrated Wiener process, we derive a representation of the roughness operator that can be appliedmore » in numerical DSMC methods as well as in analytical investigations.« less

Probability distribution of the entanglement across a cut at an infinite-randomness fixed point

NASA Astrophysics Data System (ADS)

Devakul, Trithep; Majumdar, Satya N.; Huse, David A.

2017-03-01

We calculate the probability distribution of entanglement entropy S across a cut of a finite one-dimensional spin chain of length L at an infinite-randomness fixed point using Fisher's strong randomness renormalization group (RG). Using the random transverse-field Ising model as an example, the distribution is shown to take the form p (S |L ) ˜L-ψ (k ) , where k ≡S /ln[L /L0] , the large deviation function ψ (k ) is found explicitly, and L0 is a nonuniversal microscopic length. We discuss the implications of such a distribution on numerical techniques that rely on entanglement, such as matrix-product-state-based techniques. Our results are verified with numerical RG simulations, as well as the actual entanglement entropy distribution for the random transverse-field Ising model which we calculate for large L via a mapping to Majorana fermions.

Winter Simulation Conference, Miami Beach, Fla., December 4-6, 1978, Proceedings. Volumes 1 & 2

NASA Technical Reports Server (NTRS)

Highland, H. J. (Editor); Nielsen, N. R.; Hull, L. G.

1978-01-01

The papers report on the various aspects of simulation such as random variate generation, simulation optimization, ranking and selection of alternatives, model management, documentation, data bases, and instructional methods. Simulation studies in a wide variety of fields are described, including system design and scheduling, government and social systems, agriculture, computer systems, the military, transportation, corporate planning, ecosystems, health care, manufacturing and industrial systems, computer networks, education, energy, production planning and control, financial models, behavioral models, information systems, and inventory control.

Digital simulation of two-dimensional random fields with arbitrary power spectra and non-Gaussian probability distribution functions.

PubMed

Yura, Harold T; Hanson, Steen G

2012-04-01

Methods for simulation of two-dimensional signals with arbitrary power spectral densities and signal amplitude probability density functions are disclosed. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the desired spectral distribution, after which this colored Gaussian probability distribution is transformed via an inverse transform into the desired probability distribution. In most cases the method provides satisfactory results and can thus be considered an engineering approach. Several illustrative examples with relevance for optics are given.

Contextual interference effect on perceptual-cognitive skills training.

PubMed

Broadbent, David P; Causer, Joe; Ford, Paul R; Williams, A Mark

2015-06-01

Contextual interference (CI) effect predicts that a random order of practice for multiple skills is superior for learning compared to a blocked order. We report a novel attempt to examine the CI effect during acquisition and transfer of anticipatory judgments from simulation training to an applied sport situation. Participants were required to anticipate tennis shots under either a random practice schedule or a blocked practice schedule. Response accuracy was recorded for both groups in pretest, during acquisition, and on a 7-d retention test. Transfer of learning was assessed through a field-based tennis protocol that attempted to assess performance in an applied sport setting. The random practice group had significantly higher response accuracy scores on the 7-d laboratory retention test compared to the blocked group. Moreover, during the transfer of anticipatory judgments to an applied sport situation, the decision times of the random practice group were significantly lower compared to the blocked group. The CI effect extends to the training of anticipatory judgments through simulation techniques. Furthermore, we demonstrate for the first time that the CI effect increases transfer of learning from simulation training to an applied sport task, highlighting the importance of using appropriate practice schedules during simulation training.

Phase retrieval in generalized optical interferometry systems.

PubMed

Farriss, Wesley E; Fienup, James R; Malhotra, Tanya; Vamivakas, A Nick

2018-02-05

Modal analysis of an optical field via generalized interferometry (GI) is a novel technique that treats said field as a linear superposition of transverse modes and recovers the amplitudes of modal weighting coefficients. We use phase retrieval by nonlinear optimization to recover the phase of these modal weighting coefficients. Information diversity increases the robustness of the algorithm by better constraining the solution. Additionally, multiple sets of random starting phase values assist the algorithm in overcoming local minima. The algorithm was able to recover nearly all coefficient phases for simulated fields consisting of up to 21 superpositioned Hermite Gaussian modes from simulated data and proved to be resilient to shot noise.

A statistical simulation model for field testing of non-target organisms in environmental risk assessment of genetically modified plants.

PubMed

Goedhart, Paul W; van der Voet, Hilko; Baldacchino, Ferdinando; Arpaia, Salvatore

2014-04-01

Genetic modification of plants may result in unintended effects causing potentially adverse effects on the environment. A comparative safety assessment is therefore required by authorities, such as the European Food Safety Authority, in which the genetically modified plant is compared with its conventional counterpart. Part of the environmental risk assessment is a comparative field experiment in which the effect on non-target organisms is compared. Statistical analysis of such trials come in two flavors: difference testing and equivalence testing. It is important to know the statistical properties of these, for example, the power to detect environmental change of a given magnitude, before the start of an experiment. Such prospective power analysis can best be studied by means of a statistical simulation model. This paper describes a general framework for simulating data typically encountered in environmental risk assessment of genetically modified plants. The simulation model, available as Supplementary Material, can be used to generate count data having different statistical distributions possibly with excess-zeros. In addition the model employs completely randomized or randomized block experiments, can be used to simulate single or multiple trials across environments, enables genotype by environment interaction by adding random variety effects, and finally includes repeated measures in time following a constant, linear or quadratic pattern in time possibly with some form of autocorrelation. The model also allows to add a set of reference varieties to the GM plants and its comparator to assess the natural variation which can then be used to set limits of concern for equivalence testing. The different count distributions are described in some detail and some examples of how to use the simulation model to study various aspects, including a prospective power analysis, are provided.

A statistical simulation model for field testing of non-target organisms in environmental risk assessment of genetically modified plants

PubMed Central

Goedhart, Paul W; van der Voet, Hilko; Baldacchino, Ferdinando; Arpaia, Salvatore

2014-01-01

Genetic modification of plants may result in unintended effects causing potentially adverse effects on the environment. A comparative safety assessment is therefore required by authorities, such as the European Food Safety Authority, in which the genetically modified plant is compared with its conventional counterpart. Part of the environmental risk assessment is a comparative field experiment in which the effect on non-target organisms is compared. Statistical analysis of such trials come in two flavors: difference testing and equivalence testing. It is important to know the statistical properties of these, for example, the power to detect environmental change of a given magnitude, before the start of an experiment. Such prospective power analysis can best be studied by means of a statistical simulation model. This paper describes a general framework for simulating data typically encountered in environmental risk assessment of genetically modified plants. The simulation model, available as Supplementary Material, can be used to generate count data having different statistical distributions possibly with excess-zeros. In addition the model employs completely randomized or randomized block experiments, can be used to simulate single or multiple trials across environments, enables genotype by environment interaction by adding random variety effects, and finally includes repeated measures in time following a constant, linear or quadratic pattern in time possibly with some form of autocorrelation. The model also allows to add a set of reference varieties to the GM plants and its comparator to assess the natural variation which can then be used to set limits of concern for equivalence testing. The different count distributions are described in some detail and some examples of how to use the simulation model to study various aspects, including a prospective power analysis, are provided. PMID:24834325

Meta-Analysis of Correlations Revisited: Attempted Replication and Extension of Field's (2001) Simulation Studies

ERIC Educational Resources Information Center

Hafdahl, Adam R.; Williams, Michelle A.

2009-01-01

In 2 Monte Carlo studies of fixed- and random-effects meta-analysis for correlations, A. P. Field (2001) ostensibly evaluated Hedges-Olkin-Vevea Fisher-[zeta] and Schmidt-Hunter Pearson-r estimators and tests in 120 conditions. Some authors have cited those results as evidence not to meta-analyze Fisher-[zeta] correlations, especially with…

Robotic Range Clearance Competition (R2C2)

DTIC Science & Technology

2011-10-01

unexploded ordnance (UXO). A large part of the debris field consists of ferrous metal objects that magnetic 39 Distribution A: Approved for public...was set at 7 degrees above horizontal based on terrain around the Base station. We used the BSUBR file for all fields except the Subsurface...and subsurface clearance test areas had numerous pieces of simulated unexploded ordinance (SUXO) buried at random locations around the field . These

Influence of Embedded Inhomogeneities on the Spectral Ratio of the Horizontal Components of a Random Field of Rayleigh Waves

NASA Astrophysics Data System (ADS)

Tsukanov, A. A.; Gorbatnikov, A. V.

2018-01-01

Study of the statistical parameters of the Earth's random microseismic field makes it possible to obtain estimates of the properties and structure of the Earth's crust and upper mantle. Different approaches are used to observe and process the microseismic records, which are divided into several groups of passive seismology methods. Among them are the well-known methods of surface-wave tomography, the spectral H/ V ratio of the components in the surface wave, and microseismic sounding, currently under development, which uses the spectral ratio V/ V 0 of the vertical components between pairs of spatially separated stations. In the course of previous experiments, it became clear that these ratios are stable statistical parameters of the random field that do not depend on the properties of microseism sources. This paper proposes to expand the mentioned approach and study the possibilities for using the ratio of the horizontal components H 1/ H 2 of the microseismic field. Numerical simulation was used to study the influence of an embedded velocity inhomogeneity on the spectral ratio of the horizontal components of the random field of fundamental Rayleigh modes, based on the concept that the Earth's microseismic field is represented by these waves in a significant part of the frequency spectrum.

Dynamical influence processes on networks: general theory and applications to social contagion.

PubMed

Harris, Kameron Decker; Danforth, Christopher M; Dodds, Peter Sheridan

2013-08-01

We study binary state dynamics on a network where each node acts in response to the average state of its neighborhood. By allowing varying amounts of stochasticity in both the network and node responses, we find different outcomes in random and deterministic versions of the model. In the limit of a large, dense network, however, we show that these dynamics coincide. We construct a general mean-field theory for random networks and show this predicts that the dynamics on the network is a smoothed version of the average response function dynamics. Thus, the behavior of the system can range from steady state to chaotic depending on the response functions, network connectivity, and update synchronicity. As a specific example, we model the competing tendencies of imitation and nonconformity by incorporating an off-threshold into standard threshold models of social contagion. In this way, we attempt to capture important aspects of fashions and societal trends. We compare our theory to extensive simulations of this "limited imitation contagion" model on Poisson random graphs, finding agreement between the mean-field theory and stochastic simulations.

Aging in the three-dimensional random-field Ising model

NASA Astrophysics Data System (ADS)

von Ohr, Sebastian; Manssen, Markus; Hartmann, Alexander K.

2017-07-01

We studied the nonequilibrium aging behavior of the random-field Ising model in three dimensions for various values of the disorder strength. This allowed us to investigate how the aging behavior changes across the ferromagnetic-paramagnetic phase transition. We investigated a large system size of N =2563 spins and up to 108 Monte Carlo sweeps. To reach these necessary long simulation times, we employed an implementation running on Intel Xeon Phi coprocessors, reaching single-spin-flip times as short as 6 ps. We measured typical correlation functions in space and time to extract a growing length scale and corresponding exponents.

A Gaussian random field model for similarity-based smoothing in Bayesian disease mapping.

PubMed

Baptista, Helena; Mendes, Jorge M; MacNab, Ying C; Xavier, Miguel; Caldas-de-Almeida, José

2016-08-01

Conditionally specified Gaussian Markov random field (GMRF) models with adjacency-based neighbourhood weight matrix, commonly known as neighbourhood-based GMRF models, have been the mainstream approach to spatial smoothing in Bayesian disease mapping. In the present paper, we propose a conditionally specified Gaussian random field (GRF) model with a similarity-based non-spatial weight matrix to facilitate non-spatial smoothing in Bayesian disease mapping. The model, named similarity-based GRF, is motivated for modelling disease mapping data in situations where the underlying small area relative risks and the associated determinant factors do not vary systematically in space, and the similarity is defined by "similarity" with respect to the associated disease determinant factors. The neighbourhood-based GMRF and the similarity-based GRF are compared and accessed via a simulation study and by two case studies, using new data on alcohol abuse in Portugal collected by the World Mental Health Survey Initiative and the well-known lip cancer data in Scotland. In the presence of disease data with no evidence of positive spatial correlation, the simulation study showed a consistent gain in efficiency from the similarity-based GRF, compared with the adjacency-based GMRF with the determinant risk factors as covariate. This new approach broadens the scope of the existing conditional autocorrelation models. © The Author(s) 2016.

A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields

DOE PAGES

Osborn, Sarah; Vassilevski, Panayot S.; Villa, Umberto

2017-10-26

In this paper, we propose an alternative method to generate samples of a spatially correlated random field with applications to large-scale problems for forward propagation of uncertainty. A classical approach for generating these samples is the Karhunen--Loève (KL) decomposition. However, the KL expansion requires solving a dense eigenvalue problem and is therefore computationally infeasible for large-scale problems. Sampling methods based on stochastic partial differential equations provide a highly scalable way to sample Gaussian fields, but the resulting parametrization is mesh dependent. We propose a multilevel decomposition of the stochastic field to allow for scalable, hierarchical sampling based on solving amore » mixed finite element formulation of a stochastic reaction-diffusion equation with a random, white noise source function. Lastly, numerical experiments are presented to demonstrate the scalability of the sampling method as well as numerical results of multilevel Monte Carlo simulations for a subsurface porous media flow application using the proposed sampling method.« less

A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Osborn, Sarah; Vassilevski, Panayot S.; Villa, Umberto

In this paper, we propose an alternative method to generate samples of a spatially correlated random field with applications to large-scale problems for forward propagation of uncertainty. A classical approach for generating these samples is the Karhunen--Loève (KL) decomposition. However, the KL expansion requires solving a dense eigenvalue problem and is therefore computationally infeasible for large-scale problems. Sampling methods based on stochastic partial differential equations provide a highly scalable way to sample Gaussian fields, but the resulting parametrization is mesh dependent. We propose a multilevel decomposition of the stochastic field to allow for scalable, hierarchical sampling based on solving amore » mixed finite element formulation of a stochastic reaction-diffusion equation with a random, white noise source function. Lastly, numerical experiments are presented to demonstrate the scalability of the sampling method as well as numerical results of multilevel Monte Carlo simulations for a subsurface porous media flow application using the proposed sampling method.« less

Spatio-temporal modelling of wind speed variations and extremes in the Caribbean and the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Rychlik, Igor; Mao, Wengang

2018-02-01

The wind speed variability in the North Atlantic has been successfully modelled using a spatio-temporal transformed Gaussian field. However, this type of model does not correctly describe the extreme wind speeds attributed to tropical storms and hurricanes. In this study, the transformed Gaussian model is further developed to include the occurrence of severe storms. In this new model, random components are added to the transformed Gaussian field to model rare events with extreme wind speeds. The resulting random field is locally stationary and homogeneous. The localized dependence structure is described by time- and space-dependent parameters. The parameters have a natural physical interpretation. To exemplify its application, the model is fitted to the ECMWF ERA-Interim reanalysis data set. The model is applied to compute long-term wind speed distributions and return values, e.g., 100- or 1000-year extreme wind speeds, and to simulate random wind speed time series at a fixed location or spatio-temporal wind fields around that location.

Growth of pea epicotyl in low magnetic field: implication for space research.

PubMed

Negishi, Y; Hashimoto, A; Tsushima, M; Dobrota, C; Yamashita, M; Nakamura, T

1999-01-01

A magnetic field is an inescapable environmental factor for plants on the earth. However, its impact on plant growth is not well understood. In order to survey how magnetic fields affect plant, Alaska pea seedlings were incubated under low magnetic field (LMF) and also in the normal geo-magnetic environment. Two-day-old etiolated seedlings were incubated in a magnetic shield box and in a control box. Sedimentation of amyloplasts was examined in the epicotyls of seedlings grown under these two conditions. The elongation of epicotyls was promoted by LMF. Elongation was most prominent in the middle part of the epicotyls. Cell elongation and increased osmotic pressure of cell sap were found in the epidermal cells exposed to LMF. When the gravitational environment was 1G, the epicotyls incubated under both LMF and normal geomagnetic field grew straight upward and amyloplasts sedimented similarly. However, under simulated microgravity (clinostat), epicotyl and cell elongation was promoted. Furthermore, the epicotyls bent and amyloplasts were dispersed in the cells in simulated microgravity. The dispersion of amyloplasts may relate to the posture control in epicotyl growth under simulated microgravity generated by 3D clinorotation, since it was not observed under LMF in 1G. Since enhanced elongation of cells was commonly seen both at LMF and in simulated microgravity, all elongation on the 3D-clinostat could result from pseudo-low magnetic field, as a by-product of clinorotation. (i.e., clinostat results could be based on randomization of magnetic field together with randomization of gravity vector.) Our results point to the possible use of space for studies in magnetic biology. With space experiments, the effects of dominant environmental factors, such as gravity on plants, could be neutralized or controlled for to reveal magnetic effects more clearly. c1999 COSPAR. Published by Elsevier Science Ltd.

Cluster mass inference via random field theory.

PubMed

Zhang, Hui; Nichols, Thomas E; Johnson, Timothy D

2009-01-01

Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this method for Gaussian images, evaluate it on Gaussian and Gaussianized t-statistic images and investigate its statistical properties via simulation studies and real data. Simulation results show that the method is valid under the null hypothesis and demonstrate that it can be more powerful than the cluster extent inference method. Further, analyses with a single subject and a group fMRI dataset demonstrate better power than traditional cluster size inference, and good accuracy relative to a gold-standard permutation test.

Shock Interaction with Random Spherical Particle Beds

NASA Astrophysics Data System (ADS)

Neal, Chris; Mehta, Yash; Salari, Kambiz; Jackson, Thomas L.; Balachandar, S. "Bala"; Thakur, Siddharth

2016-11-01

In this talk we present results on fully resolved simulations of shock interaction with randomly distributed bed of particles. Multiple simulations were carried out by varying the number of particles to isolate the effect of volume fraction. Major focus of these simulations was to understand 1) the effect of the shockwave and volume fraction on the forces experienced by the particles, 2) the effect of particles on the shock wave, and 3) fluid mediated particle-particle interactions. Peak drag force for particles at different volume fractions show a downward trend as the depth of the bed increased. This can be attributed to dissipation of energy as the shockwave travels through the bed of particles. One of the fascinating observations from these simulations was the fluctuations in different quantities due to presence of multiple particles and their random distribution. These are large simulations with hundreds of particles resulting in large amount of data. We present statistical analysis of the data and make relevant observations. Average pressure in the computational domain is computed to characterize the strengths of the reflected and transmitted waves. We also present flow field contour plots to support our observations. U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program, under Contract No. DE-NA0002378.

Effect of random errors in planar PIV data on pressure estimation in vortex dominated flows

NASA Astrophysics Data System (ADS)

McClure, Jeffrey; Yarusevych, Serhiy

2015-11-01

The sensitivity of pressure estimation techniques from Particle Image Velocimetry (PIV) measurements to random errors in measured velocity data is investigated using the flow over a circular cylinder as a test case. Direct numerical simulations are performed for ReD = 100, 300 and 1575, spanning laminar, transitional, and turbulent wake regimes, respectively. A range of random errors typical for PIV measurements is applied to synthetic PIV data extracted from numerical results. A parametric study is then performed using a number of common pressure estimation techniques. Optimal temporal and spatial resolutions are derived based on the sensitivity of the estimated pressure fields to the simulated random error in velocity measurements, and the results are compared to an optimization model derived from error propagation theory. It is shown that the reductions in spatial and temporal scales at higher Reynolds numbers leads to notable changes in the optimal pressure evaluation parameters. The effect of smaller scale wake structures is also quantified. The errors in the estimated pressure fields are shown to depend significantly on the pressure estimation technique employed. The results are used to provide recommendations for the use of pressure and force estimation techniques from experimental PIV measurements in vortex dominated laminar and turbulent wake flows.

Generation of dense plume fingers in saturated-unsaturated homogeneous porous media

NASA Astrophysics Data System (ADS)

Cremer, Clemens J. M.; Graf, Thomas

2015-02-01

Flow under variable-density conditions is widespread, occurring in geothermal reservoirs, at waste disposal sites or due to saltwater intrusion. The migration of dense plumes typically results in the formation of vertical plume fingers which are known to be triggered by material heterogeneity or by variations in source concentration that causes the density variation. Using a numerical groundwater model, six perturbation methods are tested under saturated and unsaturated flow conditions to mimic heterogeneity and concentration variations on the pore scale in order to realistically generate dense fingers. A laboratory-scale sand tank experiment is numerically simulated, and the perturbation methods are evaluated by comparing plume fingers obtained from the laboratory experiment with numerically simulated fingers. Dense plume fingering for saturated flow can best be reproduced with a spatially random, time-constant perturbation of the solute source. For unsaturated flow, a spatially and temporally random noise of solute concentration or a random conductivity field adequately simulate plume fingering.

Nonlinear wave chaos: statistics of second harmonic fields.

PubMed

Zhou, Min; Ott, Edward; Antonsen, Thomas M; Anlage, Steven M

2017-10-01

Concepts from the field of wave chaos have been shown to successfully predict the statistical properties of linear electromagnetic fields in electrically large enclosures. The Random Coupling Model (RCM) describes these properties by incorporating both universal features described by Random Matrix Theory and the system-specific features of particular system realizations. In an effort to extend this approach to the nonlinear domain, we add an active nonlinear frequency-doubling circuit to an otherwise linear wave chaotic system, and we measure the statistical properties of the resulting second harmonic fields. We develop an RCM-based model of this system as two linear chaotic cavities coupled by means of a nonlinear transfer function. The harmonic field strengths are predicted to be the product of two statistical quantities and the nonlinearity characteristics. Statistical results from measurement-based calculation, RCM-based simulation, and direct experimental measurements are compared and show good agreement over many decades of power.

A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

DOE PAGES

Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

2016-07-20

A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less

A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less

Simulating Flaring Events via an Intelligent Cellular Automata Mechanism

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Vlahos, L.; Isliker, H.; Georgoulis, M.

2010-07-01

We simulate flaring events through a Cellular Automaton (CA) model, in which, for the first time, we use observed vector magnetograms as initial conditions. After non-linear force free extrapolation of the magnetic field from the vector magnetograms, we identify magnetic discontinuities, using two alternative criteria: (1) the average magnetic field gradient, or (2) the normalized magnetic field curl (i.e. the current). Magnetic discontinuities are identified at the grid-sites where the magnetic field gradient or curl exceeds a specified threshold. We then relax the magnetic discontinuities according to the rules of Lu and Hamilton (1991) or Lu et al. (1993), i.e. we redistribute the magnetic field locally so that the discontinuities disappear. In order to simulate the flaring events, we consider several alternative scenarios with regard to: (1) The threshold above which magnetic discontinuities are identified (applying low, high, and height-dependent threshold values); (2) The driving process that occasionally causes new discontinuities (at randomly chosen grid sites, magnetic field increments are added that are perpendicular (or may-be also parallel) to the existing magnetic field). We address the question whether the coronal active region magnetic fields can indeed be considered to be in the state of self-organized criticality (SOC).

Zero field reversal probability in thermally assisted magnetization reversal

NASA Astrophysics Data System (ADS)

Prasetya, E. B.; Utari; Purnama, B.

2017-11-01

This paper discussed about zero field reversal probability in thermally assisted magnetization reversal (TAMR). Appearance of reversal probability in zero field investigated through micromagnetic simulation by solving stochastic Landau-Lifshitz-Gibert (LLG). The perpendicularly anisotropy magnetic dot of 50×50×20 nm3 is considered as single cell magnetic storage of magnetic random acces memory (MRAM). Thermally assisted magnetization reversal was performed by cooling writing process from near/almost Curie point to room temperature on 20 times runs for different randomly magnetized state. The results show that the probability reversal under zero magnetic field decreased with the increase of the energy barrier. The zero-field probability switching of 55% attained for energy barrier of 60 k B T and the reversal probability become zero noted at energy barrier of 2348 k B T. The higest zero-field switching probability of 55% attained for energy barrier of 60 k B T which corespond to magnetif field of 150 Oe for switching.

Conditional Random Field-Based Offline Map Matching for Indoor Environments

PubMed Central

Bataineh, Safaa; Bahillo, Alfonso; Díez, Luis Enrique; Onieva, Enrique; Bataineh, Ikram

2016-01-01

In this paper, we present an offline map matching technique designed for indoor localization systems based on conditional random fields (CRF). The proposed algorithm can refine the results of existing indoor localization systems and match them with the map, using loose coupling between the existing localization system and the proposed map matching technique. The purpose of this research is to investigate the efficiency of using the CRF technique in offline map matching problems for different scenarios and parameters. The algorithm was applied to several real and simulated trajectories of different lengths. The results were then refined and matched with the map using the CRF algorithm. PMID:27537892

Conditional Random Field-Based Offline Map Matching for Indoor Environments.

PubMed

Bataineh, Safaa; Bahillo, Alfonso; Díez, Luis Enrique; Onieva, Enrique; Bataineh, Ikram

2016-08-16

In this paper, we present an offline map matching technique designed for indoor localization systems based on conditional random fields (CRF). The proposed algorithm can refine the results of existing indoor localization systems and match them with the map, using loose coupling between the existing localization system and the proposed map matching technique. The purpose of this research is to investigate the efficiency of using the CRF technique in offline map matching problems for different scenarios and parameters. The algorithm was applied to several real and simulated trajectories of different lengths. The results were then refined and matched with the map using the CRF algorithm.

Box-Cox Mixed Logit Model for Travel Behavior Analysis

NASA Astrophysics Data System (ADS)

Orro, Alfonso; Novales, Margarita; Benitez, Francisco G.

2010-09-01

To represent the behavior of travelers when they are deciding how they are going to get to their destination, discrete choice models, based on the random utility theory, have become one of the most widely used tools. The field in which these models were developed was halfway between econometrics and transport engineering, although the latter now constitutes one of their principal areas of application. In the transport field, they have mainly been applied to mode choice, but also to the selection of destination, route, and other important decisions such as the vehicle ownership. In usual practice, the most frequently employed discrete choice models implement a fixed coefficient utility function that is linear in the parameters. The principal aim of this paper is to present the viability of specifying utility functions with random coefficients that are nonlinear in the parameters, in applications of discrete choice models to transport. Nonlinear specifications in the parameters were present in discrete choice theory at its outset, although they have seldom been used in practice until recently. The specification of random coefficients, however, began with the probit and the hedonic models in the 1970s, and, after a period of apparent little practical interest, has burgeoned into a field of intense activity in recent years with the new generation of mixed logit models. In this communication, we present a Box-Cox mixed logit model, original of the authors. It includes the estimation of the Box-Cox exponents in addition to the parameters of the random coefficients distribution. Probability of choose an alternative is an integral that will be calculated by simulation. The estimation of the model is carried out by maximizing the simulated log-likelihood of a sample of observed individual choices between alternatives. The differences between the predictions yielded by models that are inconsistent with real behavior have been studied with simulation experiments.

Universality of Critically Pinned Interfaces in Two-Dimensional Isotropic Random Media

NASA Astrophysics Data System (ADS)

Grassberger, Peter

2018-05-01

Based on extensive simulations, we conjecture that critically pinned interfaces in two-dimensional isotropic random media with short-range correlations are always in the universality class of ordinary percolation. Thus, in contrast to interfaces in >2 dimensions, there is no distinction between fractal (i.e., percolative) and rough but nonfractal interfaces. Our claim includes interfaces in zero-temperature random field Ising models (both with and without spontaneous nucleation), in heterogeneous bootstrap percolation, and in susceptible-weakened-infected-removed epidemics. It does not include models with long-range correlations in the randomness and models where overhangs are explicitly forbidden (which would imply nonisotropy of the medium).

Joint simulation of stationary grade and non-stationary rock type for quantifying geological uncertainty in a copper deposit

NASA Astrophysics Data System (ADS)

Maleki, Mohammad; Emery, Xavier

2017-12-01

In mineral resources evaluation, the joint simulation of a quantitative variable, such as a metal grade, and a categorical variable, such as a rock type, is challenging when one wants to reproduce spatial trends of the rock type domains, a feature that makes a stationarity assumption questionable. To address this problem, this work presents methodological and practical proposals for jointly simulating a grade and a rock type, when the former is represented by the transform of a stationary Gaussian random field and the latter is obtained by truncating an intrinsic random field of order k with Gaussian generalized increments. The proposals concern both the inference of the model parameters and the construction of realizations conditioned to existing data. The main difficulty is the identification of the spatial correlation structure, for which a semi-automated algorithm is designed, based on a least squares fitting of the data-to-data indicator covariances and grade-indicator cross-covariances. The proposed models and algorithms are applied to jointly simulate the copper grade and the rock type in a Chilean porphyry copper deposit. The results show their ability to reproduce the gradual transitions of the grade when crossing a rock type boundary, as well as the spatial zonation of the rock type.

MICROBIAL POPULATION CHANGES DURING BIOREMEDIATION OF AN EXPERIMENTAL OIL SPILL

EPA Science Inventory

Three crude oil bioremediation techniques were applied in a randomized block field experiment simulating a coastal oil-spill. Four treatments (no oil control, oil alone, oil + nutrients, and oil + nutrients + an indigenous inoculum) were applied. In-situ microbial community str...

Collision Models for Particle Orbit Code on SSX

NASA Astrophysics Data System (ADS)

Fisher, M. W.; Dandurand, D.; Gray, T.; Brown, M. R.; Lukin, V. S.

2011-10-01

Coulomb collision models are being developed and incorporated into the Hamiltonian particle pushing code (PPC) for applications to the Swarthmore Spheromak eXperiment (SSX). A Monte Carlo model based on that of Takizuka and Abe [JCP 25, 205 (1977)] performs binary collisions between test particles and thermal plasma field particles randomly drawn from a stationary Maxwellian distribution. A field-based electrostatic fluctuation model scatters particles from a spatially uniform random distribution of positive and negative spherical potentials generated throughout the plasma volume. The number, radii, and amplitude of these potentials are chosen to mimic the correct particle diffusion statistics without the use of random particle draws or collision frequencies. An electromagnetic fluctuating field model will be presented, if available. These numerical collision models will be benchmarked against known analytical solutions, including beam diffusion rates and Spitzer resistivity, as well as each other. The resulting collisional particle orbit models will be used to simulate particle collection with electrostatic probes in the SSX wind tunnel, as well as particle confinement in typical SSX fields. This work has been supported by US DOE, NSF and ONR.

A random walk model to simulate the atmospheric dispersion of radionuclide

NASA Astrophysics Data System (ADS)

Zhuo, Jun; Huang, Liuxing; Niu, Shengli; Xie, Honggang; Kuang, Feihong

2018-01-01

To investigate the atmospheric dispersion of radionuclide in large-medium scale, a numerical simulation method based on random walk model for radionuclide atmospheric dispersion was established in the paper. The route of radionuclide migration and concentration distribution of radionuclide can be calculated out by using the method with the real-time or historical meteorological fields. In the simulation, a plume of radionuclide is treated as a lot of particles independent of each other. The particles move randomly by the fluctuations of turbulence, and disperse, so as to enlarge the volume of the plume and dilute the concentration of radionuclide. The dispersion of the plume over time is described by the variance of the particles. Through statistical analysis, the relationships between variance of the particles and radionuclide dispersion characteristics can be derived. The main mechanisms considered in the physical model are: (1) advection of radionuclide by mean air motion, (2) mixing of radionuclide by atmospheric turbulence, (3) dry and wet deposition, (4) disintegration. A code named RADES was developed according the method. And then, the European Tracer Experiment (ETEX) in 1994 is simulated by the RADES and FLEXPART codes, the simulation results of the concentration distribution of tracer are in good agreement with the experimental data.

Machine Learning Classification of Heterogeneous Fields to Estimate Physical Responses

NASA Astrophysics Data System (ADS)

McKenna, S. A.; Akhriev, A.; Alzate, C.; Zhuk, S.

2017-12-01

The promise of machine learning to enhance physics-based simulation is examined here using the transient pressure response to a pumping well in a heterogeneous aquifer. 10,000 random fields of log10 hydraulic conductivity (K) are created and conditioned on a single K measurement at the pumping well. Each K-field is used as input to a forward simulation of drawdown (pressure decline). The differential equations governing groundwater flow to the well serve as a non-linear transform of the input K-field to an output drawdown field. The results are stored and the data set is split into training and testing sets for classification. A Euclidean distance measure between any two fields is calculated and the resulting distances between all pairs of fields define a similarity matrix. Similarity matrices are calculated for both input K-fields and the resulting drawdown fields at the end of the simulation. The similarity matrices are then used as input to spectral clustering to determine groupings of similar input and output fields. Additionally, the similarity matrix is used as input to multi-dimensional scaling to visualize the clustering of fields in lower dimensional spaces. We examine the ability to cluster both input K-fields and output drawdown fields separately with the goal of identifying K-fields that create similar drawdowns and, conversely, given a set of simulated drawdown fields, identify meaningful clusters of input K-fields. Feature extraction based on statistical parametric mapping provides insight into what features of the fields drive the classification results. The final goal is to successfully classify input K-fields into the correct output class, and also, given an output drawdown field, be able to infer the correct class of input field that created it.

Simulating and mapping spatial complexity using multi-scale techniques

USGS Publications Warehouse

De Cola, L.

1994-01-01

A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author

Dynamics and morphology of chiral magnetic bubbles in perpendicularly magnetized ultra-thin films

NASA Astrophysics Data System (ADS)

Sarma, Bhaskarjyoti; Garcia-Sanchez, Felipe; Nasseri, S. Ali; Casiraghi, Arianna; Durin, Gianfranco

2018-06-01

We study bubble domain wall dynamics using micromagnetic simulations in perpendicularly magnetized ultra-thin films with disorder and Dzyaloshinskii-Moriya interaction. Disorder is incorporated into the material as grains with randomly distributed sizes and varying exchange constant at the edges. As expected, magnetic bubbles expand asymmetrically along the axis of the in-plane field under the simultaneous application of out-of-plane and in-plane fields. Remarkably, the shape of the bubble has a ripple-like part which causes a kink-like (steep decrease) feature in the velocity versus in-plane field curve. We show that these ripples originate due to the nucleation and interaction of vertical Bloch lines. Furthermore, we show that the Dzyaloshinskii-Moriya interaction field is not constant but rather depends on the in-plane field. We also extend the collective coordinate model for domain wall motion to a magnetic bubble and compare it with the results of micromagnetic simulations.

MAGNETIC FIELD LINE RANDOM WALK FOR DISTURBED FLUX SURFACES: TRAPPING EFFECTS AND MULTIPLE ROUTES TO BOHM DIFFUSION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghilea, M. C.; Ruffolo, D.; Sonsrettee, W.

2011-11-01

The magnetic field line random walk (FLRW) is important for the transport of energetic particles in many astrophysical situations. While all authors agree on the quasilinear diffusion of field lines for fluctuations that mainly vary parallel to a large-scale field, for the opposite case of fluctuations that mainly vary in the perpendicular directions, there has been an apparent conflict between concepts of Bohm diffusion and percolation/trapping effects. Here computer simulation and non-perturbative analytic techniques are used to re-examine the FLRW in magnetic turbulence with slab and two-dimensional (2D) components, in which 2D flux surfaces are disturbed by the slab fluctuations.more » Previous non-perturbative theories for D{sub perpendicular}, based on Corrsin's hypothesis, have identified a slab contribution with quasilinear behavior and a 2D contribution due to Bohm diffusion with diffusive decorrelation (DD), combined in a quadratic formula. Here we present analytic theories for other routes to Bohm diffusion, with random ballistic decorrelation (RBD) either due to the 2D component itself (for a weak slab contribution) or the total fluctuation field (for a strong slab contribution), combined in a direct sum with the slab contribution. Computer simulations confirm the applicability of RBD routes for weak or strong slab contributions, while the DD route applies for a moderate slab contribution. For a very low slab contribution, interesting trapping effects are found, including a depressed diffusion coefficient and subdiffusive behavior. Thus quasilinear, Bohm, and trapping behaviors are all found in the same system, together with an overall viewpoint to explain these behaviors.« less

Subwavelenght Light Localization in Nanostructured Surfaces

NASA Astrophysics Data System (ADS)

Coello, V.; Wang, S.; Siqueiros, J.; Bozhevolnyi, S. I.

Using a photon scanning tunneling microscope, we studied near field optical images obtained with a surface plasmon polariton (SPP) being resonantly excited along a surface with a random introduced roughness. The SPP intensity field distributions showed an optical enhancement in the form of round bright spots up to 5 times larger than the background signal. We also show an artificially fabricated SPP curved micromirror along with the corresponding near-field optical image. The recorded optical signal exhibited an enhancement up to 10 times larger than the background, which has been generated for the first time in a controlled form. A numerical simulation of a parabolic micromirror based on isotropic pointlike scatterers is analyzed and compared with experimental results. The potential of creating microstructures able to control SPP optical field enhancement is showed in a novel numerically simulated microcavity for SPP's.

Relative distribution of cosmic rays and magnetic fields

NASA Astrophysics Data System (ADS)

Seta, Amit; Shukurov, Anvar; Wood, Toby S.; Bushby, Paul J.; Snodin, Andrew P.

2018-02-01

Synchrotron radiation from cosmic rays is a key observational probe of the galactic magnetic field. Interpreting synchrotron emission data requires knowledge of the cosmic ray number density, which is often assumed to be in energy equipartition (or otherwise tightly correlated) with the magnetic field energy. However, there is no compelling observational or theoretical reason to expect such a tight correlation to hold across all scales. We use test particle simulations, tracing the propagation of charged particles (protons) through a random magnetic field, to study the cosmic ray distribution at scales comparable to the correlation scale of the turbulent flow in the interstellar medium (≃100 pc in spiral galaxies). In these simulations, we find that there is no spatial correlation between the cosmic ray number density and the magnetic field energy density. In fact, their distributions are approximately statistically independent. We find that low-energy cosmic rays can become trapped between magnetic mirrors, whose location depends more on the structure of the field lines than on the field strength.

A phase-field approach to model multi-axial and microstructure dependent fracture in nuclear grade graphite

DOE PAGES

Chakraborty, Pritam; Sabharwall, Piyush; Carroll, Mark C.

2016-04-07

The fracture behavior of nuclear grade graphites is strongly influenced by underlying microstructural features such as the character of filler particles, and the distribution of pores and voids. These microstructural features influence the crack nucleation and propagation behavior, resulting in quasi-brittle fracture with a tortuous crack path and significant scatter in measured bulk strength. This paper uses a phase-field method to model the microstructural and multi-axial fracture in H-451, a historic variant of nuclear graphite that provides the basis for an idealized study on a legacy grade. The representative volume elements are constructed from randomly located pores with random sizemore » obtained from experimentally determined log-normal distribution. The representative volume elements are then subjected to simulated multi-axial loading, and a reasonable agreement of the resulting fracture stress with experiments is obtained. Finally, quasi-brittle stress-strain evolution with a tortuous crack path is also observed from the simulations and is consistent with experimental results.« less

Localized surface plasmon enhanced cellular imaging using random metallic structures

NASA Astrophysics Data System (ADS)

Son, Taehwang; Lee, Wonju; Kim, Donghyun

2017-02-01

We have studied fluorescence cellular imaging with randomly distributed localized near-field induced by silver nano-islands. For the fabrication of nano-islands, a 10-nm silver thin film evaporated on a BK7 glass substrate with an adhesion layer of 2-nm thick chromium. Micrometer sized silver square pattern was defined using e-beam lithography and then the film was annealed at 200°C. Raw images were restored using electric field distribution produced on the surface of random nano-islands. Nano-islands were modeled from SEM images. 488-nm p-polarized light source was set to be incident at 60°. Simulation results show that localized electric fields were created among nano-islands and that their average size was found to be 135 nm. The feasibility was tested using conventional total internal reflection fluorescence microscopy while the angle of incidence was adjusted to maximize field enhancement. Mouse microphage cells were cultured on nano-islands, and actin filaments were selectively stained with FITC-conjugated phalloidin. Acquired images were deconvolved based on linear imaging theory, in which molecular distribution was sampled by randomly distributed localized near-field and blurred by point spread function of far-field optics. The optimum fluorophore distribution was probabilistically estimated by repetitively matching a raw image. The deconvolved images are estimated to have a resolution in the range of 100-150 nm largely determined by the size of localized near-fields. We also discuss and compare the results with images acquired with periodic nano-aperture arrays in various optical configurations to excite localized plasmonic fields and to produce super-resolved molecular images.

specsim: A Fortran-77 program for conditional spectral simulation in 3D

NASA Astrophysics Data System (ADS)

Yao, Tingting

1998-12-01

A Fortran 77 program, specsim, is presented for conditional spectral simulation in 3D domains. The traditional Fourier integral method allows generating random fields with a given covariance spectrum. Conditioning to local data is achieved by an iterative identification of the conditional phase information. A flowchart of the program is given to illustrate the implementation procedures of the program. A 3D case study is presented to demonstrate application of the program. A comparison with the traditional sequential Gaussian simulation algorithm emphasizes the advantages and drawbacks of the proposed algorithm.

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

Spectral turning bands for efficient Gaussian random fields generation on GPUs and accelerators

NASA Astrophysics Data System (ADS)

Hunger, L.; Cosenza, B.; Kimeswenger, S.; Fahringer, T.

2015-11-01

A random field (RF) is a set of correlated random variables associated with different spatial locations. RF generation algorithms are of crucial importance for many scientific areas, such as astrophysics, geostatistics, computer graphics, and many others. Current approaches commonly make use of 3D fast Fourier transform (FFT), which does not scale well for RF bigger than the available memory; they are also limited to regular rectilinear meshes. We introduce random field generation with the turning band method (RAFT), an RF generation algorithm based on the turning band method that is optimized for massively parallel hardware such as GPUs and accelerators. Our algorithm replaces the 3D FFT with a lower-order, one-dimensional FFT followed by a projection step and is further optimized with loop unrolling and blocking. RAFT can easily generate RF on non-regular (non-uniform) meshes and efficiently produce fields with mesh sizes bigger than the available device memory by using a streaming, out-of-core approach. Our algorithm generates RF with the correct statistical behavior and is tested on a variety of modern hardware, such as NVIDIA Tesla, AMD FirePro and Intel Phi. RAFT is faster than the traditional methods on regular meshes and has been successfully applied to two real case scenarios: planetary nebulae and cosmological simulations.

Imparting protean behavior to mobile robots accomplishing patrolling tasks in the presence of adversaries.

PubMed

Curiac, Daniel-Ioan; Volosencu, Constantin

2015-10-08

Providing unpredictable trajectories for patrol robots is essential when coping with adversaries. In order to solve this problem we developed an effective approach based on the known protean behavior of individual prey animals-random zig-zag movement. The proposed bio-inspired method modifies the normal robot's path by incorporating sudden and irregular direction changes without jeopardizing the robot's mission. Such a tactic is aimed to confuse the enemy (e.g. a sniper), offering less time to acquire and retain sight alignment and sight picture. This idea is implemented by simulating a series of fictive-temporary obstacles that will randomly appear in the robot's field of view, deceiving the obstacle avoiding mechanism to react. The new general methodology is particularized by using the Arnold's cat map to obtain the timely random appearance and disappearance of the fictive obstacles. The viability of the proposed method is confirmed through an extensive simulation case study.

Exploring the parameter space of the coarse-grained UNRES force field by random search: selecting a transferable medium-resolution force field.

PubMed

He, Yi; Xiao, Yi; Liwo, Adam; Scheraga, Harold A

2009-10-01

We explored the energy-parameter space of our coarse-grained UNRES force field for large-scale ab initio simulations of protein folding, to obtain good initial approximations for hierarchical optimization of the force field with new virtual-bond-angle bending and side-chain-rotamer potentials which we recently introduced to replace the statistical potentials. 100 sets of energy-term weights were generated randomly, and good sets were selected by carrying out replica-exchange molecular dynamics simulations of two peptides with a minimal alpha-helical and a minimal beta-hairpin fold, respectively: the tryptophan cage (PDB code: 1L2Y) and tryptophan zipper (PDB code: 1LE1). Eight sets of parameters produced native-like structures of these two peptides. These eight sets were tested on two larger proteins: the engrailed homeodomain (PDB code: 1ENH) and FBP WW domain (PDB code: 1E0L); two sets were found to produce native-like conformations of these proteins. These two sets were tested further on a larger set of nine proteins with alpha or alpha + beta structure and found to locate native-like structures of most of them. These results demonstrate that, in addition to finding reasonable initial starting points for optimization, an extensive search of parameter space is a powerful method to produce a transferable force field. Copyright 2009 Wiley Periodicals, Inc.

Minimization of required model runs in the Random Mixing approach to inverse groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Hoerning, Sebastian; Bardossy, Andras; du Plessis, Jaco

2017-04-01

Most geostatistical inverse groundwater flow and transport modelling approaches utilize a numerical solver to minimize the discrepancy between observed and simulated hydraulic heads and/or hydraulic concentration values. The optimization procedure often requires many model runs, which for complex models lead to long run times. Random Mixing is a promising new geostatistical technique for inverse modelling. The method is an extension of the gradual deformation approach. It works by finding a field which preserves the covariance structure and maintains observed hydraulic conductivities. This field is perturbed by mixing it with new fields that fulfill the homogeneous conditions. This mixing is expressed as an optimization problem which aims to minimize the difference between the observed and simulated hydraulic heads and/or concentration values. To preserve the spatial structure, the mixing weights must lie on the unit hyper-sphere. We present a modification to the Random Mixing algorithm which significantly reduces the number of model runs required. The approach involves taking n equally spaced points on the unit circle as weights for mixing conditional random fields. Each of these mixtures provides a solution to the forward model at the conditioning locations. For each of the locations the solutions are then interpolated around the circle to provide solutions for additional mixing weights at very low computational cost. The interpolated solutions are used to search for a mixture which maximally reduces the objective function. This is in contrast to other approaches which evaluate the objective function for the n mixtures and then interpolate the obtained values. Keeping the mixture on the unit circle makes it easy to generate equidistant sampling points in the space; however, this means that only two fields are mixed at a time. Once the optimal mixture for two fields has been found, they are combined to form the input to the next iteration of the algorithm. This process is repeated until a threshold in the objective function is met or insufficient changes are produced in successive iterations.

Investigation of Biotransport in a Tumor With Uncertain Material Properties Using a Nonintrusive Spectral Uncertainty Quantification Method.

PubMed

Alexanderian, Alen; Zhu, Liang; Salloum, Maher; Ma, Ronghui; Yu, Meilin

2017-09-01

In this study, statistical models are developed for modeling uncertain heterogeneous permeability and porosity in tumors, and the resulting uncertainties in pressure and velocity fields during an intratumoral injection are quantified using a nonintrusive spectral uncertainty quantification (UQ) method. Specifically, the uncertain permeability is modeled as a log-Gaussian random field, represented using a truncated Karhunen-Lòeve (KL) expansion, and the uncertain porosity is modeled as a log-normal random variable. The efficacy of the developed statistical models is validated by simulating the concentration fields with permeability and porosity of different uncertainty levels. The irregularity in the concentration field bears reasonable visual agreement with that in MicroCT images from experiments. The pressure and velocity fields are represented using polynomial chaos (PC) expansions to enable efficient computation of their statistical properties. The coefficients in the PC expansion are computed using a nonintrusive spectral projection method with the Smolyak sparse quadrature. The developed UQ approach is then used to quantify the uncertainties in the random pressure and velocity fields. A global sensitivity analysis is also performed to assess the contribution of individual KL modes of the log-permeability field to the total variance of the pressure field. It is demonstrated that the developed UQ approach can effectively quantify the flow uncertainties induced by uncertain material properties of the tumor.

Strong Shock Propagating Over A Random Bed of Spherical Particles

NASA Astrophysics Data System (ADS)

Mehta, Yash; Salari, Kambiz; Jackson, Thomas L.; Balachandar, S.; Thakur, Siddharth

2017-11-01

The study of shock interaction with particles has been largely motivated because of its wide-ranging applications. The complex interaction between the compressible flow features, such as shock wave and expansion fan, and the dispersed phase makes this multi-phase flow very difficult to predict and control. In this talk we will be presenting results on fully resolved inviscid simulations of shock interaction with random bed of particles. One of the fascinating observations from these simulations are the flow field fluctuations due to the presence of randomly distributed particles. Rigorous averaging (Favre averaging) of the governing equations results in Reynolds stress like term, which can be classified as pseudo turbulence in this case. We have computed this ``Reynolds stress'' term along with individual fluctuations and the turbulent kinetic energy. Average pressure was also computed to characterize the strength of the transmitted and the reflected waves. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program.

Self-Organization by Stochastic Reconnection: The Mechanism Underlying CMEs/Flares

NASA Astrophysics Data System (ADS)

Antiochos, S. K.; Knizhnik, K. J.; DeVore, C. R.

2017-12-01

The largest explosions in the solar system are the giant CMEs/flares that produce the most dangerous space weather at Earth, yet may also have been essential for the origin of life. The root cause of CMEs/flares is that the lowest-lying magnetic field lines in the Sun's corona undergo the continual buildup of stress and free energy that can be released only through explosive ejection. We perform the first MHD simulations of a coronal-photospheric magnetic system that is driven by random photospheric convective flows and has a realistic geometry for the coronal field. Furthermore, our simulations accurately preserve the key constraint of magnetic helicity. We find that even though small-scale stress is injected randomly throughout the corona, the net result of "stochastic" coronal reconnection is a coherent stretching of the lowest-lying field lines. This highly counter-intuitive demonstration of self-organization - magnetic stress builds up locally rather than spreading out to a minimum energy state - is the fundamental mechanism responsible for the Sun's magnetic explosions and is likely to be a mechanism that is ubiquitous throughout space and laboratory plasmas. This work was supported in part by the NASA LWS and SR Programs.

Passive scalar entrainment and mixing in a forced, spatially-developing mixing layer

NASA Technical Reports Server (NTRS)

Lowery, P. S.; Reynolds, W. C.; Mansour, N. N.

1987-01-01

Numerical simulations are performed for the forced, spatially-developing plane mixing layer in two and three dimensions. Transport of a passive scalar field is included in the computation. This, together with the allowance for spatial development in the simulations, affords the opportunity for study of the asymmetric entrainment of irrotational fluid into the layer. The inclusion of a passive scalar field provides a means for simulating the effect of this entrainment asymmetry on the generation of 'products' from a 'fast' chemical reaction. Further, the three-dimensional simulations provide useful insight into the effect of streamwise structures on these entrainment and 'fast' reaction processes. Results from a two-dimensional simulation indicate 1.22 parts high-speed fluid are entrained for every one part low-speed fluid. Inclusion of streamwise vortices at the inlet plane of a three-dimensional simulation indicate a further increase in asymmetric entrainment - 1.44:1. Results from a final three-dimensional simulation are presented. In this case, a random velocity perturbation is imposed at the inlet plane. The results indicate the 'natural' development of the large spanwise structures characteristic of the mixing layer.

The effect of electronically steering a phased array ultrasound transducer on near-field tissue heating.

PubMed

Payne, Allison; Vyas, Urvi; Todd, Nick; de Bever, Joshua; Christensen, Douglas A; Parker, Dennis L

2011-09-01

This study presents the results obtained from both simulation and experimental techniques that show the effect of mechanically or electronically steering a phased array transducer on proximal tissue heating. The thermal response of a nine-position raster and a 16-mm diameter circle scanning trajectory executed through both electronic and mechanical scanning was evaluated in computer simulations and experimentally in a homogeneous tissue-mimicking phantom. Simulations were performed using power deposition maps obtained from the hybrid angular spectrum (HAS) method and applying a finite-difference approximation of the Pennes' bioheat transfer equation for the experimentally used transducer and also for a fully sampled transducer to demonstrate the effect of acoustic window, ultrasound beam overlap and grating lobe clutter on near-field heating. Both simulation and experimental results show that electronically steering the ultrasound beam for the two trajectories using the 256-element phased array significantly increases the thermal dose deposited in the near-field tissues when compared with the same treatment executed through mechanical steering only. In addition, the individual contributions of both beam overlap and grating lobe clutter to the near-field thermal effects were determined through comparing the simulated ultrasound beam patterns and resulting temperature fields from mechanically and electronically steered trajectories using the 256-randomized element phased array transducer to an electronically steered trajectory using a fully sampled transducer with 40 401 phase-adjusted sample points. Three distinctly different three distinctly different transducers were simulated to analyze the tradeoffs of selected transducer design parameters on near-field heating. Careful consideration of design tradeoffs and accurate patient treatment planning combined with thorough monitoring of the near-field tissue temperature will help to ensure patient safety during an MRgHIFU treatment.

Evolution of the magnetorotational instability on initially tangled magnetic fields

NASA Astrophysics Data System (ADS)

Bhat, Pallavi; Ebrahimi, Fatima; Blackman, Eric G.; Subramanian, Kandaswamy

2017-12-01

The initial magnetic field of previous magnetorotational instability (MRI) simulations has always included a significant system-scale component, even if stochastic. However, it is of conceptual and practical interest to assess whether the MRI can grow when the initial field is turbulent. The ubiquitous presence of turbulent or random flows in astrophysical plasmas generically leads to a small-scale dynamo (SSD), which would provide initial seed turbulent velocity and magnetic fields in the plasma that becomes an accretion disc. Can the MRI grow from these more realistic initial conditions? To address this, we supply a standard shearing box with isotropically forced SSD generated magnetic and velocity fields as initial conditions and remove the forcing. We find that if the initially supplied fields are too weak or too incoherent, they decay from the initial turbulent cascade faster than they can grow via the MRI. When the initially supplied fields are sufficient to allow MRI growth and sustenance, the saturated stresses, large-scale fields and power spectra match those of the standard zero net flux MRI simulation with an initial large-scale vertical field.

Full Wave Analysis of RF Signal Attenuation in a Lossy Cave using a High Order Time Domain Vector Finite Element Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pingenot, J; Rieben, R; White, D

2004-12-06

We present a computational study of signal propagation and attenuation of a 200 MHz dipole antenna in a cave environment. The cave is modeled as a straight and lossy random rough wall. To simulate a broad frequency band, the full wave Maxwell equations are solved directly in the time domain via a high order vector finite element discretization using the massively parallel CEM code EMSolve. The simulation is performed for a series of random meshes in order to generate statistical data for the propagation and attenuation properties of the cave environment. Results for the power spectral density and phase ofmore » the electric field vector components are presented and discussed.« less

Digital Sound Encryption with Logistic Map and Number Theoretic Transform

NASA Astrophysics Data System (ADS)

Satria, Yudi; Gabe Rizky, P. H.; Suryadi, MT

2018-03-01

Digital sound security has limits on encrypting in Frequency Domain. Number Theoretic Transform based on field (GF 2521 – 1) improve and solve that problem. The algorithm for this sound encryption is based on combination of Chaos function and Number Theoretic Transform. The Chaos function that used in this paper is Logistic Map. The trials and the simulations are conducted by using 5 different digital sound files data tester in Wave File Extension Format and simulated at least 100 times each. The key stream resulted is random with verified by 15 NIST’s randomness test. The key space formed is very big which more than 10469. The processing speed of algorithm for encryption is slightly affected by Number Theoretic Transform.

Statistical mechanics of a cat's cradle

NASA Astrophysics Data System (ADS)

Shen, Tongye; Wolynes, Peter G.

2006-11-01

It is believed that, much like a cat's cradle, the cytoskeleton can be thought of as a network of strings under tension. We show that both regular and random bond-disordered networks having bonds that buckle upon compression exhibit a variety of phase transitions as a function of temperature and extension. The results of self-consistent phonon calculations for the regular networks agree very well with computer simulations at finite temperature. The analytic theory also yields a rigidity onset (mechanical percolation) and the fraction of extended bonds for random networks. There is very good agreement with the simulations by Delaney et al (2005 Europhys. Lett. 72 990). The mean field theory reveals a nontranslationally invariant phase with self-generated heterogeneity of tautness, representing 'antiferroelasticity'.

Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible?

PubMed

Knapp, B; Frantal, S; Cibena, M; Schreiner, W; Bauer, P

2011-08-01

Molecular dynamics is a commonly used technique in computational biology. One key issue of each molecular dynamics simulation is: When does this simulation reach equilibrium state? A widely used way to determine this is the visual and intuitive inspection of root mean square deviation (RMSD) plots of the simulation. Although this technique has been criticized several times, it is still often used. Therefore, we present a study proving that this method is not reliable at all. We conducted a survey with participants from the field in which we illustrated different RMSD plots to scientists in the field of molecular dynamics. These plots were randomized and repeated, using a statistical model and different variants of the plots. We show that there is no mutual consent about the point of equilibrium. The decisions are severely biased by different parameters. Therefore, we conclude that scientists should not discuss the equilibration of a molecular dynamics simulation on the basis of a RMSD plot.

Signatures Of Coronal Heating Driven By Footpoint Shuffling: Closed and Open Structures.

NASA Astrophysics Data System (ADS)

Velli, M. C. M.; Rappazzo, A. F.; Dahlburg, R. B.; Einaudi, G.; Ugarte-Urra, I.

2017-12-01

We have previously described the characteristic state of the confined coronal magnetic field as a special case of magnetically dominated magnetohydrodynamic (MHD) turbulence, where the free energy in the transverse magnetic field is continuously cascaded to small scales, even though the overall kinetic energy is small. This coronal turbulence problem is defined by the photospheric boundary conditions: here we discuss recent numerical simulations of the fully compressible 3D MHD equations using the HYPERION code. Loops are forced at their footpoints by random photospheric motions, energizing the field to a state with continuous formation and dissipation of field-aligned current sheets: energy is deposited at small scales where heating occurs. Only a fraction of the coronal mass and volume gets heated at any time. Temperature and density are highly structured at scales that, in the solar corona, remain observationally unresolved: the plasma of simulated loops is multithermal, where highly dynamical hotter and cooler plasma strands are scattered throughout the loop at sub-observational scales. We will also compare Reduced MHD simulations with fully compressible simulations and photospheric forcings with different time-scales compared to the Alfv'en transit time. Finally, we will discuss the differences between the closed field and open field (solar wind) turbulence heating problem, leading to observational consequences that may be amenable to Parker Solar Probe and Solar Orbiter.

A software system for the simulation of chest lesions

NASA Astrophysics Data System (ADS)

Ryan, John T.; McEntee, Mark; Barrett, Saoirse; Evanoff, Michael; Manning, David; Brennan, Patrick

2007-03-01

We report on the development of a novel software tool for the simulation of chest lesions. This software tool was developed for use in our study to attain optimal ambient lighting conditions for chest radiology. This study involved 61 consultant radiologists from the American Board of Radiology. Because of its success, we intend to use the same tool for future studies. The software has two main functions: the simulation of lesions and retrieval of information for ROC (Receiver Operating Characteristic) and JAFROC (Jack-Knife Free Response ROC) analysis. The simulation layer operates by randomly selecting an image from a bank of reportedly normal chest x-rays. A random location is then generated for each lesion, which is checked against a reference lung-map. If the location is within the lung fields, as derived from the lung-map, a lesion is superimposed. Lesions are also randomly selected from a bank of manually created chest lesion images. A blending algorithm determines which are the best intensity levels for the lesion to sit naturally within the chest x-ray. The same software was used to run a study for all 61 radiologists. A sequence of images is displayed in random order. Half of these images had simulated lesions, ranging from subtle to obvious, and half of the images were normal. The operator then selects locations where he/she thinks lesions exist and grades the lesion accordingly. We have found that this software was very effective in this study and intend to use the same principles for future studies.

Mirror Instability in the Turbulent Solar Wind

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hellinger, Petr; Landi, Simone; Verdini, Andrea

2017-04-01

The relationship between a decaying strong turbulence and the mirror instability in a slowly expanding plasma is investigated using two-dimensional hybrid expanding box simulations. We impose an initial ambient magnetic field perpendicular to the simulation box, and we start with a spectrum of large-scale, linearly polarized, random-phase Alfvénic fluctuations that have energy equipartition between kinetic and magnetic fluctuations and a vanishing correlation between the two fields. A turbulent cascade rapidly develops, magnetic field fluctuations exhibit a Kolmogorov-like power-law spectrum at large scales and a steeper spectrum at sub-ion scales. The imposed expansion (taking a strictly transverse ambient magnetic field) leadsmore » to the generation of an important perpendicular proton temperature anisotropy that eventually drives the mirror instability. This instability generates large-amplitude, nonpropagating, compressible, pressure-balanced magnetic structures in a form of magnetic enhancements/humps that reduce the perpendicular temperature anisotropy.« less

Effect of surrounding vasculature on intravoxel BOLD signal.

PubMed

Chen, Zikuan; Caprihan, Arvind; Calhoun, Vince

2010-04-01

The nonlocal influence from distant magnetization will affect the magnetic field at a voxel in question. Existing reports on BOLD simulation only consider vasculature inside a single voxel, thus omitting the contribution from the surrounding regions. In this article, the authors study the effect of the surrounding vasculature on the magnetic field and the BOLD signal at a cortical voxel by numerical simulation. A cortical voxel is generated as a cubic bin filled with randomly networked capillary vessels. First, the authors generate a cortical voxel with a random vessel network and embed it in a greater voxel by filling its surrounding region with vasculatures by different strategies. Next, they calculate the blood-susceptibility-induced magnetic field (BOLD field) at the voxel of interest (VOI) by a Fourier transform technique for different surrounding scenarios and varying surrounding extent. The BOLD field inhomogeneity is described by a radial distribution with a collection of cubic shell masks. The surrounding extent is defined by a collection of concentric cubes, which encase the VOI. Given a BOLD field in the presence of surrounding vasculature, they calculate BOLD signals by intravoxel dephasing. The influence from the surroundings on the BOLD field at a voxel in question mainly happens at the boundary. The most influence to the BOLD signal is from the inner surroundings. For a 160 x 160 x 160 microm3 voxel embedded in a 480 x 480 x 480 microm3 greater region, the surroundings could disturb the magnetic field by an amount in the range of [-0.002, 0.010] ppmT and could change the BOLD signal ratio in the range of [2.5%, 10%]. (These results were generated from the setting of delta(chi b)B0 = 3 ppmT, capillary = {2.5,6,9} microm, and relaxation time = 60 ms). The surrounding vasculature will impose a magnetic field disturbance at the voxel in question due to the nonlocal influence of magnetization. Simulation results show that the surrounding vasculature significantly alters the magnetic field (up to 0.01 ppmT) and BOLD signal (typically no more than 10%) at the central voxel and thus should be considered in accurate BOLD modeling.

Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes

DOE PAGES

Osborn, Sarah; Zulian, Patrick; Benson, Thomas; ...

2018-01-30

This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on anmore » embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.« less

Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Osborn, Sarah; Zulian, Patrick; Benson, Thomas

This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on anmore » embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.« less

Galaxy Alignments: Theory, Modelling & Simulations

NASA Astrophysics Data System (ADS)

Kiessling, Alina; Cacciato, Marcello; Joachimi, Benjamin; Kirk, Donnacha; Kitching, Thomas D.; Leonard, Adrienne; Mandelbaum, Rachel; Schäfer, Björn Malte; Sifón, Cristóbal; Brown, Michael L.; Rassat, Anais

2015-11-01

The shapes of galaxies are not randomly oriented on the sky. During the galaxy formation and evolution process, environment has a strong influence, as tidal gravitational fields in the large-scale structure tend to align nearby galaxies. Additionally, events such as galaxy mergers affect the relative alignments of both the shapes and angular momenta of galaxies throughout their history. These "intrinsic galaxy alignments" are known to exist, but are still poorly understood. This review will offer a pedagogical introduction to the current theories that describe intrinsic galaxy alignments, including the apparent difference in intrinsic alignment between early- and late-type galaxies and the latest efforts to model them analytically. It will then describe the ongoing efforts to simulate intrinsic alignments using both N-body and hydrodynamic simulations. Due to the relative youth of this field, there is still much to be done to understand intrinsic galaxy alignments and this review summarises the current state of the field, providing a solid basis for future work.

Influence of changes in initial conditions for the simulation of dynamic systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kotyrba, Martin

2015-03-10

Chaos theory is a field of study in mathematics, with applications in several disciplines including meteorology, sociology, physics, engineering, economics, biology, and philosophy. Chaos theory studies the behavior of dynamical systems that are highly sensitive to initial conditions—a paradigm popularly referred to as the butterfly effect. Small differences in initial conditions field widely diverging outcomes for such dynamical systems, rendering long-term prediction impossible in general. This happens even though these systems are deterministic, meaning that their future behavior is fully determined by their initial conditions, with no random elements involved. In this paperinfluence of changes in initial conditions will bemore » presented for the simulation of Lorenz system.« less

A Markov model for the temporal dynamics of balanced random networks of finite size

PubMed Central

Lagzi, Fereshteh; Rotter, Stefan

2014-01-01

The balanced state of recurrent networks of excitatory and inhibitory spiking neurons is characterized by fluctuations of population activity about an attractive fixed point. Numerical simulations show that these dynamics are essentially nonlinear, and the intrinsic noise (self-generated fluctuations) in networks of finite size is state-dependent. Therefore, stochastic differential equations with additive noise of fixed amplitude cannot provide an adequate description of the stochastic dynamics. The noise model should, rather, result from a self-consistent description of the network dynamics. Here, we consider a two-state Markovian neuron model, where spikes correspond to transitions from the active state to the refractory state. Excitatory and inhibitory input to this neuron affects the transition rates between the two states. The corresponding nonlinear dependencies can be identified directly from numerical simulations of networks of leaky integrate-and-fire neurons, discretized at a time resolution in the sub-millisecond range. Deterministic mean-field equations, and a noise component that depends on the dynamic state of the network, are obtained from this model. The resulting stochastic model reflects the behavior observed in numerical simulations quite well, irrespective of the size of the network. In particular, a strong temporal correlation between the two populations, a hallmark of the balanced state in random recurrent networks, are well represented by our model. Numerical simulations of such networks show that a log-normal distribution of short-term spike counts is a property of balanced random networks with fixed in-degree that has not been considered before, and our model shares this statistical property. Furthermore, the reconstruction of the flow from simulated time series suggests that the mean-field dynamics of finite-size networks are essentially of Wilson-Cowan type. We expect that this novel nonlinear stochastic model of the interaction between neuronal populations also opens new doors to analyze the joint dynamics of multiple interacting networks. PMID:25520644

Pulsed field gradients in simulations of one- and two-dimensional NMR spectra.

PubMed

Meresi, G H; Cuperlovic, M; Palke, W E; Gerig, J T

1999-03-01

A method for the inclusion of the effects of z-axis pulsed field gradients in computer simulations of an arbitrary pulsed NMR experiment with spin (1/2) nuclei is described. Recognizing that the phase acquired by a coherence following the application of a z-axis pulsed field gradient bears a fixed relation to its order and the spatial position of the spins in the sample tube, the sample is regarded as a collection of volume elements, each phase-encoded by a characteristic, spatially dependent precession frequency. The evolution of the sample's density matrix is thus obtained by computing the evolution of the density matrix for each volume element. Following the last gradient pulse, these density matrices are combined to form a composite density matrix which evolves through the rest of the experiment to yield the observable signal. This approach is implemented in a program which includes capabilities for rigorous inclusion of spin relaxation by dipole-dipole, chemical shift anisotropy, and random field mechanisms, plus the effects of arbitrary RF fields. Mathematical procedures for accelerating these calculations are described. The approach is illustrated by simulations of representative one- and two-dimensional NMR experiments. Copyright 1999 Academic Press.

Meta-analysis of correlations revisited: attempted replication and extension of Field's (2001) simulation studies.

PubMed

Hafdahl, Adam R; Williams, Michelle A

2009-03-01

In 2 Monte Carlo studies of fixed- and random-effects meta-analysis for correlations, A. P. Field (2001) ostensibly evaluated Hedges-Olkin-Vevea Fisher-z and Schmidt-Hunter Pearson-r estimators and tests in 120 conditions. Some authors have cited those results as evidence not to meta-analyze Fisher-z correlations, especially with heterogeneous correlation parameters. The present attempt to replicate Field's simulations included comparisons with analytic values as well as results for efficiency and confidence-interval coverage. Field's results under homogeneity were mostly replicable, but those under heterogeneity were not: The latter exhibited up to over .17 more bias than ours and, for tests of the mean correlation and homogeneity, respectively, nonnull rejection rates up to .60 lower and .65 higher. Changes to Field's observations and conclusions are recommended, and practical guidance is offered regarding simulation evidence and choices among methods. Most cautions about poor performance of Fisher-z methods are largely unfounded, especially with a more appropriate z-to-r transformation. The Appendix gives a computer program for obtaining Pearson-r moments from a normal Fisher-z distribution, which is used to demonstrate distortion due to direct z-to-r transformation of a mean Fisher-z correlation.

Unveiling the Role of the Magnetic Field at the Smallest Scales of Star Formation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hull, Charles L. H.; Mocz, Philip; Burkhart, Blakesley

We report Atacama Large Millimeter/submillimeter Array (ALMA) observations of polarized dust emission from the protostellar source Ser-emb 8 at a linear resolution of 140 au. Assuming models of dust-grain alignment hold, the observed polarization pattern gives a projected view of the magnetic field structure in this source. Contrary to expectations based on models of strongly magnetized star formation, the magnetic field in Ser-emb 8 does not exhibit an hourglass morphology. Combining the new ALMA data with previous observational studies, we can connect magnetic field structure from protostellar core (∼80,000 au) to disk (∼100 au) scales. We compare our observations withmore » four magnetohydrodynamic gravo-turbulence simulations made with the AREPO code that have initial conditions ranging from super-Alfvénic (weakly magnetized) to sub-Alfvénic (strongly magnetized). These simulations achieve the spatial dynamic range necessary to resolve the collapse of protostars from the parsec scale of star-forming clouds down to the ∼100 au scale probed by ALMA. Only in the very strongly magnetized simulation do we see both the preservation of the field direction from cloud to disk scales and an hourglass-shaped field at <1000 au scales. We conduct an analysis of the relative orientation of the magnetic field and the density structure in both the Ser-emb 8 ALMA observations and the synthetic observations of the four AREPO simulations. We conclude that the Ser-emb 8 data are most similar to the weakly magnetized simulations, which exhibit random alignment, in contrast to the strongly magnetized simulation, where the magnetic field plays a role in shaping the density structure in the source. In the weak-field case, it is turbulence—not the magnetic field—that shapes the material that forms the protostar, highlighting the dominant role that turbulence can play across many orders of magnitude in spatial scale.« less

Portal imaging based definition of the planning target volume during pelvic irradiation for gynecological malignancies.

PubMed

Mock, U; Dieckmann, K; Wolff, U; Knocke, T H; Pötter, R

1999-08-01

Geometrical accuracy in patient positioning can vary substantially during external radiotherapy. This study estimated the set-up accuracy during pelvic irradiation for gynecological malignancies for determination of safety margins (planning target volume, PTV). Based on electronic portal imaging devices (EPID), 25 patients undergoing 4-field pelvic irradiation for gynecological malignancies were analyzed with regard to set-up accuracy during the treatment course. Regularly performed EPID images were used in order to systematically assess the systematic and random component of set-up displacements. Anatomical matching of verification and simulation images was followed by measuring corresponding distances between the central axis and anatomical features. Data analysis of set-up errors referred to the x-, y-,and z-axes. Additionally, cumulative frequencies were evaluated. A total of 50 simulation films and 313 verification images were analyzed. For the anterior-posterior (AP) beam direction mean deviations along the x- and z-axes were 1.5 mm and -1.9 mm, respectively. Moreover, random errors of 4.8 mm (x-axis) and 3.0 mm (z-axis) were determined. Concerning the latero-lateral treatment fields, the systematic errors along the two axes were calculated to 2.9 mm (y-axis) and -2.0 mm (z-axis) and random errors of 3.8 mm and 3.5 mm were found, respectively. The cumulative frequency of misalignments < or =5 mm showed values of 75% (AP fields) and 72% (latero-lateral fields). With regard to cumulative frequencies < or =10 mm quantification revealed values of 97% for both beam directions. During external pelvic irradiation therapy for gynecological malignancies, EPID images on a regular basis revealed acceptable set-up inaccuracies. Safety margins (PTV) of 1 cm appear to be sufficient, accounting for more than 95% of all deviations.

Studies on thermal decomposition behaviors of polypropylene using molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Huang, Jinbao; He, Chao; Tong, Hong; Pan, Guiying

2017-11-01

Polypropylene (PP) is one of the main components of waste plastics. In order to understand the mechanism of PP thermal decomposition, the pyrolysis behaviour of PP has been simulated from 300 to 1000 K in periodic boundary conditions by molecular dynamic method, based on AMBER force field. The simulation results show that the pyrolysis process of PP can mostly be divided into three stages: low temperature pyrolysis stage, intermediate temperature stage and high temperature pyrolysis stage. PP pyrolysis is typical of random main-chain scission, and the possible formation mechanism of major pyrolysis products was analyzed.

Remote Numerical Simulations of the Interaction of High Velocity Clouds with Random Magnetic Fields

NASA Astrophysics Data System (ADS)

Santillan, Alfredo; Hernandez--Cervantes, Liliana; Gonzalez--Ponce, Alejandro; Kim, Jongsoo

The numerical simulations associated with the interaction of High Velocity Clouds (HVC) with the Magnetized Galactic Interstellar Medium (ISM) are a powerful tool to describe the evolution of the interaction of these objects in our Galaxy. In this work we present a new project referred to as Theoretical Virtual i Observatories. It is oriented toward to perform numerical simulations in real time through a Web page. This is a powerful astrophysical computational tool that consists of an intuitive graphical user interface (GUI) and a database produced by numerical calculations. In this Website the user can make use of the existing numerical simulations from the database or run a new simulation introducing initial conditions such as temperatures, densities, velocities, and magnetic field intensities for both the ISM and HVC. The prototype is programmed using Linux, Apache, MySQL, and PHP (LAMP), based on the open source philosophy. All simulations were performed with the MHD code ZEUS-3D, which solves the ideal MHD equations by finite differences on a fixed Eulerian mesh. Finally, we present typical results that can be obtained with this tool.

Numerical simulation of a helical shape electric arc in the external axial magnetic field

NASA Astrophysics Data System (ADS)

Urusov, R. M.; Urusova, I. R.

2016-10-01

Within the frameworks of non-stationary three-dimensional mathematical model, in approximation of a partial local thermodynamic equilibrium, a numerical calculation was made of characteristics of DC electric arc burning in a cylindrical channel in the uniform external axial magnetic field. The method of numerical simulation of the arc of helical shape in a uniform external axial magnetic field was proposed. This method consists in that that in the computational algorithm, a "scheme" analog of fluctuations for electrons temperature is supplemented. The "scheme" analogue of fluctuations increases a weak numerical asymmetry of electrons temperature distribution, which occurs randomly in the course of computing. This asymmetry can be "picked up" by the external magnetic field that continues to increase up to a certain value, which is sufficient for the formation of helical structure of the arc column. In the absence of fluctuations in the computational algorithm, the arc column in the external axial magnetic field maintains cylindrical axial symmetry, and a helical form of the arc is not observed.

Tortuosity of lightning return stroke channels

NASA Technical Reports Server (NTRS)

Levine, D. M.; Gilson, B.

1984-01-01

Data obtained from photographs of lightning are presented on the tortuosity of return stroke channels. The data were obtained by making piecewise linear fits to the channels, and recording the cartesian coordinates of the ends of each linear segment. The mean change between ends of the segments was nearly zero in the horizontal direction and was about eight meters in the vertical direction. Histograms of these changes are presented. These data were used to create model lightning channels and to predict the electric fields radiated during return strokes. This was done using a computer generated random walk in which linear segments were placed end-to-end to form a piecewise linear representation of the channel. The computer selected random numbers for the ends of the segments assuming a normal distribution with the measured statistics. Once the channels were simulated, the electric fields radiated during a return stroke were predicted using a transmission line model on each segment. It was found that realistic channels are obtained with this procedure, but only if the model includes two scales of tortuosity: fine scale irregularities corresponding to the local channel tortuosity which are superimposed on large scale horizontal drifts. The two scales of tortuosity are also necessary to obtain agreement between the electric fields computed mathematically from the simulated channels and the electric fields radiated from real return strokes. Without large scale drifts, the computed electric fields do not have the undulations characteristics of the data.

Assessing the significance of pedobarographic signals using random field theory.

PubMed

Pataky, Todd C

2008-08-07

Traditional pedobarographic statistical analyses are conducted over discrete regions. Recent studies have demonstrated that regionalization can corrupt pedobarographic field data through conflation when arbitrary dividing lines inappropriately delineate smooth field processes. An alternative is to register images such that homologous structures optimally overlap and then conduct statistical tests at each pixel to generate statistical parametric maps (SPMs). The significance of SPM processes may be assessed within the framework of random field theory (RFT). RFT is ideally suited to pedobarographic image analysis because its fundamental data unit is a lattice sampling of a smooth and continuous spatial field. To correct for the vast number of multiple comparisons inherent in such data, recent pedobarographic studies have employed a Bonferroni correction to retain a constant family-wise error rate. This approach unfortunately neglects the spatial correlation of neighbouring pixels, so provides an overly conservative (albeit valid) statistical threshold. RFT generally relaxes the threshold depending on field smoothness and on the geometry of the search area, but it also provides a framework for assigning p values to suprathreshold clusters based on their spatial extent. The current paper provides an overview of basic RFT concepts and uses simulated and experimental data to validate both RFT-relevant field smoothness estimations and RFT predictions regarding the topological characteristics of random pedobarographic fields. Finally, previously published experimental data are re-analysed using RFT inference procedures to demonstrate how RFT yields easily understandable statistical results that may be incorporated into routine clinical and laboratory analyses.

Plasmon response evaluation based on image-derived arbitrary nanostructures.

PubMed

Trautmann, S; Richard-Lacroix, M; Dathe, A; Schneidewind, H; Dellith, J; Fritzsche, W; Deckert, V

2018-05-31

The optical response of realistic 3D plasmonic substrates composed of randomly shaped particles of different size and interparticle distance distributions in addition to nanometer scale surface roughness is intrinsically challenging to simulate due to computational limitations. Here, we present a Finite Element Method (FEM)-based methodology that bridges in-depth theoretical investigations and experimental optical response of plasmonic substrates composed of such silver nanoparticles. Parametrized scanning electron microscopy (SEM) images of surface enhanced Raman spectroscopy (SERS) active substrate and tip-enhanced Raman spectroscopy (TERS) probes are used to simulate the far-and near-field optical response. Far-field calculations are consistent with experimental dark field spectra and charge distribution images reveal for the first time in arbitrary structures the contributions of interparticle hybridized modes such as sub-radiant and super-radiant modes that also locally organize as basic units for Fano resonances. Near-field simulations expose the spatial position-dependent impact of hybridization on field enhancement. Simulations of representative sections of TERS tips are shown to exhibit the same unexpected coupling modes. Near-field simulations suggest that these modes can contribute up to 50% of the amplitude of the plasmon resonance at the tip apex but, interestingly, have a small effect on its frequency in the visible range. The band position is shown to be extremely sensitive to particle nanoscale roughness, highlighting the necessity to preserve detailed information at both the largest and the smallest scales. To the best of our knowledge, no currently available method enables reaching such a detailed description of large scale realistic 3D plasmonic systems.

Probabilistic finite elements for transient analysis in nonlinear continua

NASA Technical Reports Server (NTRS)

Liu, W. K.; Belytschko, T.; Mani, A.

1985-01-01

The probabilistic finite element method (PFEM), which is a combination of finite element methods and second-moment analysis, is formulated for linear and nonlinear continua with inhomogeneous random fields. Analogous to the discretization of the displacement field in finite element methods, the random field is also discretized. The formulation is simplified by transforming the correlated variables to a set of uncorrelated variables through an eigenvalue orthogonalization. Furthermore, it is shown that a reduced set of the uncorrelated variables is sufficient for the second-moment analysis. Based on the linear formulation of the PFEM, the method is then extended to transient analysis in nonlinear continua. The accuracy and efficiency of the method is demonstrated by application to a one-dimensional, elastic/plastic wave propagation problem. The moments calculated compare favorably with those obtained by Monte Carlo simulation. Also, the procedure is amenable to implementation in deterministic FEM based computer programs.

Experimental vibroacoustic testing of plane panels using synthesized random pressure fields.

PubMed

Robin, Olivier; Berry, Alain; Moreau, Stéphane

2014-06-01

The experimental reproduction of random pressure fields on a plane panel and corresponding induced vibrations is studied. An open-loop reproduction strategy is proposed that uses the synthetic array concept, for which a small array element is moved to create a large array by post-processing. Three possible approaches are suggested to define the complex amplitudes to be imposed to the reproduction sources distributed on a virtual plane facing the panel to be tested. Using a single acoustic monopole, a scanning laser vibrometer and a baffled simply supported aluminum panel, experimental vibroacoustic indicators such as the Transmission Loss for Diffuse Acoustic Field, high-speed subsonic and supersonic Turbulent Boundary Layer excitations are obtained. Comparisons with simulation results obtained using a commercial software show that the Transmission Loss estimation is possible under both excitations. Moreover and as a complement to frequency domain indicators, the vibroacoustic behavior of the panel can be studied in the wave number domain.

Effects of force fields on the conformational and dynamic properties of amyloid β(1-40) dimer explored by replica exchange molecular dynamics simulations.

PubMed

Watts, Charles R; Gregory, Andrew; Frisbie, Cole; Lovas, Sándor

2018-03-01

The conformational space and structural ensembles of amyloid beta (Aβ) peptides and their oligomers in solution are inherently disordered and proven to be challenging to study. Optimum force field selection for molecular dynamics (MD) simulations and the biophysical relevance of results are still unknown. We compared the conformational space of the Aβ(1-40) dimers by 300 ns replica exchange MD simulations at physiological temperature (310 K) using: the AMBER-ff99sb-ILDN, AMBER-ff99sb*-ILDN, AMBER-ff99sb-NMR, and CHARMM22* force fields. Statistical comparisons of simulation results to experimental data and previously published simulations utilizing the CHARMM22* and CHARMM36 force fields were performed. All force fields yield sampled ensembles of conformations with collision cross sectional areas for the dimer that are statistically significantly larger than experimental results. All force fields, with the exception of AMBER-ff99sb-ILDN (8.8 ± 6.4%) and CHARMM36 (2.7 ± 4.2%), tend to overestimate the α-helical content compared to experimental CD (5.3 ± 5.2%). Using the AMBER-ff99sb-NMR force field resulted in the greatest degree of variance (41.3 ± 12.9%). Except for the AMBER-ff99sb-NMR force field, the others tended to under estimate the expected amount of β-sheet and over estimate the amount of turn/bend/random coil conformations. All force fields, with the exception AMBER-ff99sb-NMR, reproduce a theoretically expected β-sheet-turn-β-sheet conformational motif, however, only the CHARMM22* and CHARMM36 force fields yield results compatible with collapse of the central and C-terminal hydrophobic cores from residues 17-21 and 30-36. Although analyses of essential subspace sampling showed only minor variations between force fields, secondary structures of lowest energy conformers are different. © 2017 Wiley Periodicals, Inc.

An efficient distribution method for nonlinear transport problems in highly heterogeneous stochastic porous media

NASA Astrophysics Data System (ADS)

Ibrahima, Fayadhoi; Meyer, Daniel; Tchelepi, Hamdi

2016-04-01

Because geophysical data are inexorably sparse and incomplete, stochastic treatments of simulated responses are crucial to explore possible scenarios and assess risks in subsurface problems. In particular, nonlinear two-phase flows in porous media are essential, yet challenging, in reservoir simulation and hydrology. Adding highly heterogeneous and uncertain input, such as the permeability and porosity fields, transforms the estimation of the flow response into a tough stochastic problem for which computationally expensive Monte Carlo (MC) simulations remain the preferred option.We propose an alternative approach to evaluate the probability distribution of the (water) saturation for the stochastic Buckley-Leverett problem when the probability distributions of the permeability and porosity fields are available. We give a computationally efficient and numerically accurate method to estimate the one-point probability density (PDF) and cumulative distribution functions (CDF) of the (water) saturation. The distribution method draws inspiration from a Lagrangian approach of the stochastic transport problem and expresses the saturation PDF and CDF essentially in terms of a deterministic mapping and the distribution and statistics of scalar random fields. In a large class of applications these random fields can be estimated at low computational costs (few MC runs), thus making the distribution method attractive. Even though the method relies on a key assumption of fixed streamlines, we show that it performs well for high input variances, which is the case of interest. Once the saturation distribution is determined, any one-point statistics thereof can be obtained, especially the saturation average and standard deviation. Moreover, the probability of rare events and saturation quantiles (e.g. P10, P50 and P90) can be efficiently derived from the distribution method. These statistics can then be used for risk assessment, as well as data assimilation and uncertainty reduction in the prior knowledge of input distributions. We provide various examples and comparisons with MC simulations to illustrate the performance of the method.

Determination of the Spatial Distribution in Hydraulic Conductivity Using Genetic Algorithm Optimization

NASA Astrophysics Data System (ADS)

Aksoy, A.; Lee, J. H.; Kitanidis, P. K.

2016-12-01

Heterogeneity in hydraulic conductivity (K) impacts the transport and fate of contaminants in subsurface as well as design and operation of managed aquifer recharge (MAR) systems. Recently, improvements in computational resources and availability of big data through electrical resistivity tomography (ERT) and remote sensing have provided opportunities to better characterize the subsurface. Yet, there is need to improve prediction and evaluation methods in order to obtain information from field measurements for better field characterization. In this study, genetic algorithm optimization, which has been widely used in optimal aquifer remediation designs, was used to determine the spatial distribution of K. A hypothetical 2 km by 2 km aquifer was considered. A genetic algorithm library, PGAPack, was linked with a fast Fourier transform based random field generator as well as a groundwater flow and contaminant transport simulation model (BIO2D-KE). The objective of the optimization model was to minimize the total squared error between measured and predicted field values. It was assumed measured K values were available through ERT. Performance of genetic algorithm in predicting the distribution of K was tested for different cases. In the first one, it was assumed that observed K values were evaluated using the random field generator only as the forward model. In the second case, as well as K-values obtained through ERT, measured head values were incorporated into evaluation in which BIO2D-KE and random field generator were used as the forward models. Lastly, tracer concentrations were used as additional information in the optimization model. Initial results indicated enhanced performance when random field generator and BIO2D-KE are used in combination in predicting the spatial distribution in K.

Identification of Langmuir wave turbulence-supercontinuum transition by application of von Neumann entropy

NASA Astrophysics Data System (ADS)

Kawamori, Eiichirou

2017-09-01

A transition from Langmuir wave turbulence (LWT) to coherent Langmuir wave supercontinuum (LWSC) is identified in one-dimensional particle-in-cell simulations as the emergence of a broad frequency band showing significant temporal coherence of a wave field accompanied by a decrease in the von Neumann entropy of classical wave fields. The concept of the von Neumann entropy is utilized for evaluation of the phase-randomizing degree of the classical wave fields, together with introduction of the density matrix of the wave fields. The transition from LWT to LWSC takes place when the energy per one plasmon (one wave quantum) exceeds a certain threshold. The coherent nature, which Langmuir wave systems acquire through the transition, is created by four wave mixings of the plasmons. The emergence of temporal coherence and the decrease in the phase randomization are considered as the development of long-range order and spontaneous symmetry breaking, respectively, indicating that the LWT-LWSC transition is a second order phase transition phenomenon.

Numerical Generation of Dense Plume Fingers in Unsaturated Homogeneous Porous Media

NASA Astrophysics Data System (ADS)

Cremer, C.; Graf, T.

2012-04-01

In nature, the migration of dense plumes typically results in the formation of vertical plume fingers. Flow direction in fingers is downwards, which is counterbalanced by upwards flow of less dense fluid between fingers. In heterogeneous media, heterogeneity itself is known to trigger the formation of fingers. In homogeneous media, however, fingers are also created even if all grains had the same diameter. The reason is that pore-scale heterogeneity leading to different flow velocities also exists in homogeneous media due to two effects: (i) Grains of identical size may randomly arrange differently, e.g. forming tetrahedrons, hexahedrons or octahedrons. Each arrangement creates pores of varying diameter, thus resulting in different average flow velocities. (ii) Random variations of solute concentration lead to varying buoyancy effects, thus also resulting in different velocities. As a continuation of previously made efforts to incorporate pore-scale heterogeneity into fully saturated soil such that dense fingers are realistically generated (Cremer and Graf, EGU Assembly, 2011), the current paper extends the research scope from saturated to unsaturated soil. Perturbation methods are evaluated by numerically re-simulating a laboratory-scale experiment of plume transport in homogeneous unsaturated sand (Simmons et al., Transp. Porous Media, 2002). The following 5 methods are being discussed: (i) homogeneous sand, (ii) initial perturbation of solute concentration, (iii) spatially random, time-constant perturbation of solute source, (iv) spatially and temporally random noise of simulated solute concentration, and (v) random K-field that introduces physically insignificant but numerically significant heterogeneity. Results demonstrate that, as opposed to saturated flow, perturbing the solute source will not result in plume fingering. This is because the location of the perturbed source (domain top) and the location of finger generation (groundwater surface) do not coincide. Alternatively, similar to saturated flow, applying either a random concentration noise (iv) or a random K-field (v) generates realistic plume fingering. Future work will focus on the generation mechanisms of plume finger splitting.

Sustainability of transport structures - some aspects of the nonlinear reliability assessment

NASA Astrophysics Data System (ADS)

Pukl, Radomír; Sajdlová, Tereza; Strauss, Alfred; Lehký, David; Novák, Drahomír

2017-09-01

Efficient techniques for both nonlinear numerical analysis of concrete structures and advanced stochastic simulation methods have been combined in order to offer an advanced tool for assessment of realistic behaviour, failure and safety assessment of transport structures. The utilized approach is based on randomization of the non-linear finite element analysis of the structural models. Degradation aspects such as carbonation of concrete can be accounted in order predict durability of the investigated structure and its sustainability. Results can serve as a rational basis for the performance and sustainability assessment based on advanced nonlinear computer analysis of the structures of transport infrastructure such as bridges or tunnels. In the stochastic simulation the input material parameters obtained from material tests including their randomness and uncertainty are represented as random variables or fields. Appropriate identification of material parameters is crucial for the virtual failure modelling of structures and structural elements. Inverse analysis using artificial neural networks and virtual stochastic simulations approach is applied to determine the fracture mechanical parameters of the structural material and its numerical model. Structural response, reliability and sustainability have been investigated on different types of transport structures made from various materials using the above mentioned methodology and tools.

Role of turbulence fluctuations on uncertainties of acoutic Doppler current profiler discharge measurements

USGS Publications Warehouse

Tarrab, Leticia; Garcia, Carlos M.; Cantero, Mariano I.; Oberg, Kevin

2012-01-01

This work presents a systematic analysis quantifying the role of the presence of turbulence fluctuations on uncertainties (random errors) of acoustic Doppler current profiler (ADCP) discharge measurements from moving platforms. Data sets of three-dimensional flow velocities with high temporal and spatial resolution were generated from direct numerical simulation (DNS) of turbulent open channel flow. Dimensionless functions relating parameters quantifying the uncertainty in discharge measurements due to flow turbulence (relative variance and relative maximum random error) to sampling configuration were developed from the DNS simulations and then validated with field-scale discharge measurements. The validated functions were used to evaluate the role of the presence of flow turbulence fluctuations on uncertainties in ADCP discharge measurements. The results of this work indicate that random errors due to the flow turbulence are significant when: (a) a low number of transects is used for a discharge measurement, and (b) measurements are made in shallow rivers using high boat velocity (short time for the boat to cross a flow turbulence structure).

Bouchaud-Mézard model on a random network

NASA Astrophysics Data System (ADS)

Ichinomiya, Takashi

2012-09-01

We studied the Bouchaud-Mézard (BM) model, which was introduced to explain Pareto's law in a real economy, on a random network. Using “adiabatic and independent” assumptions, we analytically obtained the stationary probability distribution function of wealth. The results show that wealth condensation, indicated by the divergence of the variance of wealth, occurs at a larger J than that obtained by the mean-field theory, where J represents the strength of interaction between agents. We compared our results with numerical simulation results and found that they were in good agreement.

Power-law exponent of the Bouchaud-Mézard model on regular random networks

NASA Astrophysics Data System (ADS)

Ichinomiya, Takashi

2013-07-01

We study the Bouchaud-Mézard model on a regular random network. By assuming adiabaticity and independency, and utilizing the generalized central limit theorem and the Tauberian theorem, we derive an equation that determines the exponent of the probability distribution function of the wealth as x→∞. The analysis shows that the exponent can be smaller than 2, while a mean-field analysis always gives the exponent as being larger than 2. The results of our analysis are shown to be in good agreement with those of the numerical simulations.

Design and implementation of the NaI(Tl)/CsI(Na) detectors output signal generator

NASA Astrophysics Data System (ADS)

Zhou, Xu; Liu, Cong-Zhan; Zhao, Jian-Ling; Zhang, Fei; Zhang, Yi-Fei; Li, Zheng-Wei; Zhang, Shuo; Li, Xu-Fang; Lu, Xue-Feng; Xu, Zhen-Ling; Lu, Fang-Jun

2014-02-01

We designed and implemented a signal generator that can simulate the output of the NaI(Tl)/CsI(Na) detectors' pre-amplifier onboard the Hard X-ray Modulation Telescope (HXMT). Using the development of the FPGA (Field Programmable Gate Array) with VHDL language and adding a random constituent, we have finally produced the double exponential random pulse signal generator. The statistical distribution of the signal amplitude is programmable. The occurrence time intervals of the adjacent signals contain negative exponential distribution statistically.

Micromagnetic Simulation of Thermal Effects in Magnetic Nanostructures

DTIC Science & Technology

2003-01-01

NiFe magnetic nano- elements are calculated. INTRODUCTION With decreasing size of magnetic nanostructures thermal effects become increasingly important...thermal field. The thermal field is assumed to be a Gaussian random process with the following statistical properties : (H,,,(t))=0 and (H,I.(t),H,.1(t...following property DI " =VE(M’’) - [VE(M"’)• t] t =0, for k =1.m (12) 186 The optimal path can be found using an iterative scheme. In each iteration step the

Modelling Geomechanical Heterogeneity of Rock Masses Using Direct and Indirect Geostatistical Conditional Simulation Methods

NASA Astrophysics Data System (ADS)

Eivazy, Hesameddin; Esmaieli, Kamran; Jean, Raynald

2017-12-01

An accurate characterization and modelling of rock mass geomechanical heterogeneity can lead to more efficient mine planning and design. Using deterministic approaches and random field methods for modelling rock mass heterogeneity is known to be limited in simulating the spatial variation and spatial pattern of the geomechanical properties. Although the applications of geostatistical techniques have demonstrated improvements in modelling the heterogeneity of geomechanical properties, geostatistical estimation methods such as Kriging result in estimates of geomechanical variables that are not fully representative of field observations. This paper reports on the development of 3D models for spatial variability of rock mass geomechanical properties using geostatistical conditional simulation method based on sequential Gaussian simulation. A methodology to simulate the heterogeneity of rock mass quality based on the rock mass rating is proposed and applied to a large open-pit mine in Canada. Using geomechanical core logging data collected from the mine site, a direct and an indirect approach were used to model the spatial variability of rock mass quality. The results of the two modelling approaches were validated against collected field data. The study aims to quantify the risks of pit slope failure and provides a measure of uncertainties in spatial variability of rock mass properties in different areas of the pit.

Drag Reduction of an Airfoil Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, Chiyu; Sun, Anzhu; Marcus, Philip

2017-11-01

We reduced the drag of a 2D airfoil by starting with a NACA-0012 airfoil and used deep learning methods. We created a database which consists of simulations of 2D external flow over randomly generated shapes. We then developed a machine learning framework for external flow field inference given input shapes. Past work which utilized machine learning in Computational Fluid Dynamics focused on estimations of specific flow parameters, but this work is novel in the inference of entire flow fields. We further showed that learned flow patterns are transferable to cases that share certain similarities. This study illustrates the prospects of deeper integration of data-based modeling into current CFD simulation frameworks for faster flow inference and more accurate flow modeling.

Perceived change in orientation from optic flow in the central visual field

NASA Technical Reports Server (NTRS)

Dyre, Brian P.; Andersen, George J.

1988-01-01

The effects of internal depth within a simulation display on perceived changes in orientation have been studied. Subjects monocularly viewed displays simulating observer motion within a volume of randomly positioned points through a window which limited the field of view to 15 deg. Changes in perceived spatial orientation were measured by changes in posture. The extent of internal depth within the display, the presence or absence of visual information specifying change in orientation, and the frequency of motion supplied by the display were examined. It was found that increased sway occurred at frequencies equal to or below 0.375 Hz when motion at these frequencies was displayed. The extent of internal depth had no effect on the perception of changing orientation.

Quantitative model of price diffusion and market friction based on trading as a mechanistic random process.

PubMed

Daniels, Marcus G; Farmer, J Doyne; Gillemot, László; Iori, Giulia; Smith, Eric

2003-03-14

We model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of markets, such as the diffusion rate of prices (which is the standard measure of financial risk) and the spread and price impact functions (which are the main determinants of transaction cost). Guided by dimensional analysis, simulation, and mean-field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process

NASA Astrophysics Data System (ADS)

Daniels, Marcus G.; Farmer, J. Doyne; Gillemot, László; Iori, Giulia; Smith, Eric

2003-03-01

We model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of markets, such as the diffusion rate of prices (which is the standard measure of financial risk) and the spread and price impact functions (which are the main determinants of transaction cost). Guided by dimensional analysis, simulation, and mean-field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

Combining numerical simulations with time-domain random walk for pathogen risk assessment in groundwater

NASA Astrophysics Data System (ADS)

Cvetkovic, V.; Molin, S.

2012-02-01

We present a methodology that combines numerical simulations of groundwater flow and advective transport in heterogeneous porous media with analytical retention models for computing the infection risk probability from pathogens in aquifers. The methodology is based on the analytical results presented in [1,2] for utilising the colloid filtration theory in a time-domain random walk framework. It is shown that in uniform flow, the results from the numerical simulations of advection yield comparable results as the analytical TDRW model for generating advection segments. It is shown that spatial variability of the attachment rate may be significant, however, it appears to affect risk in a different manner depending on if the flow is uniform or radially converging. In spite of the fact that numerous issues remain open regarding pathogen transport in aquifers on the field scale, the methodology presented here may be useful for screening purposes, and may also serve as a basis for future studies that would include greater complexity.

Anisotropic Stochastic Vortex Structure Method for Simulating Particle Collision in Turbulent Shear Flows

NASA Astrophysics Data System (ADS)

Dizaji, Farzad; Marshall, Jeffrey; Grant, John; Jin, Xing

2017-11-01

Accounting for the effect of subgrid-scale turbulence on interacting particles remains a challenge when using Reynolds-Averaged Navier Stokes (RANS) or Large Eddy Simulation (LES) approaches for simulation of turbulent particulate flows. The standard stochastic Lagrangian method for introducing turbulence into particulate flow computations is not effective when the particles interact via collisions, contact electrification, etc., since this method is not intended to accurately model relative motion between particles. We have recently developed the stochastic vortex structure (SVS) method and demonstrated its use for accurate simulation of particle collision in homogeneous turbulence; the current work presents an extension of the SVS method to turbulent shear flows. The SVS method simulates subgrid-scale turbulence using a set of randomly-positioned, finite-length vortices to generate a synthetic fluctuating velocity field. It has been shown to accurately reproduce the turbulence inertial-range spectrum and the probability density functions for the velocity and acceleration fields. In order to extend SVS to turbulent shear flows, a new inversion method has been developed to orient the vortices in order to generate a specified Reynolds stress field. The extended SVS method is validated in the present study with comparison to direct numerical simulations for a planar turbulent jet flow. This research was supported by the U.S. National Science Foundation under Grant CBET-1332472.

Disorder and Quantum Spin Ice

NASA Astrophysics Data System (ADS)

Martin, N.; Bonville, P.; Lhotel, E.; Guitteny, S.; Wildes, A.; Decorse, C.; Ciomaga Hatnean, M.; Balakrishnan, G.; Mirebeau, I.; Petit, S.

2017-10-01

We report on diffuse neutron scattering experiments providing evidence for the presence of random strains in the quantum spin-ice candidate Pr2Zr2O7 . Since Pr3 + is a non-Kramers ion, the strain deeply modifies the picture of Ising magnetic moments governing the low-temperature properties of this material. It is shown that the derived strain distribution accounts for the temperature dependence of the specific heat and of the spin-excitation spectra. Taking advantage of mean-field and spin-dynamics simulations, we argue that the randomness in Pr2Zr2O7 promotes a new state of matter, which is disordered yet characterized by short-range antiferroquadrupolar correlations, and from which emerge spin-ice-like excitations. Thus, this study gives an original research route in the field of quantum spin ice.

ReaxFF Study of the Oxidation of Softwood Lignin in View of Carbon Fiber Production

DOE PAGES

Beste, Ariana

2014-10-06

We investigate the oxidative, thermal conversion of softwood lignin by performing molecular dynamics simulations based on a reactive force field (ReaxFF). The lignin samples are constructed from coniferyl alcohol units, which are connected through linkages that are randomly selected from a natural distribution of linkages in softwood. The goal of this work is to simulate the oxidative stabilization step during carbon fiber production from lignin precursor. We find that at simulation conditions where stabilization reactions occur, the lignin fragments have already undergone extensive degradation. The 5-5 linkage shows the highest reactivity towards cyclization and dehydrogenation.

Collisional PIC Simulations of Particles in Magnetic Fields

NASA Astrophysics Data System (ADS)

Peter, William

2003-10-01

Because of the long range of Coloumb forces, collisions with distant particles in plasmas are more important than collisions with near neighbors. In addition, many problems in space physics and magnetic confinement include regions of weak magnetic field where the MHD approximation breaks down. A particle-in-cell code based on the quiet direct simulation Monte-Carlo method(B. J. Albright, W. Daughton, D. Lemons, D. Winske, and M. E. Jones, Physics of Plasmas) 9, 1898 (2002). is being developed to study collisional (e.g., ν ˜ Ω) particle motion in magnetic fields. Primary application is to energetic particle loss in the radiation belts(K. Papadopoulos, COSPAR Meeting, Houston, TX, Oct., 2002.) at a given energy and L-shell. Other applications include trapping in rotating field-reversed configurations(N. Rostoker and A. Qerushi, Physics of Plasmas) 9, 3057 (2002)., and electron behavior in magnetic traps(V. Gorgadze, T. Pasquini, J. S. Wurtele, and J. Fajans, Bull. Am. Phys. Soc.) 47, 127 (2002).. The use of the random time-step method(W. Peter, Bull. Am. Phys. Soc.) 47, 52 (2002). to decrease simulation times by 1-2 orders of magnitude is also being studied.

A New Method of Random Environmental Walking for Assessing Behavioral Preferences for Different Lighting Applications

PubMed Central

Patching, Geoffrey R.; Rahm, Johan; Jansson, Märit; Johansson, Maria

2017-01-01

Accurate assessment of people’s preferences for different outdoor lighting applications is increasingly considered important in the development of new urban environments. Here a new method of random environmental walking is proposed to complement current methods of assessing urban lighting applications, such as self-report questionnaires. The procedure involves participants repeatedly walking between different lighting applications by random selection of a lighting application and preferred choice or by random selection of a lighting application alone. In this manner, participants are exposed to all lighting applications of interest more than once and participants’ preferences for the different lighting applications are reflected in the number of times they walk to each lighting application. On the basis of an initial simulation study, to explore the feasibility of this approach, a comprehensive field test was undertaken. The field test included random environmental walking and collection of participants’ subjective ratings of perceived pleasantness (PP), perceived quality, perceived strength, and perceived flicker of four lighting applications. The results indicate that random environmental walking can reveal participants’ preferences for different lighting applications that, in the present study, conformed to participants’ ratings of PP and perceived quality of the lighting applications. As a complement to subjectively stated environmental preferences, random environmental walking has the potential to expose behavioral preferences for different lighting applications. PMID:28337163

A distance limited method for sampling downed coarse woody debris

Treesearch

Jeffrey H. Gove; Mark J. Ducey; Harry T. Valentine; Michael S. Williams

2012-01-01

A new sampling method for down coarse woody debris is proposed based on limiting the perpendicular distance from individual pieces to a randomly chosen sample point. Two approaches are presented that allow different protocols to be used to determine field measurements; estimators for each protocol are also developed. Both protocols are compared via simulation against...

A stochastic-geometric model of soil variation in Pleistocene patterned ground

NASA Astrophysics Data System (ADS)

Lark, Murray; Meerschman, Eef; Van Meirvenne, Marc

2013-04-01

In this paper we examine the spatial variability of soil in parent material with complex spatial structure which arises from complex non-linear geomorphic processes. We show that this variability can be better-modelled by a stochastic-geometric model than by a standard Gaussian random field. The benefits of the new model are seen in the reproduction of features of the target variable which influence processes like water movement and pollutant dispersal. Complex non-linear processes in the soil give rise to properties with non-Gaussian distributions. Even under a transformation to approximate marginal normality, such variables may have a more complex spatial structure than the Gaussian random field model of geostatistics can accommodate. In particular the extent to which extreme values of the variable are connected in spatially coherent regions may be misrepresented. As a result, for example, geostatistical simulation generally fails to reproduce the pathways for preferential flow in an environment where coarse infill of former fluvial channels or coarse alluvium of braided streams creates pathways for rapid movement of water. Multiple point geostatistics has been developed to deal with this problem. Multiple point methods proceed by sampling from a set of training images which can be assumed to reproduce the non-Gaussian behaviour of the target variable. The challenge is to identify appropriate sources of such images. In this paper we consider a mode of soil variation in which the soil varies continuously, exhibiting short-range lateral trends induced by local effects of the factors of soil formation which vary across the region of interest in an unpredictable way. The trends in soil variation are therefore only apparent locally, and the soil variation at regional scale appears random. We propose a stochastic-geometric model for this mode of soil variation called the Continuous Local Trend (CLT) model. We consider a case study of soil formed in relict patterned ground with pronounced lateral textural variations arising from the presence of infilled ice-wedges of Pleistocene origin. We show how knowledge of the pedogenetic processes in this environment, along with some simple descriptive statistics, can be used to select and fit a CLT model for the apparent electrical conductivity (ECa) of the soil. We use the model to simulate realizations of the CLT process, and compare these with realizations of a fitted Gaussian random field. We show how statistics that summarize the spatial coherence of regions with small values of ECa, which are expected to have coarse texture and so larger saturated hydraulic conductivity, are better reproduced by the CLT model than by the Gaussian random field. This suggests that the CLT model could be used to generate an unlimited supply of training images to allow multiple point geostatistical simulation or prediction of this or similar variables.

Variational approach to probabilistic finite elements

NASA Technical Reports Server (NTRS)

Belytschko, T.; Liu, W. K.; Mani, A.; Besterfield, G.

1991-01-01

Probabilistic finite element methods (PFEM), synthesizing the power of finite element methods with second-moment techniques, are formulated for various classes of problems in structural and solid mechanics. Time-invariant random materials, geometric properties and loads are incorporated in terms of their fundamental statistics viz. second-moments. Analogous to the discretization of the displacement field in finite element methods, the random fields are also discretized. Preserving the conceptual simplicity, the response moments are calculated with minimal computations. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. By construction, these methods are applicable when the scale of randomness is not very large and when the probabilistic density functions have decaying tails. The accuracy and efficiency of these methods, along with their limitations, are demonstrated by various applications. Results obtained are compared with those of Monte Carlo simulation and it is shown that good accuracy can be obtained for both linear and nonlinear problems. The methods are amenable to implementation in deterministic FEM based computer codes.

Variational approach to probabilistic finite elements

NASA Astrophysics Data System (ADS)

Belytschko, T.; Liu, W. K.; Mani, A.; Besterfield, G.

1991-08-01

Probabilistic finite element methods (PFEM), synthesizing the power of finite element methods with second-moment techniques, are formulated for various classes of problems in structural and solid mechanics. Time-invariant random materials, geometric properties and loads are incorporated in terms of their fundamental statistics viz. second-moments. Analogous to the discretization of the displacement field in finite element methods, the random fields are also discretized. Preserving the conceptual simplicity, the response moments are calculated with minimal computations. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. By construction, these methods are applicable when the scale of randomness is not very large and when the probabilistic density functions have decaying tails. The accuracy and efficiency of these methods, along with their limitations, are demonstrated by various applications. Results obtained are compared with those of Monte Carlo simulation and it is shown that good accuracy can be obtained for both linear and nonlinear problems. The methods are amenable to implementation in deterministic FEM based computer codes.

Variational approach to probabilistic finite elements

NASA Technical Reports Server (NTRS)

Belytschko, T.; Liu, W. K.; Mani, A.; Besterfield, G.

1987-01-01

Probabilistic finite element method (PFEM), synthesizing the power of finite element methods with second-moment techniques, are formulated for various classes of problems in structural and solid mechanics. Time-invariant random materials, geometric properties, and loads are incorporated in terms of their fundamental statistics viz. second-moments. Analogous to the discretization of the displacement field in finite element methods, the random fields are also discretized. Preserving the conceptual simplicity, the response moments are calculated with minimal computations. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. By construction, these methods are applicable when the scale of randomness is not very large and when the probabilistic density functions have decaying tails. The accuracy and efficiency of these methods, along with their limitations, are demonstrated by various applications. Results obtained are compared with those of Monte Carlo simulation and it is shown that good accuracy can be obtained for both linear and nonlinear problems. The methods are amenable to implementation in deterministic FEM based computer codes.

Projective simulation for artificial intelligence

NASA Astrophysics Data System (ADS)

Briegel, Hans J.; de Las Cuevas, Gemma

2012-05-01

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.

Projective simulation for artificial intelligence

PubMed Central

Briegel, Hans J.; De las Cuevas, Gemma

2012-01-01

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation. PMID:22590690

Numerical Simulation of DC Coronal Heating

NASA Astrophysics Data System (ADS)

Dahlburg, Russell B.; Einaudi, G.; Taylor, Brian D.; Ugarte-Urra, Ignacio; Warren, Harry; Rappazzo, A. F.; Velli, Marco

2016-05-01

Recent research on observational signatures of turbulent heating of a coronal loop will be discussed. The evolution of the loop is is studied by means of numerical simulations of the fully compressible three-dimensional magnetohydrodynamic equations using the HYPERION code. HYPERION calculates the full energy cycle involving footpoint convection, magnetic reconnection, nonlinear thermal conduction and optically thin radiation. The footpoints of the loop magnetic field are convected by random photospheric motions. As a consequence the magnetic field in the loop is energized and develops turbulent nonlinear dynamics characterized by the continuous formation and dissipation of field-aligned current sheets: energy is deposited at small scales where heating occurs. Dissipation is non-uniformly distributed so that only a fraction of thecoronal mass and volume gets heated at any time. Temperature and density are highly structured at scales which, in the solar corona, remain observationally unresolved: the plasma of the simulated loop is multi thermal, where highly dynamical hotter and cooler plasma strands are scattered throughout the loop at sub-observational scales. Typical simulated coronal loops are 50000 km length and have axial magnetic field intensities ranging from 0.01 to 0.04 Tesla. To connect these simulations to observations the computed number densities and temperatures are used to synthesize the intensities expected in emission lines typically observed with the Extreme ultraviolet Imaging Spectrometer (EIS) on Hinode. These intensities are then employed to compute differential emission measure distributions, which are found to be very similar to those derived from observations of solar active regions.

Modeling Nonstationarity in Space and Time

PubMed Central

2017-01-01

Summary We propose to model a spatio-temporal random field that has nonstationary covariance structure in both space and time domains by applying the concept of the dimension expansion method in Bornn et al. (2012). Simulations are conducted for both separable and nonseparable space-time covariance models, and the model is also illustrated with a streamflow dataset. Both simulation and data analyses show that modeling nonstationarity in both space and time can improve the predictive performance over stationary covariance models or models that are nonstationary in space but stationary in time. PMID:28134977

Modeling nonstationarity in space and time.

PubMed

Shand, Lyndsay; Li, Bo

2017-09-01

We propose to model a spatio-temporal random field that has nonstationary covariance structure in both space and time domains by applying the concept of the dimension expansion method in Bornn et al. (2012). Simulations are conducted for both separable and nonseparable space-time covariance models, and the model is also illustrated with a streamflow dataset. Both simulation and data analyses show that modeling nonstationarity in both space and time can improve the predictive performance over stationary covariance models or models that are nonstationary in space but stationary in time. © 2017, The International Biometric Society.

Simple stochastic simulation.

PubMed

Schilstra, Maria J; Martin, Stephen R

2009-01-01

Stochastic simulations may be used to describe changes with time of a reaction system in a way that explicitly accounts for the fact that molecules show a significant degree of randomness in their dynamic behavior. The stochastic approach is almost invariably used when small numbers of molecules or molecular assemblies are involved because this randomness leads to significant deviations from the predictions of the conventional deterministic (or continuous) approach to the simulation of biochemical kinetics. Advances in computational methods over the three decades that have elapsed since the publication of Daniel Gillespie's seminal paper in 1977 (J. Phys. Chem. 81, 2340-2361) have allowed researchers to produce highly sophisticated models of complex biological systems. However, these models are frequently highly specific for the particular application and their description often involves mathematical treatments inaccessible to the nonspecialist. For anyone completely new to the field to apply such techniques in their own work might seem at first sight to be a rather intimidating prospect. However, the fundamental principles underlying the approach are in essence rather simple, and the aim of this article is to provide an entry point to the field for a newcomer. It focuses mainly on these general principles, both kinetic and computational, which tend to be not particularly well covered in specialist literature, and shows that interesting information may even be obtained using very simple operations in a conventional spreadsheet.

Charged Particle Diffusion in Isotropic Random Static Magnetic Fields

NASA Astrophysics Data System (ADS)

Subedi, P.; Sonsrettee, W.; Matthaeus, W. H.; Ruffolo, D. J.; Wan, M.; Montgomery, D.

2013-12-01

Study of the transport and diffusion of charged particles in a turbulent magnetic field remains a subject of considerable interest. Research has most frequently concentrated on determining the diffusion coefficient in the presence of a mean magnetic field. Here we consider Diffusion of charged particles in fully three dimensional statistically isotropic magnetic field turbulence with no mean field which is pertinent to many astrophysical situations. We classify different regions of particle energy depending upon the ratio of Larmor radius of the charged particle to the characteristic outer length scale of turbulence. We propose three different theoretical models to calculate the diffusion coefficient each applicable to a distinct range of particle energies. The theoretical results are compared with those from computer simulations, showing very good agreement.

Reactivating dynamics for the susceptible-infected-susceptible model: a simple method to simulate the absorbing phase

NASA Astrophysics Data System (ADS)

Macedo-Filho, A.; Alves, G. A.; Costa Filho, R. N.; Alves, T. F. A.

2018-04-01

We investigated the susceptible-infected-susceptible model on a square lattice in the presence of a conjugated field based on recently proposed reactivating dynamics. Reactivating dynamics consists of reactivating the infection by adding one infected site, chosen randomly when the infection dies out, avoiding the dynamics being trapped in the absorbing state. We show that the reactivating dynamics can be interpreted as the usual dynamics performed in the presence of an effective conjugated field, named the reactivating field. The reactivating field scales as the inverse of the lattice number of vertices n, which vanishes at the thermodynamic limit and does not affect any scaling properties including ones related to the conjugated field.

Modeling of contact tracing in social networks

NASA Astrophysics Data System (ADS)

Tsimring, Lev S.; Huerta, Ramón

2003-07-01

Spreading of certain infections in complex networks is effectively suppressed by using intelligent strategies for epidemic control. One such standard epidemiological strategy consists in tracing contacts of infected individuals. In this paper, we use a recently introduced generalization of the standard susceptible-infectious-removed stochastic model for epidemics in sparse random networks which incorporates an additional (traced) state. We describe a deterministic mean-field description which yields quantitative agreement with stochastic simulations on random graphs. We also discuss the role of contact tracing in epidemics control in small-world and scale-free networks. Effectiveness of contact tracing grows as the rewiring probability is reduced.

Multisource passive acoustic tracking: an application of random finite set data fusion

NASA Astrophysics Data System (ADS)

Ali, Andreas M.; Hudson, Ralph E.; Lorenzelli, Flavio; Yao, Kung

2010-04-01

Multisource passive acoustic tracking is useful in animal bio-behavioral study by replacing or enhancing human involvement during and after field data collection. Multiple simultaneous vocalizations are a common occurrence in a forest or a jungle, where many species are encountered. Given a set of nodes that are capable of producing multiple direction-of-arrivals (DOAs), such data needs to be combined into meaningful estimates. Random Finite Set provides the mathematical probabilistic model, which is suitable for analysis and optimal estimation algorithm synthesis. Then the proposed algorithm has been verified using a simulation and a controlled test experiment.

How many photons are needed to reconstruct random objects in coherent X-ray diffractive imaging?

PubMed

Jahn, T; Wilke, R N; Chushkin, Y; Salditt, T

2017-01-01

This paper presents an investigation of the reconstructibility of coherent X-ray diffractive imaging diffraction patterns for a class of binary random `bitmap' objects. Combining analytical results and numerical simulations, the critical fluence per bitmap pixel is determined, for arbitrary contrast values (absorption level and phase shift), both for the optical near- and far-field. This work extends previous investigations based on information theory, enabling a comparison of the amount of information carried by single photons in different diffraction regimes. The experimental results show an order-of-magnitude agreement.

A path-level exact parallelization strategy for sequential simulation

NASA Astrophysics Data System (ADS)

Peredo, Oscar F.; Baeza, Daniel; Ortiz, Julián M.; Herrero, José R.

2018-01-01

Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian approach for simulation of conditionally dependent random events, Sequential Indicator Simulation (SIS) method draws simulated values for K categories (categorical case) or classes defined by K different thresholds (continuous case). Similarly, Sequential Gaussian Simulation (SGS) method draws simulated values from a multivariate Gaussian field. In this work, a path-level approach to parallelize SIS and SGS methods is presented. A first stage of re-arrangement of the simulation path is performed, followed by a second stage of parallel simulation for non-conflicting nodes. A key advantage of the proposed parallelization method is to generate identical realizations as with the original non-parallelized methods. Case studies are presented using two sequential simulation codes from GSLIB: SISIM and SGSIM. Execution time and speedup results are shown for large-scale domains, with many categories and maximum kriging neighbours in each case, achieving high speedup results in the best scenarios using 16 threads of execution in a single machine.

Phase diagram, correlation gap, and critical properties of the Coulomb glass

NASA Astrophysics Data System (ADS)

Palassini, Matteo; Goethe, Martin

2009-03-01

We investigate the lattice Coulomb glass model in three dimensions via extensive Monte Carlo simulations. 1. No evidence for an equilibrium glass phase is found down to very low temperatures, contrary to mean-field predictions, although the correlation length increases rapidly near T=0. 2. The single-particle density of states near the Coulomb gap satisfies the scaling law g(e,T)=T^λf(e/T) with λ 2.2. 3. A charge-ordered phase exists at low disorder. The phase transition from the fluid to the charge ordered phase is consistent with the Random Field Ising universality class, which shows that the interaction is effectively screened at moderate temperature. Results from nonequilibrium simulations will also be briefly discussed. Reference: M.Goethe and M.Palassini, arXiv:0810.1047

Modeling and Simulation of the Dynamics of Dissipative, Inelastic Spheres with Applications to Planetary Rovers and Gravitational Billiards

NASA Astrophysics Data System (ADS)

Hartl, Alexandre E.

This dissertation provides a thorough treatment on the dynamic modeling and simulation of spherical objects, and its applications to planetary rovers and gravitational billiards. First, the equations governing the motion of a wind-driven spherical rover are developed, and a numerical procedure for their implementation is shown. Dynamic simulations (considering the Earth and Mars atmospheres) for several terrain types and conditions illustrate how a rover may maneuver across flat terrain, channels and craters. The effects of aerodynamic forces on the rover's motion is studied. The results show the wind force may both push and hinder the rover's motion while sliding, rolling and bouncing. The rover will periodically transition between these modes of movement when the rover impacts sloped surfaces. Combinations of rolling and bouncing may be a more effective means of transport for a rover traveling through a channel when compared to rolling alone. The aerodynamic effects, of drag and the Magnus force, are contributing factors to the possible capture of the rover by a crater. Next, a strategy is formulated for creating randomized Martian rock fields based on statistical models, where the rover's interactions with these fields are analyzed. Novel procedures for creating randomized Martian rock fields are presented, where optimization techniques allow terrain generation to coincide with the rover's motion. Efficient collision detection routines reduce the number of tests of potential collisions between the rover and the terrain while establishing new contact constraints. The procedures allow for the exploration of large regions of terrain while minimizing computational costs. Simulations demonstrate that bouncing is the rover's dominant mode of travel through the rock fields. Monte-Carlo simulations illustrate how the rover's down-range position depends on the rover design and atmospheric conditions. Moreover, the simulations verify the rover's capacity for long distance travel over Martian rock fields. Finally, a mathematical model that captures the essential dynamics required for describing the motion of a real world billiard for arbitrary boundaries is presented. The model considers the more realistic situation of an inelastic, rotating, gravitational billiard in which there are retarding forces due to air resistance and friction. The simulations demonstrate that the parabola has stable, periodic motion, while the wedge and hyperbola, at high driving frequencies, appear chaotic. The hyperbola, at low driving frequencies, behaves similarly to the parabola, and has regular motion. Direct comparisons are made between the model's predictions and previously published experimental data. The representation of the coefficient of restitution employed in the model resulted in good agreement with the experimental data for all boundary shapes investigated. It is shown that the data can be successfully modeled with a simple set of parameters without an assumption of exotic energy dependence.

Choosing a Transformation in Analyses of Insect Counts from Contagious Distributions with Low Means

Treesearch

W.D. Pepper; S.J. Zarnoch; G.L. DeBarr; P. de Groot; C.D. Tangren

1997-01-01

Guidelines based on computer simulation are suggested for choosing a transformation of insect counts from negative binomial distributions with low mean counts and high levels of contagion. Typical values and ranges of negative binomial model parameters were determined by fitting the model to data from 19 entomological field studies. Random sampling of negative binomial...

Coherent states field theory in supramolecular polymer physics

NASA Astrophysics Data System (ADS)

Fredrickson, Glenn H.; Delaney, Kris T.

2018-05-01

In 1970, Edwards and Freed presented an elegant representation of interacting branched polymers that resembles the coherent states (CS) formulation of second-quantized field theory. This CS polymer field theory has been largely overlooked during the intervening period in favor of more conventional "auxiliary field" (AF) interacting polymer representations that form the basis of modern self-consistent field theory (SCFT) and field-theoretic simulation approaches. Here we argue that the CS representation provides a simpler and computationally more efficient framework than the AF approach for broad classes of reversibly bonding polymers encountered in supramolecular polymer science. The CS formalism is reviewed, initially for a simple homopolymer solution, and then extended to supramolecular polymers capable of forming reversible linkages and networks. In the context of the Edwards model of a non-reacting homopolymer solution and one and two-component models of telechelic reacting polymers, we discuss the structure of CS mean-field theory, including the equivalence to SCFT, and show how weak-amplitude expansions (random phase approximations) can be readily developed without explicit enumeration of all reaction products in a mixture. We further illustrate how to analyze CS field theories beyond SCFT at the level of Gaussian field fluctuations and provide a perspective on direct numerical simulations using a recently developed complex Langevin technique.

Fluid-driven fracture propagation in heterogeneous media: Probability distributions of fracture trajectories

NASA Astrophysics Data System (ADS)

Santillán, David; Mosquera, Juan-Carlos; Cueto-Felgueroso, Luis

2017-11-01

Hydraulic fracture trajectories in rocks and other materials are highly affected by spatial heterogeneity in their mechanical properties. Understanding the complexity and structure of fluid-driven fractures and their deviation from the predictions of homogenized theories is a practical problem in engineering and geoscience. We conduct a Monte Carlo simulation study to characterize the influence of heterogeneous mechanical properties on the trajectories of hydraulic fractures propagating in elastic media. We generate a large number of random fields of mechanical properties and simulate pressure-driven fracture propagation using a phase-field model. We model the mechanical response of the material as that of an elastic isotropic material with heterogeneous Young modulus and Griffith energy release rate, assuming that fractures propagate in the toughness-dominated regime. Our study shows that the variance and the spatial covariance of the mechanical properties are controlling factors in the tortuousness of the fracture paths. We characterize the deviation of fracture paths from the homogenous case statistically, and conclude that the maximum deviation grows linearly with the distance from the injection point. Additionally, fracture path deviations seem to be normally distributed, suggesting that fracture propagation in the toughness-dominated regime may be described as a random walk.

Fluid-driven fracture propagation in heterogeneous media: Probability distributions of fracture trajectories.

PubMed

Santillán, David; Mosquera, Juan-Carlos; Cueto-Felgueroso, Luis

2017-11-01

Hydraulic fracture trajectories in rocks and other materials are highly affected by spatial heterogeneity in their mechanical properties. Understanding the complexity and structure of fluid-driven fractures and their deviation from the predictions of homogenized theories is a practical problem in engineering and geoscience. We conduct a Monte Carlo simulation study to characterize the influence of heterogeneous mechanical properties on the trajectories of hydraulic fractures propagating in elastic media. We generate a large number of random fields of mechanical properties and simulate pressure-driven fracture propagation using a phase-field model. We model the mechanical response of the material as that of an elastic isotropic material with heterogeneous Young modulus and Griffith energy release rate, assuming that fractures propagate in the toughness-dominated regime. Our study shows that the variance and the spatial covariance of the mechanical properties are controlling factors in the tortuousness of the fracture paths. We characterize the deviation of fracture paths from the homogenous case statistically, and conclude that the maximum deviation grows linearly with the distance from the injection point. Additionally, fracture path deviations seem to be normally distributed, suggesting that fracture propagation in the toughness-dominated regime may be described as a random walk.

Images of turbulent, absorbing-emitting atmospheres and their application to windshear detection

NASA Astrophysics Data System (ADS)

Watt, David W.; Philbrick, Daniel A.

1991-03-01

The simulation of images generated by thermally-radiating, optically- thick turbulent media are discussed and the time-dependent evolution of these images is modeled. This characteristics of these images are particularly applicable to the atmosphere in the 13-15 mm band and their behavior may have application in detecting aviation hazards. The image is generated by volumetric thermal emission by atmospheric constituents within the field-of-view of the detector. The structure of the turbulent temperature field and the attenuating properties of the atmosphere interact with the field-of-view's geometry to produce a localized region which dominates the optical flow of the image. The simulations discussed in this paper model the time-dependent behavior of images generated by atmospheric flows viewed from an airborne platform. The images ar modelled by (1) generating a random field of temperature fluctuations have the proper spatial structure, (2) adding these fluctuation to the baseline temperature field of the atmospheric event, (3) accumulating the image on the detector from radiation emitted in the imaging volume, (4) allowing the individual radiating points within the imaging volume to move with the local velocity, (5) recalculating the thermal field and generating a new image. This approach was used to simulate the images generated by the temperature and velocity fields of a windshear. The simulation generated pais of images separated by a small time interval. These image paris were analyzed by image cross-correlation. The displacement of the cross-correlation peak was used to infer the velocity at the localized region. The localized region was found to depend weakly on the shape of the velocity profile. Prediction of the localized region, the effects of imaging from a moving platform, alternative image analysis schemes, and possible application to aviation hazards are discussed.

On the joint spectral density of bivariate random sequences. Thesis Technical Report No. 21

NASA Technical Reports Server (NTRS)

Aalfs, David D.

1995-01-01

For univariate random sequences, the power spectral density acts like a probability density function of the frequencies present in the sequence. This dissertation extends that concept to bivariate random sequences. For this purpose, a function called the joint spectral density is defined that represents a joint probability weighing of the frequency content of pairs of random sequences. Given a pair of random sequences, the joint spectral density is not uniquely determined in the absence of any constraints. Two approaches to constraining the sequences are suggested: (1) assume the sequences are the margins of some stationary random field, (2) assume the sequences conform to a particular model that is linked to the joint spectral density. For both approaches, the properties of the resulting sequences are investigated in some detail, and simulation is used to corroborate theoretical results. It is concluded that under either of these two constraints, the joint spectral density can be computed from the non-stationary cross-correlation.

Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

PubMed

Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

2011-10-01

Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Anomalous Growth of Aging Populations

NASA Astrophysics Data System (ADS)

Grebenkov, Denis S.

2016-04-01

We consider a discrete-time population dynamics with age-dependent structure. At every time step, one of the alive individuals from the population is chosen randomly and removed with probability q_k depending on its age, whereas a new individual of age 1 is born with probability r. The model can also describe a single queue in which the service order is random while the service efficiency depends on a customer's "age" in the queue. We propose a mean field approximation to investigate the long-time asymptotic behavior of the mean population size. The age dependence is shown to lead to anomalous power-law growth of the population at the critical regime. The scaling exponent is determined by the asymptotic behavior of the probabilities q_k at large k. The mean field approximation is validated by Monte Carlo simulations.

Risk perception in epidemic modeling

NASA Astrophysics Data System (ADS)

Bagnoli, Franco; Liò, Pietro; Sguanci, Luca

2007-12-01

We investigate the effects of risk perception in a simple model of epidemic spreading. We assume that the perception of the risk of being infected depends on the fraction of neighbors that are ill. The effect of this factor is to decrease the infectivity, that therefore becomes a dynamical component of the model. We study the problem in the mean-field approximation and by numerical simulations for regular, random, and scale-free networks. We show that for homogeneous and random networks, there is always a value of perception that stops the epidemics. In the “worst-case” scenario of a scale-free network with diverging input connectivity, a linear perception cannot stop the epidemics; however, we show that a nonlinear increase of the perception risk may lead to the extinction of the disease. This transition is discontinuous, and is not predicted by the mean-field analysis.

Phase unwrapping using region-based markov random field model.

PubMed

Dong, Ying; Ji, Jim

2010-01-01

Phase unwrapping is a classical problem in Magnetic Resonance Imaging (MRI), Interferometric Synthetic Aperture Radar and Sonar (InSAR/InSAS), fringe pattern analysis, and spectroscopy. Although many methods have been proposed to address this problem, robust and effective phase unwrapping remains a challenge. This paper presents a novel phase unwrapping method using a region-based Markov Random Field (MRF) model. Specifically, the phase image is segmented into regions within which the phase is not wrapped. Then, the phase image is unwrapped between different regions using an improved Highest Confidence First (HCF) algorithm to optimize the MRF model. The proposed method has desirable theoretical properties as well as an efficient implementation. Simulations and experimental results on MRI images show that the proposed method provides similar or improved phase unwrapping than Phase Unwrapping MAx-flow/min-cut (PUMA) method and ZpM method.

Sample design effects in landscape genetics

USGS Publications Warehouse

Oyler-McCance, Sara J.; Fedy, Bradley C.; Landguth, Erin L.

2012-01-01

An important research gap in landscape genetics is the impact of different field sampling designs on the ability to detect the effects of landscape pattern on gene flow. We evaluated how five different sampling regimes (random, linear, systematic, cluster, and single study site) affected the probability of correctly identifying the generating landscape process of population structure. Sampling regimes were chosen to represent a suite of designs common in field studies. We used genetic data generated from a spatially-explicit, individual-based program and simulated gene flow in a continuous population across a landscape with gradual spatial changes in resistance to movement. Additionally, we evaluated the sampling regimes using realistic and obtainable number of loci (10 and 20), number of alleles per locus (5 and 10), number of individuals sampled (10-300), and generational time after the landscape was introduced (20 and 400). For a simulated continuously distributed species, we found that random, linear, and systematic sampling regimes performed well with high sample sizes (>200), levels of polymorphism (10 alleles per locus), and number of molecular markers (20). The cluster and single study site sampling regimes were not able to correctly identify the generating process under any conditions and thus, are not advisable strategies for scenarios similar to our simulations. Our research emphasizes the importance of sampling data at ecologically appropriate spatial and temporal scales and suggests careful consideration for sampling near landscape components that are likely to most influence the genetic structure of the species. In addition, simulating sampling designs a priori could help guide filed data collection efforts.

A dose optimization method for electron radiotherapy using randomized aperture beams

NASA Astrophysics Data System (ADS)

Engel, Konrad; Gauer, Tobias

2009-09-01

The present paper describes the entire optimization process of creating a radiotherapy treatment plan for advanced electron irradiation. Special emphasis is devoted to the selection of beam incidence angles and beam energies as well as to the choice of appropriate subfields generated by a refined version of intensity segmentation and a novel random aperture approach. The algorithms have been implemented in a stand-alone programme using dose calculations from a commercial treatment planning system. For this study, the treatment planning system Pinnacle from Philips has been used and connected to the optimization programme using an ASCII interface. Dose calculations in Pinnacle were performed by Monte Carlo simulations for a remote-controlled electron multileaf collimator (MLC) from Euromechanics. As a result, treatment plans for breast cancer patients could be significantly improved when using randomly generated aperture beams. The combination of beams generated through segmentation and randomization achieved the best results in terms of target coverage and sparing of critical organs. The treatment plans could be further improved by use of a field reduction algorithm. Without a relevant loss in dose distribution, the total number of MLC fields and monitor units could be reduced by up to 20%. In conclusion, using randomized aperture beams is a promising new approach in radiotherapy and exhibits potential for further improvements in dose optimization through a combination of randomized electron and photon aperture beams.

Features of the energy structure of acoustic fields in the ocean with two-dimensional random inhomogeneities

NASA Astrophysics Data System (ADS)

Gulin, O. E.; Yaroshchuk, I. O.

2017-03-01

The paper is devoted to the analytic study and numerical simulation of mid-frequency acoustic signal propagation in a two-dimensional inhomogeneous random shallow-water medium. The study was carried out by the cross section method (local modes). We present original theoretical estimates for the behavior of the average acoustic field intensity and show that at different distances, the features of propagation loss behavior are determined by the intensity of fluctuations and their horizontal scale and depend on the initial regular parameters, such as the emission frequency and size of sound losses in the bottom. We establish analytically that for the considered waveguide and sound frequency parameters, mode coupling effect has a local character and weakly influences the statistics. We establish that the specific form of the spatial spectrum of sound velocity inhomogeneities for the statistical patterns of the field intensity is insignificant during observations in the range of shallow-water distances of practical interest.

Multi-fidelity Gaussian process regression for prediction of random fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parussini, L.; Venturi, D., E-mail: venturi@ucsc.edu; Perdikaris, P.

We propose a new multi-fidelity Gaussian process regression (GPR) approach for prediction of random fields based on observations of surrogate models or hierarchies of surrogate models. Our method builds upon recent work on recursive Bayesian techniques, in particular recursive co-kriging, and extends it to vector-valued fields and various types of covariances, including separable and non-separable ones. The framework we propose is general and can be used to perform uncertainty propagation and quantification in model-based simulations, multi-fidelity data fusion, and surrogate-based optimization. We demonstrate the effectiveness of the proposed recursive GPR techniques through various examples. Specifically, we study the stochastic Burgersmore » equation and the stochastic Oberbeck–Boussinesq equations describing natural convection within a square enclosure. In both cases we find that the standard deviation of the Gaussian predictors as well as the absolute errors relative to benchmark stochastic solutions are very small, suggesting that the proposed multi-fidelity GPR approaches can yield highly accurate results.« less

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

PubMed

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

PubMed Central

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation. PMID:28596730

Control of the electromagnetic drag using fluctuating light fields

NASA Astrophysics Data System (ADS)

Pastor, Víctor J. López; Marqués, Manuel I.

2018-05-01

An expression for the electromagnetic drag force experienced by an electric dipole in a light field consisting of a monochromatic plane wave with polarization and phase randomly fluctuating is obtained. The expression explicitly considers the transformations of the field and frequency due to the Doppler shift and the change of the polarizability response of the electric dipole. The conditions to be fulfilled by the polarizability of the dipole in order to obtain a positive, a null, and a negative drag coefficient are analytically determined and checked against numerical simulations for the dynamics of a silver nanoparticle. The theoretically predicted diffusive, superdiffusive, and exponentially accelerated dynamical regimes are numerically confirmed.

Dealing with correlated choices: how a spin-glass model can help political parties select their policies.

PubMed

Moore, M A; Katzgraber, Helmut G

2014-10-01

Starting from preferences on N proposed policies obtained via questionnaires from a sample of the electorate, an Ising spin-glass model in a field can be constructed from which a political party could find the subset of the proposed policies which would maximize its appeal, form a coherent choice in the eyes of the electorate, and have maximum overlap with the party's existing policies. We illustrate the application of the procedure by simulations of a spin glass in a random field on scale-free networks.

Supernova-regulated ISM. V. Space and Time Correlations

NASA Astrophysics Data System (ADS)

Hollins, J. F.; Sarson, G. R.; Shukurov, A.; Fletcher, A.; Gent, F. A.

2017-11-01

We apply correlation analysis to random fields in numerical simulations of the supernova-driven interstellar medium (ISM) with the magnetic field produced by dynamo action. We solve the magnetohydrodynamic (MHD) equations in a shearing Cartesian box representing a local region of the ISM, subject to thermal and kinetic energy injection by supernova explosions, and parameterized, optically thin radiative cooling. We consider the cold, warm, and hot phases of the ISM separately; the analysis mostly considers the warm gas, which occupies the bulk of the domain. Various physical variables have different correlation lengths in the warm phase: 40,50, and 60 {pc} for the random magnetic field, density, and velocity, respectively, in the midplane. The correlation time of the random velocity is comparable to the eddy turnover time, about {10}7 {year}, although it may be shorter in regions with a higher star formation rate. The random magnetic field is anisotropic, with the standard deviations of its components {b}x/{b}y/{b}z having approximate ratios 0.5/0.6/0.6 in the midplane. The anisotropy is attributed to the global velocity shear from galactic differential rotation and locally inhomogeneous outflow to the galactic halo. The correlation length of Faraday depth along the z axis, 120 {pc}, is greater than for electron density, 60{--}90 {pc}, and the vertical magnetic field, 60 {pc}. Such comparisons may be sensitive to the orientation of the line of sight. Uncertainties of the structure functions of synchrotron intensity rapidly increase with the scale. This feature is hidden in a power spectrum analysis, which can undermine the usefulness of power spectra for detailed studies of interstellar turbulence.

NMR diffusion simulation based on conditional random walk.

PubMed

Gudbjartsson, H; Patz, S

1995-01-01

The authors introduce here a new, very fast, simulation method for free diffusion in a linear magnetic field gradient, which is an extension of the conventional Monte Carlo (MC) method or the convolution method described by Wong et al. (in 12th SMRM, New York, 1993, p.10). In earlier NMR-diffusion simulation methods, such as the finite difference method (FD), the Monte Carlo method, and the deterministic convolution method, the outcome of the calculations depends on the simulation time step. In the authors' method, however, the results are independent of the time step, although, in the convolution method the step size has to be adequate for spins to diffuse to adjacent grid points. By always selecting the largest possible time step the computation time can therefore be reduced. Finally the authors point out that in simple geometric configurations their simulation algorithm can be used to reduce computation time in the simulation of restricted diffusion.

Full Wave Analysis of RF Signal Attenuation in a Lossy Rough Surface Cave using a High Order Time Domain Vector Finite Element Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pingenot, J; Rieben, R; White, D

2005-10-31

We present a computational study of signal propagation and attenuation of a 200 MHz planar loop antenna in a cave environment. The cave is modeled as a straight and lossy random rough wall. To simulate a broad frequency band, the full wave Maxwell equations are solved directly in the time domain via a high order vector finite element discretization using the massively parallel CEM code EMSolve. The numerical technique is first verified against theoretical results for a planar loop antenna in a smooth lossy cave. The simulation is then performed for a series of random rough surface meshes in ordermore » to generate statistical data for the propagation and attenuation properties of the antenna in a cave environment. Results for the mean and variance of the power spectral density of the electric field are presented and discussed.« less

Dynamical models for the formation of elephant trunks in HII regions

NASA Astrophysics Data System (ADS)

Mackey, Jonathan; Lim, Andrew J.

2010-04-01

The formation of pillars of dense gas at the boundaries of HII regions is investigated with hydrodynamical numerical simulations including ionizing radiation from a point source. We show that shadowing of ionizing radiation by an inhomogeneous density field is capable of forming so-called elephant trunks (pillars of dense gas as in e.g. M16) without the assistance of self-gravity or of ionization front and cooling instabilities. A large simulation of a density field containing randomly generated clumps of gas is shown to naturally generate elephant trunks with certain clump configurations. These configurations are simulated in isolation and analysed in detail to show the formation mechanism and determine possible observational signatures. Pillars formed by the shadowing mechanism are shown to have rather different velocity profiles depending on the initial gas configuration, but asymmetries mean that the profiles also vary significantly with perspective, limiting their ability to discriminate between formation scenarios. Neutral and molecular gas cooling are shown to have a strong effect on these results.

Microgravity simulation by diamagnetic levitation: effects of a strong gradient magnetic field on the transcriptional profile of Drosophila melanogaster.

PubMed

Herranz, Raul; Larkin, Oliver J; Dijkstra, Camelia E; Hill, Richard J A; Anthony, Paul; Davey, Michael R; Eaves, Laurence; van Loon, Jack J W A; Medina, F Javier; Marco, Roberto

2012-02-01

Many biological systems respond to the presence or absence of gravity. Since experiments performed in space are expensive and can only be undertaken infrequently, Earth-based simulation techniques are used to investigate the biological response to weightlessness. A high gradient magnetic field can be used to levitate a biological organism so that its net weight is zero. We have used a superconducting magnet to assess the effect of diamagnetic levitation on the fruit fly D. melanogaster in levitation experiments that proceeded for up to 22 consecutive days. We have compared the results with those of similar experiments performed in another paradigm for microgravity simulation, the Random Positioning Machine (RPM). We observed a delay in the development of the fruit flies from embryo to adult. Microarray analysis indicated changes in overall gene expression of imagoes that developed from larvae under diamagnetic levitation, and also under simulated hypergravity conditions. Significant changes were observed in the expression of immune-, stress-, and temperature-response genes. For example, several heat shock proteins were affected. We also found that a strong magnetic field, of 16.5 Tesla, had a significant effect on the expression of these genes, independent of the effects associated with magnetically-induced levitation and hypergravity. Diamagnetic levitation can be used to simulate an altered effective gravity environment in which gene expression is tuned differentially in diverse Drosophila melanogaster populations including those of different age and gender. Exposure to the magnetic field per se induced similar, but weaker, changes in gene expression.

Microgravity simulation by diamagnetic levitation: effects of a strong gradient magnetic field on the transcriptional profile of Drosophila melanogaster

PubMed Central

2012-01-01

Background Many biological systems respond to the presence or absence of gravity. Since experiments performed in space are expensive and can only be undertaken infrequently, Earth-based simulation techniques are used to investigate the biological response to weightlessness. A high gradient magnetic field can be used to levitate a biological organism so that its net weight is zero. Results We have used a superconducting magnet to assess the effect of diamagnetic levitation on the fruit fly D. melanogaster in levitation experiments that proceeded for up to 22 consecutive days. We have compared the results with those of similar experiments performed in another paradigm for microgravity simulation, the Random Positioning Machine (RPM). We observed a delay in the development of the fruit flies from embryo to adult. Microarray analysis indicated changes in overall gene expression of imagoes that developed from larvae under diamagnetic levitation, and also under simulated hypergravity conditions. Significant changes were observed in the expression of immune-, stress-, and temperature-response genes. For example, several heat shock proteins were affected. We also found that a strong magnetic field, of 16.5 Tesla, had a significant effect on the expression of these genes, independent of the effects associated with magnetically-induced levitation and hypergravity. Conclusions Diamagnetic levitation can be used to simulate an altered effective gravity environment in which gene expression is tuned differentially in diverse Drosophila melanogaster populations including those of different age and gender. Exposure to the magnetic field per se induced similar, but weaker, changes in gene expression. PMID:22296880

A novel approach to assess the treatment response using Gaussian random field in PET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Mengdie; Guo, Ning; Hu, Guangshu

2016-02-15

Purpose: The assessment of early therapeutic response to anticancer therapy is vital for treatment planning and patient management in clinic. With the development of personal treatment plan, the early treatment response, especially before any anatomically apparent changes after treatment, becomes urgent need in clinic. Positron emission tomography (PET) imaging serves an important role in clinical oncology for tumor detection, staging, and therapy response assessment. Many studies on therapy response involve interpretation of differences between two PET images, usually in terms of standardized uptake values (SUVs). However, the quantitative accuracy of this measurement is limited. This work proposes a statistically robustmore » approach for therapy response assessment based on Gaussian random field (GRF) to provide a statistically more meaningful scale to evaluate therapy effects. Methods: The authors propose a new criterion for therapeutic assessment by incorporating image noise into traditional SUV method. An analytical method based on the approximate expressions of the Fisher information matrix was applied to model the variance of individual pixels in reconstructed images. A zero mean unit variance GRF under the null hypothesis (no response to therapy) was obtained by normalizing each pixel of the post-therapy image with the mean and standard deviation of the pretherapy image. The performance of the proposed method was evaluated by Monte Carlo simulation, where XCAT phantoms (128{sup 2} pixels) with lesions of various diameters (2–6 mm), multiple tumor-to-background contrasts (3–10), and different changes in intensity (6.25%–30%) were used. The receiver operating characteristic curves and the corresponding areas under the curve were computed for both the proposed method and the traditional methods whose figure of merit is the percentage change of SUVs. The formula for the false positive rate (FPR) estimation was developed for the proposed therapy response assessment utilizing local average method based on random field. The accuracy of the estimation was validated in terms of Euler distance and correlation coefficient. Results: It is shown that the performance of therapy response assessment is significantly improved by the introduction of variance with a higher area under the curve (97.3%) than SUVmean (91.4%) and SUVmax (82.0%). In addition, the FPR estimation serves as a good prediction for the specificity of the proposed method, consistent with simulation outcome with ∼1 correlation coefficient. Conclusions: In this work, the authors developed a method to evaluate therapy response from PET images, which were modeled as Gaussian random field. The digital phantom simulations demonstrated that the proposed method achieved a large reduction in statistical variability through incorporating knowledge of the variance of the original Gaussian random field. The proposed method has the potential to enable prediction of early treatment response and shows promise for application to clinical practice. In future work, the authors will report on the robustness of the estimation theory for application to clinical practice of therapy response evaluation, which pertains to binary discrimination tasks at a fixed location in the image such as detection of small and weak lesion.« less

Numerical Schemes for Dynamically Orthogonal Equations of Stochastic Fluid and Ocean Flows

DTIC Science & Technology

2011-11-03

stages of the simulation (see §5.1). Also, because the pdf is discrete, we calculate the mo- ments using the biased estimator CYiYj ≈ 1q ∑ r Yr,iYr,j...independent random variables. For problems that require large p (e.g. non-Gaussian) and large s (e.g. large ocean or fluid simulations ), the number of...Sc = ν̂/K̂ is the Schmidt number which is the ratio of kinematic viscosity ν̂ to molecular diffusivity K̂ for the density field, ĝ′ = ĝ (ρ̂max−ρ̂min

Simulation study of entropy production in the one-dimensional Vlasov system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Zongliang, E-mail: liangliang1223@gmail.com; Wang, Shaojie

2016-07-15

The coarse-grain averaged distribution function of the one-dimensional Vlasov system is obtained by numerical simulation. The entropy productions in cases of the random field, the linear Landau damping, and the bump-on-tail instability are computed with the coarse-grain averaged distribution function. The computed entropy production is converged with increasing length of coarse-grain average. When the distribution function differs slightly from a Maxwellian distribution, the converged value agrees with the result computed by using the definition of thermodynamic entropy. The length of the coarse-grain average to compute the coarse-grain averaged distribution function is discussed.

Nonequilibrium dynamic phases in driven vortex lattices with periodic pinning

NASA Astrophysics Data System (ADS)

Reichhardt, Charles Michael

1998-12-01

We present the results of an extensive series of simulations of flux-gradient and current driven vortices interacting with either random or periodically arranged pinning sites. First, we consider flux-gradient-driven simulations of superconducting vortices interacting with strong randomly-distributed columnar pinning defects, as an external field H(t) is quasi-statically swept from zero through a matching field Bsb{phi}. Here, we find significant changes in the behavior of the local flux density B(x, y, H(t)), magnetization M(H(t)), critical current Jsb{c}(B(t)), and the individual vortex flow paths, as the local flux density crosses Bsb{phi}. Further, we find that for a given pin density, Jsb{c}(B) can be enhanced by maximizing the distance between the pins for B < Bsb{phi}. For the case of periodic pinning sites as a function of applied field, we find a rich variety of ordered and partially-ordered vortex lattice configurations. We present formulas that predict the matching fields at which commensurate vortex configurations occur and the vortex lattice orientation with respect to the pinning lattice. Our results are in excellent agreement with recent imaging experiments on square pinning arrays (K. Harada et al., Science 274, 1167 (1996)). For current driven simulations with periodic pinning we find a remarkable number of dynamical plastic flow phases. Signatures of the transitions between these different dynamical phases include sudden jumps in the current-voltage curves, hysteresis, as well as marked changes in the vortex trajectories and vortex lattice order. These phases are outlined in a series of dynamic phase diagrams. We show that several of these phases and their phase-boundaries can be understood in terms of analytical arguments. Finally, when the vortex lattice is driven at varying angles with respect to the underlying periodic pinning array, the transverse voltage-current V(I) curves show a series of mode-locked plateaus with the overall V(I) forming a devil's staircase structure.

A New Random Walk for Replica Detection in WSNs.

PubMed

Aalsalem, Mohammed Y; Khan, Wazir Zada; Saad, N M; Hossain, Md Shohrab; Atiquzzaman, Mohammed; Khan, Muhammad Khurram

2016-01-01

Wireless Sensor Networks (WSNs) are vulnerable to Node Replication attacks or Clone attacks. Among all the existing clone detection protocols in WSNs, RAWL shows the most promising results by employing Simple Random Walk (SRW). More recently, RAND outperforms RAWL by incorporating Network Division with SRW. Both RAND and RAWL have used SRW for random selection of witness nodes which is problematic because of frequently revisiting the previously passed nodes that leads to longer delays, high expenditures of energy with lower probability that witness nodes intersect. To circumvent this problem, we propose to employ a new kind of constrained random walk, namely Single Stage Memory Random Walk and present a distributed technique called SSRWND (Single Stage Memory Random Walk with Network Division). In SSRWND, single stage memory random walk is combined with network division aiming to decrease the communication and memory costs while keeping the detection probability higher. Through intensive simulations it is verified that SSRWND guarantees higher witness node security with moderate communication and memory overheads. SSRWND is expedient for security oriented application fields of WSNs like military and medical.

A New Random Walk for Replica Detection in WSNs

PubMed Central

Aalsalem, Mohammed Y.; Saad, N. M.; Hossain, Md. Shohrab; Atiquzzaman, Mohammed; Khan, Muhammad Khurram

2016-01-01

Wireless Sensor Networks (WSNs) are vulnerable to Node Replication attacks or Clone attacks. Among all the existing clone detection protocols in WSNs, RAWL shows the most promising results by employing Simple Random Walk (SRW). More recently, RAND outperforms RAWL by incorporating Network Division with SRW. Both RAND and RAWL have used SRW for random selection of witness nodes which is problematic because of frequently revisiting the previously passed nodes that leads to longer delays, high expenditures of energy with lower probability that witness nodes intersect. To circumvent this problem, we propose to employ a new kind of constrained random walk, namely Single Stage Memory Random Walk and present a distributed technique called SSRWND (Single Stage Memory Random Walk with Network Division). In SSRWND, single stage memory random walk is combined with network division aiming to decrease the communication and memory costs while keeping the detection probability higher. Through intensive simulations it is verified that SSRWND guarantees higher witness node security with moderate communication and memory overheads. SSRWND is expedient for security oriented application fields of WSNs like military and medical. PMID:27409082

Spectrally resolved far-fields of terahertz quantum cascade lasers.

PubMed

Brandstetter, Martin; Schönhuber, Sebastian; Krall, Michael; Kainz, Martin A; Detz, Hermann; Zederbauer, Tobias; Andrews, Aaron M; Strasser, Gottfried; Unterrainer, Karl

2016-10-31

We demonstrate a convenient and fast method to measure the spectrally resolved far-fields of multimode terahertz quantum cascade lasers by combining a microbolometer focal plane array with an FTIR spectrometer. Far-fields of fundamental TM0 and higher lateral order TM1 modes of multimode Fabry-Pérot type lasers have been distinguished, which very well fit to the results obtained by a 3D finite-element simulation. Furthermore, multimode random laser cavities have been investigated, analyzing the contribution of each single laser mode to the total far-field. The presented method is thus an important tool to gain in-depth knowledge of the emission properties of multimode laser cavities at terahertz frequencies, which become increasingly important for future sensing applications.

Engineering Design Handbook. Army Weapon Systems Analysis. Part 2

DTIC Science & Technology

1979-10-01

EXPERIMENTAL DESIGN ............................... ............ 41-3 41-5 RESULTS OF THE ASARS lIX SIMULATIONS ........................... 41-4 41-6 LATIN...sciences and human factors engineering fields utilizing experimental methodology and multi-variable statistical techniques drawn from experimental ...randomly to grenades for the test design . The nine experimental types of hand grenades (first’ nine in Table 33-2) had a "pip" on their spherical

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

NASA Astrophysics Data System (ADS)

Crevillén-García, D.; Power, H.

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Micromechanical analysis of composites with fibers distributed randomly over the transverse cross-section

NASA Astrophysics Data System (ADS)

Weng, Jingmeng; Wen, Weidong; Cui, Haitao; Chen, Bo

2018-06-01

A new method to generate the random distribution of fibers in the transverse cross-section of fiber reinforced composites with high fiber volume fraction is presented in this paper. Based on the microscopy observation of the transverse cross-sections of unidirectional composite laminates, hexagon arrangement is set as the initial arrangement status, and the initial velocity of each fiber is arbitrary at an arbitrary direction, the micro-scale representative volume element (RVE) is established by simulating perfectly elastic collision. Combined with the proposed periodic boundary conditions which are suitable for multi-axial loading, the effective elastic properties of composite materials can be predicted. The predicted properties show reasonable agreement with experimental results. By comparing the stress field of RVE with fibers distributed randomly and RVE with fibers distributed periodically, the predicted elastic modulus of RVE with fibers distributed randomly is greater than RVE with fibers distributed periodically.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media.

PubMed

Crevillén-García, D; Power, H

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

PubMed Central

Power, H.

2017-01-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen–Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error. PMID:28878974

Theoretical comparison and experimental test of the secular and nonperturbative approaches on the ESR lineshapes of randomly oriented, anisotropic systems undergoing internal motion

NASA Astrophysics Data System (ADS)

Benetis, N. P.; Sjöqvist, L.; Lund, A.; Maruani, J.

The nuclear Zeeman and the electronic nonsecular parts of the spin Hamiltonian complicate the ESR lineshape of exchanging anisotropic spin systems by introducing, at high field, "forbidden" transitions and, at low field, additional shift and splitting. We compare the nonperturbative with the secular approach for such systems. The exchange is treated within the Kaplan-Alexander limit and both A and g tensors are included, resulting in spectrum asymmetry, in contrast to previous separate treatments. The two approaches are then used to simulate the powder spectrum of OCH 2COO - and compare the results to experimental spectra of an irradiated powder of ZnAc. The powder X-band spectra simulations using the secular approach appear to be accurate. For both the low-field (20 to 200 G) and the high-field (Q-band) regions, however, the nonsecular part of the electronic term and the nuclear Zeeman term, respectively, cannot be neglected. On the other hand, the approximate approach is much faster and consequently more appropriate for treating large, multisite exchanging systems.

Stochastic inflation lattice simulations - Ultra-large scale structure of the universe

NASA Technical Reports Server (NTRS)

Salopek, D. S.

1991-01-01

Non-Gaussian fluctuations for structure formation may arise in inflation from the nonlinear interaction of long wavelength gravitational and scalar fields. Long wavelength fields have spatial gradients, a (exp -1), small compared to the Hubble radius, and they are described in terms of classical random fields that are fed by short wavelength quantum noise. Lattice Langevin calculations are given for a toy model with a scalar field interacting with an exponential potential where one can obtain exact analytic solutions of the Fokker-Planck equation. For single scalar field models that are consistent with current microwave background fluctuations, the fluctuations are Gaussian. However, for scales much larger than our observable Universe, one expects large metric fluctuations that are non-Gaussian. This example illuminates non-Gaussian models involving multiple scalar fields which are consistent with current microwave background limits.

Molecular-dynamics simulation of polymethylene chain confined in cylindrical potentials. I. Nature of the conformational defects

NASA Astrophysics Data System (ADS)

Yamamoto, Takashi; Kimikawa, Yuichi

1992-10-01

The conformational motion of a polymethylene molecule constrained by a cylindrical potential is simulated up to 100 ps. The molecule consists of 60 CH2 groups and has variable bond lengths, bond angles, and dihedral angles. Our main concern here is the excitation and the dynamics of the conformational defects: kinks, jogs, etc. Under weaker constraint a number of gauche bonds are excited; they mostly form pairs such as gtḡ kinks or gtttḡ jogs. These conformational defects show no continuous drift in space. Instead they often annihilate and then recreate at different sites showing apparently random positional changes. The conformational defects produce characteristic strain fields around them. It seems that the conformational defects interact attractively through these strain fields. This is evidenced by remarkably correlated spatial distributions of the gauche bonds.

Simulating the large-scale structure of HI intensity maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seehars, Sebastian; Paranjape, Aseem; Witzemann, Amadeus

Intensity mapping of neutral hydrogen (HI) is a promising observational probe of cosmology and large-scale structure. We present wide field simulations of HI intensity maps based on N-body simulations of a 2.6 Gpc / h box with 2048{sup 3} particles (particle mass 1.6 × 10{sup 11} M{sub ⊙} / h). Using a conditional mass function to populate the simulated dark matter density field with halos below the mass resolution of the simulation (10{sup 8} M{sub ⊙} / h < M{sub halo} < 10{sup 13} M{sub ⊙} / h), we assign HI to those halos according to a phenomenological halo to HI mass relation. The simulations span a redshift range of 0.35 ∼< z ∼< 0.9 in redshift bins of width Δ z ≈ 0.05 andmore » cover a quarter of the sky at an angular resolution of about 7'. We use the simulated intensity maps to study the impact of non-linear effects and redshift space distortions on the angular clustering of HI. Focusing on the autocorrelations of the maps, we apply and compare several estimators for the angular power spectrum and its covariance. We verify that these estimators agree with analytic predictions on large scales and study the validity of approximations based on Gaussian random fields, particularly in the context of the covariance. We discuss how our results and the simulated maps can be useful for planning and interpreting future HI intensity mapping surveys.« less

The impact of different interstellar medium structures on the dynamical evolution of supernova remnants

NASA Astrophysics Data System (ADS)

Wang, Yueyang; Bao, Biwen; Yang, Chuyuan; Zhang, Li

2018-05-01

The dynamical properties of supernova remnants (SNRs) evolving with different interstellar medium structures are investigated through performing extensive two-dimensional magnetohydrodynamic (MHD) simulations in the cylindrical symmetry. Three cases of different interstellar medium structures are considered: the uniform medium, the turbulent medium and the cloudy medium. Large-scale density and magnetic fluctuations are calculated and mapped into the computational domain before simulations. The clouds are set by random distribution in advance. The above configuration allows us to study the time-dependent dynamical properties and morphological evolution of the SNR evolving with different ambient structures, along with the development of the instabilities at the contact discontinuity. Our simulation results indicate that remnant morphology deviates from symmetry if the interstellar medium contains clouds or turbulent density fluctuations. In the cloudy medium case, interactions between the shock wave and clouds lead to clouds' fragmentation. The magnetic field can be greatly enhanced by stretching field lines with a combination of instabilities while the width of amplification region is quite different among the three cases. Moreover, both the width of amplification region and the maximum magnetic-field strength are closely related to the clouds' density.

Compiling probabilistic, bio-inspired circuits on a field programmable analog array

PubMed Central

Marr, Bo; Hasler, Jennifer

2014-01-01

A field programmable analog array (FPAA) is presented as an energy and computational efficiency engine: a mixed mode processor for which functions can be compiled at significantly less energy costs using probabilistic computing circuits. More specifically, it will be shown that the core computation of any dynamical system can be computed on the FPAA at significantly less energy per operation than a digital implementation. A stochastic system that is dynamically controllable via voltage controlled amplifier and comparator thresholds is implemented, which computes Bernoulli random variables. From Bernoulli variables it is shown exponentially distributed random variables, and random variables of an arbitrary distribution can be computed. The Gillespie algorithm is simulated to show the utility of this system by calculating the trajectory of a biological system computed stochastically with this probabilistic hardware where over a 127X performance improvement over current software approaches is shown. The relevance of this approach is extended to any dynamical system. The initial circuits and ideas for this work were generated at the 2008 Telluride Neuromorphic Workshop. PMID:24847199

Direct Simulation of Multiple Scattering by Discrete Random Media Illuminated by Gaussian Beams

NASA Technical Reports Server (NTRS)

Mackowski, Daniel W.; Mishchenko, Michael I.

2011-01-01

The conventional orientation-averaging procedure developed in the framework of the superposition T-matrix approach is generalized to include the case of illumination by a Gaussian beam (GB). The resulting computer code is parallelized and used to perform extensive numerically exact calculations of electromagnetic scattering by volumes of discrete random medium consisting of monodisperse spherical particles. The size parameters of the scattering volumes are 40, 50, and 60, while their packing density is fixed at 5%. We demonstrate that all scattering patterns observed in the far-field zone of a random multisphere target and their evolution with decreasing width of the incident GB can be interpreted in terms of idealized theoretical concepts such as forward-scattering interference, coherent backscattering (CB), and diffuse multiple scattering. It is shown that the increasing violation of electromagnetic reciprocity with decreasing GB width suppresses and eventually eradicates all observable manifestations of CB. This result supplements the previous demonstration of the effects of broken reciprocity in the case of magneto-optically active particles subjected to an external magnetic field.

Scaling analysis and instantons for thermally assisted tunneling and quantum Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Jiang, Zhang; Smelyanskiy, Vadim N.; Isakov, Sergei V.; Boixo, Sergio; Mazzola, Guglielmo; Troyer, Matthias; Neven, Hartmut

2017-01-01

We develop an instantonic calculus to derive an analytical expression for the thermally assisted tunneling decay rate of a metastable state in a fully connected quantum spin model. The tunneling decay problem can be mapped onto the Kramers escape problem of a classical random dynamical field. This dynamical field is simulated efficiently by path-integral quantum Monte Carlo (QMC). We show analytically that the exponential scaling with the number of spins of the thermally assisted quantum tunneling rate and the escape rate of the QMC process are identical. We relate this effect to the existence of a dominant instantonic tunneling path. The instanton trajectory is described by nonlinear dynamical mean-field theory equations for a single-site magnetization vector, which we solve exactly. Finally, we derive scaling relations for the "spiky" barrier shape when the spin tunneling and QMC rates scale polynomially with the number of spins N while a purely classical over-the-barrier activation rate scales exponentially with N .

Non-Gaussian Multi-resolution Modeling of Magnetosphere-Ionosphere Coupling Processes

NASA Astrophysics Data System (ADS)

Fan, M.; Paul, D.; Lee, T. C. M.; Matsuo, T.

2016-12-01

The most dynamic coupling between the magnetosphere and ionosphere occurs in the Earth's polar atmosphere. Our objective is to model scale-dependent stochastic characteristics of high-latitude ionospheric electric fields that originate from solar wind magnetosphere-ionosphere interactions. The Earth's high-latitude ionospheric electric field exhibits considerable variability, with increasing non-Gaussian characteristics at decreasing spatio-temporal scales. Accurately representing the underlying stochastic physical process through random field modeling is crucial not only for scientific understanding of the energy, momentum and mass exchanges between the Earth's magnetosphere and ionosphere, but also for modern technological systems including telecommunication, navigation, positioning and satellite tracking. While a lot of efforts have been made to characterize the large-scale variability of the electric field in the context of Gaussian processes, no attempt has been made so far to model the small-scale non-Gaussian stochastic process observed in the high-latitude ionosphere. We construct a novel random field model using spherical needlets as building blocks. The double localization of spherical needlets in both spatial and frequency domains enables the model to capture the non-Gaussian and multi-resolutional characteristics of the small-scale variability. The estimation procedure is computationally feasible due to the utilization of an adaptive Gibbs sampler. We apply the proposed methodology to the computational simulation output from the Lyon-Fedder-Mobarry (LFM) global magnetohydrodynamics (MHD) magnetosphere model. Our non-Gaussian multi-resolution model results in characterizing significantly more energy associated with the small-scale ionospheric electric field variability in comparison to Gaussian models. By accurately representing unaccounted-for additional energy and momentum sources to the Earth's upper atmosphere, our novel random field modeling approach will provide a viable remedy to the current numerical models' systematic biases resulting from the underestimation of high-latitude energy and momentum sources.

A stochastic approach to uncertainty in the equations of MHD kinematics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, Edward G., E-mail: egphillips@math.umd.edu; Elman, Howard C., E-mail: elman@cs.umd.edu

2015-03-01

The magnetohydrodynamic (MHD) kinematics model describes the electromagnetic behavior of an electrically conducting fluid when its hydrodynamic properties are assumed to be known. In particular, the MHD kinematics equations can be used to simulate the magnetic field induced by a given velocity field. While prescribing the velocity field leads to a simpler model than the fully coupled MHD system, this may introduce some epistemic uncertainty into the model. If the velocity of a physical system is not known with certainty, the magnetic field obtained from the model may not be reflective of the magnetic field seen in experiments. Additionally, uncertaintymore » in physical parameters such as the magnetic resistivity may affect the reliability of predictions obtained from this model. By modeling the velocity and the resistivity as random variables in the MHD kinematics model, we seek to quantify the effects of uncertainty in these fields on the induced magnetic field. We develop stochastic expressions for these quantities and investigate their impact within a finite element discretization of the kinematics equations. We obtain mean and variance data through Monte Carlo simulation for several test problems. Toward this end, we develop and test an efficient block preconditioner for the linear systems arising from the discretized equations.« less

Efficient prediction designs for random fields.

PubMed

Müller, Werner G; Pronzato, Luc; Rendas, Joao; Waldl, Helmut

2015-03-01

For estimation and predictions of random fields, it is increasingly acknowledged that the kriging variance may be a poor representative of true uncertainty. Experimental designs based on more elaborate criteria that are appropriate for empirical kriging (EK) are then often non-space-filling and very costly to determine. In this paper, we investigate the possibility of using a compound criterion inspired by an equivalence theorem type relation to build designs quasi-optimal for the EK variance when space-filling designs become unsuitable. Two algorithms are proposed, one relying on stochastic optimization to explicitly identify the Pareto front, whereas the second uses the surrogate criteria as local heuristic to choose the points at which the (costly) true EK variance is effectively computed. We illustrate the performance of the algorithms presented on both a simple simulated example and a real oceanographic dataset. © 2014 The Authors. Applied Stochastic Models in Business and Industry published by John Wiley & Sons, Ltd.

Dynamical transition for a particle in a squared Gaussian potential

NASA Astrophysics Data System (ADS)

Touya, C.; Dean, D. S.

2007-02-01

We study the problem of a Brownian particle diffusing in finite dimensions in a potential given by ψ = phi2/2 where phi is Gaussian random field. Exact results for the diffusion constant in the high temperature phase are given in one and two dimensions and it is shown to vanish in a power-law fashion at the dynamical transition temperature. Our results are confronted with numerical simulations where the Gaussian field is constructed, in a standard way, as a sum over random Fourier modes. We show that when the number of Fourier modes is finite the low temperature diffusion constant becomes non-zero and has an Arrhenius form. Thus we have a simple model with a fully understood finite size scaling theory for the dynamical transition. In addition we analyse the nature of the anomalous diffusion in the low temperature regime and show that the anomalous exponent agrees with that predicted by a trap model.

Assessing the significance of global and local correlations under spatial autocorrelation: a nonparametric approach.

PubMed

Viladomat, Júlia; Mazumder, Rahul; McInturff, Alex; McCauley, Douglas J; Hastie, Trevor

2014-06-01

We propose a method to test the correlation of two random fields when they are both spatially autocorrelated. In this scenario, the assumption of independence for the pair of observations in the standard test does not hold, and as a result we reject in many cases where there is no effect (the precision of the null distribution is overestimated). Our method recovers the null distribution taking into account the autocorrelation. It uses Monte-Carlo methods, and focuses on permuting, and then smoothing and scaling one of the variables to destroy the correlation with the other, while maintaining at the same time the initial autocorrelation. With this simulation model, any test based on the independence of two (or more) random fields can be constructed. This research was motivated by a project in biodiversity and conservation in the Biology Department at Stanford University. © 2014, The International Biometric Society.

Screening effects in flow through rough channels.

PubMed

Andrade, J S; Araújo, A D; Filoche, M; Sapoval, B

2007-05-11

A surprising similarity is found between the distribution of hydrodynamic stress on the wall of an irregular channel and the distribution of flux from a purely Laplacian field on the same geometry. This finding is a direct outcome of numerical simulations of the Navier-Stokes equations for flow at low Reynolds numbers in two-dimensional channels with rough walls presenting either deterministic or random self-similar geometries. For high Reynolds numbers, the distribution of wall stresses on deterministic and random fractal rough channels becomes substantially dependent on the microscopic details of the walls geometry. Finally, the effects on the flow behavior of the channel symmetry and aspect ratio are also investigated.

Single realization stochastic FDTD for weak scattering waves in biological random media.

PubMed

Tan, Tengmeng; Taflove, Allen; Backman, Vadim

2013-02-01

This paper introduces an iterative scheme to overcome the unresolved issues presented in S-FDTD (stochastic finite-difference time-domain) for obtaining ensemble average field values recently reported by Smith and Furse in an attempt to replace the brute force multiple-realization also known as Monte-Carlo approach with a single-realization scheme. Our formulation is particularly useful for studying light interactions with biological cells and tissues having sub-wavelength scale features. Numerical results demonstrate that such a small scale variation can be effectively modeled with a random medium problem which when simulated with the proposed S-FDTD indeed produces a very accurate result.

Single realization stochastic FDTD for weak scattering waves in biological random media

PubMed Central

Tan, Tengmeng; Taflove, Allen; Backman, Vadim

2015-01-01

This paper introduces an iterative scheme to overcome the unresolved issues presented in S-FDTD (stochastic finite-difference time-domain) for obtaining ensemble average field values recently reported by Smith and Furse in an attempt to replace the brute force multiple-realization also known as Monte-Carlo approach with a single-realization scheme. Our formulation is particularly useful for studying light interactions with biological cells and tissues having sub-wavelength scale features. Numerical results demonstrate that such a small scale variation can be effectively modeled with a random medium problem which when simulated with the proposed S-FDTD indeed produces a very accurate result. PMID:27158153

Effects of ignition location models on the burn patterns of simulated wildfires

USGS Publications Warehouse

Bar-Massada, A.; Syphard, A.D.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

2011-01-01

Fire simulation studies that use models such as FARSITE often assume that ignition locations are distributed randomly, because spatially explicit information about actual ignition locations are difficult to obtain. However, many studies show that the spatial distribution of ignition locations, whether human-caused or natural, is non-random. Thus, predictions from fire simulations based on random ignitions may be unrealistic. However, the extent to which the assumption of ignition location affects the predictions of fire simulation models has never been systematically explored. Our goal was to assess the difference in fire simulations that are based on random versus non-random ignition location patterns. We conducted four sets of 6000 FARSITE simulations for the Santa Monica Mountains in California to quantify the influence of random and non-random ignition locations and normal and extreme weather conditions on fire size distributions and spatial patterns of burn probability. Under extreme weather conditions, fires were significantly larger for non-random ignitions compared to random ignitions (mean area of 344.5 ha and 230.1 ha, respectively), but burn probability maps were highly correlated (r = 0.83). Under normal weather, random ignitions produced significantly larger fires than non-random ignitions (17.5 ha and 13.3 ha, respectively), and the spatial correlations between burn probability maps were not high (r = 0.54), though the difference in the average burn probability was small. The results of the study suggest that the location of ignitions used in fire simulation models may substantially influence the spatial predictions of fire spread patterns. However, the spatial bias introduced by using a random ignition location model may be minimized if the fire simulations are conducted under extreme weather conditions when fire spread is greatest. ?? 2010 Elsevier Ltd.

Atomistic simulation on charge mobility of amorphous tris(8-hydroxyquinoline) aluminum (Alq3): origin of Poole-Frenkel-type behavior.

PubMed

Nagata, Yuki; Lennartz, Christian

2008-07-21

The atomistic simulation of charge transfer process for an amorphous Alq(3) system is reported. By employing electrostatic potential charges, we calculate site energies and find that the standard deviation of site energy distribution is about twice as large as predicted in previous research. The charge mobility is calculated via the Miller-Abrahams formalism and the master equation approach. We find that the wide site energy distribution governs Poole-Frenkel-type behavior of charge mobility against electric field, while the spatially correlated site energy is not a dominant mechanism of Poole-Frenkel behavior in the range from 2x10(5) to 1.4x10(6) V/cm. Also we reveal that randomly meshed connectivities are, in principle, required to account for the Poole-Frenkel mechanism. Charge carriers find a zigzag pathway at low electric field, while they find a straight pathway along electric field when a high electric field is applied. In the space-charge-limited current scheme, the charge-carrier density increases with electric field strength so that the nonlinear behavior of charge mobility is enhanced through the strong charge-carrier density dependence of charge mobility.

A Numerical Simulation of Scattering from One-Dimensional Inhomogeneous Dielectric Random Surfaces

NASA Technical Reports Server (NTRS)

Sarabandi, Kamal; Oh, Yisok; Ulaby, Fawwaz T.

1996-01-01

In this paper, an efficient numerical solution for the scattering problem of inhomogeneous dielectric rough surfaces is presented. The inhomogeneous dielectric random surface represents a bare soil surface and is considered to be comprised of a large number of randomly positioned dielectric humps of different sizes, shapes, and dielectric constants above an impedance surface. Clods with nonuniform moisture content and rocks are modeled by inhomogeneous dielectric humps and the underlying smooth wet soil surface is modeled by an impedance surface. In this technique, an efficient numerical solution for the constituent dielectric humps over an impedance surface is obtained using Green's function derived by the exact image theory in conjunction with the method of moments. The scattered field from a sample of the rough surface is obtained by summing the scattered fields from all the individual humps of the surface coherently ignoring the effect of multiple scattering between the humps. The statistical behavior of the scattering coefficient sigma(sup 0) is obtained from the calculation of scattered fields of many different realizations of the surface. Numerical results are presented for several different roughnesses and dielectric constants of the random surfaces. The numerical technique is verified by comparing the numerical solution with the solution based on the small perturbation method and the physical optics model for homogeneous rough surfaces. This technique can be used to study the behavior of scattering coefficient and phase difference statistics of rough soil surfaces for which no analytical solution exists.

Robust spectral-domain optical coherence tomography speckle model and its cross-correlation coefficient analysis

PubMed Central

Liu, Xuan; Ramella-Roman, Jessica C.; Huang, Yong; Guo, Yuan; Kang, Jin U.

2013-01-01

In this study, we proposed a generic speckle simulation for optical coherence tomography (OCT) signal, by convolving the point spread function (PSF) of the OCT system with the numerically synthesized random sample field. We validated our model and used the simulation method to study the statistical properties of cross-correlation coefficients (XCC) between Ascans which have been recently applied in transverse motion analysis by our group. The results of simulation show that over sampling is essential for accurate motion tracking; exponential decay of OCT signal leads to an under estimate of motion which can be corrected; lateral heterogeneity of sample leads to an over estimate of motion for a few pixels corresponding to the structural boundary. PMID:23456001

Three-dimensional simulations of the orientation and structure of reconnection X-lines

NASA Astrophysics Data System (ADS)

Schreier, R.; Swisdak, M.; Drake, J. F.; Cassak, P. A.

2010-11-01

This letter employs Hall magnetohydrodynamic simulations to study X-lines formed during the reconnection of magnetic fields with differing strengths and orientations embedded in plasmas of differing densities. Although random initial perturbations trigger the growth of X-lines with many orientations, a few robust X-lines sharing an orientation consistent with the direction of maximal outflow speed, as predicted by Swisdak and Drake [Geophys. Res. Lett. 34, L11106 (2007)] eventually dominate the system. Reconnection in the geometry examined here contradicts the suggestion of Sonnerup [J. Geophys. Res. 79, 1546 (1974)] that it occurs in a plane normal to the equilibrium current. At late time, the X-lines' growth stagnates, leaving them shorter than the simulation domain.

Computational algorithms for simulations in atmospheric optics.

PubMed

Konyaev, P A; Lukin, V P

2016-04-20

A computer simulation technique for atmospheric and adaptive optics based on parallel programing is discussed. A parallel propagation algorithm is designed and a modified spectral-phase method for computer generation of 2D time-variant random fields is developed. Temporal power spectra of Laguerre-Gaussian beam fluctuations are considered as an example to illustrate the applications discussed. Implementation of the proposed algorithms using Intel MKL and IPP libraries and NVIDIA CUDA technology is shown to be very fast and accurate. The hardware system for the computer simulation is an off-the-shelf desktop with an Intel Core i7-4790K CPU operating at a turbo-speed frequency up to 5 GHz and an NVIDIA GeForce GTX-960 graphics accelerator with 1024 1.5 GHz processors.

On the radial evolution of reflection-driven turbulence in the inner solar wind in preparation for Parker Solar Probe

NASA Astrophysics Data System (ADS)

Perez, J. C.; Chandran, B. D. G.

2017-12-01

In this work we present recent results from high-resolution direct numerical simulations and a phenomenological model that describes the radial evolution of reflection-driven Alfven Wave turbulence in the solar atmosphere and the inner solar wind. The simulations are performed inside a narrow magnetic flux tube that models a coronal hole extending from the solar surface through the chromosphere and into the solar corona to approximately 21 solar radii. The simulations include prescribed empirical profiles that account for the inhomogeneities in density, background flow, and the background magnetic field present in coronal holes. Alfven waves are injected into the solar corona by imposing random, time-dependent velocity and magnetic field fluctuations at the photosphere. The phenomenological model incorporates three important features observed in the simulations: dynamic alignment, weak/strong nonlinear AW-AW interactions, and that the outward-propagating AWs launched by the Sun split into two populations with different characteristic frequencies. Model and simulations are in good agreement and show that when the key physical parameters are chosen within observational constraints, reflection-driven Alfven turbulence is a plausible mechanism for the heating and acceleration of the fast solar wind. By flying a virtual Parker Solar Probe (PSP) through the simulations, we will also establish comparisons between the model and simulations with the kind of single-point measurements that PSP will provide.

Oculo-vestibular recoupling using galvanic vestibular stimulation to mitigate simulator sickness.

PubMed

Cevette, Michael J; Stepanek, Jan; Cocco, Daniela; Galea, Anna M; Pradhan, Gaurav N; Wagner, Linsey S; Oakley, Sarah R; Smith, Benn E; Zapala, David A; Brookler, Kenneth H

2012-06-01

Despite improvement in the computational capabilities of visual displays in flight simulators, intersensory visual-vestibular conflict remains the leading cause of simulator sickness (SS). By using galvanic vestibular stimulation (GVS), the vestibular system can be synchronized with a moving visual field in order to lessen the mismatch of sensory inputs thought to result in SS. A multisite electrode array was used to deliver combinations of GVS in 21 normal subjects. Optimal electrode combinations were identified and used to establish GVS dose-response predictions for the perception of roll, pitch, and yaw. Based on these data, an algorithm was then implemented in flight simulator hardware in order to synchronize visual and GVS-induced vestibular sensations (oculo-vestibular-recoupled or OVR simulation). Subjects were then randomly exposed to flight simulation either with or without OVR simulation. A self-report SS checklist was administered to all subjects after each session. An overall SS score was calculated for each category of symptoms for both groups. The analysis of GVS stimulation data yielded six unique combinations of electrode positions inducing motion perceptions in the three rotational axes. This provided the algorithm used for OVR simulation. The overall SS scores for gastrointestinal, central, and peripheral categories were 17%, 22.4%, and 20% for the Control group and 6.3%, 20%, and 8% for the OVR group, respectively. When virtual head signals produced by GVS are synchronized to the speed and direction of a moving visual field, manifestations of induced SS in a cockpit flight simulator are significantly reduced.

Stochastical analysis of surfactant-enhanced remediation of denser-than-water nonaqueous phase liquid (DNAPL)-contaminated soils.

PubMed

Zhang, Renduo; Wood, A Lynn; Enfield, Carl G; Jeong, Seung-Woo

2003-01-01

Stochastical analysis was performed to assess the effect of soil spatial variability and heterogeneity on the recovery of denser-than-water nonaqueous phase liquids (DNAPL) during the process of surfactant-enhanced remediation. UTCHEM, a three-dimensional, multicomponent, multiphase, compositional model, was used to simulate water flow and chemical transport processes in heterogeneous soils. Soil spatial variability and heterogeneity were accounted for by considering the soil permeability as a spatial random variable and a geostatistical method was used to generate random distributions of the permeability. The randomly generated permeability fields were incorporated into UTCHEM to simulate DNAPL transport in heterogeneous media and stochastical analysis was conducted based on the simulated results. From the analysis, an exponential relationship between average DNAPL recovery and soil heterogeneity (defined as the standard deviation of log of permeability) was established with a coefficient of determination (r2) of 0.991, which indicated that DNAPL recovery decreased exponentially with increasing soil heterogeneity. Temporal and spatial distributions of relative saturations in the water phase, DNAPL, and microemulsion in heterogeneous soils were compared with those in homogeneous soils and related to soil heterogeneity. Cleanup time and uncertainty to determine DNAPL distributions in heterogeneous soils were also quantified. The study would provide useful information to design strategies for the characterization and remediation of nonaqueous phase liquid-contaminated soils with spatial variability and heterogeneity.

Evaluation of high-resolution sea ice models on the basis of statistical and scaling properties of Arctic sea ice drift and deformation

NASA Astrophysics Data System (ADS)

Girard, L.; Weiss, J.; Molines, J. M.; Barnier, B.; Bouillon, S.

2009-08-01

Sea ice drift and deformation from models are evaluated on the basis of statistical and scaling properties. These properties are derived from two observation data sets: the RADARSAT Geophysical Processor System (RGPS) and buoy trajectories from the International Arctic Buoy Program (IABP). Two simulations obtained with the Louvain-la-Neuve Ice Model (LIM) coupled to a high-resolution ocean model and a simulation obtained with the Los Alamos Sea Ice Model (CICE) were analyzed. Model ice drift compares well with observations in terms of large-scale velocity field and distributions of velocity fluctuations although a significant bias on the mean ice speed is noted. On the other hand, the statistical properties of ice deformation are not well simulated by the models: (1) The distributions of strain rates are incorrect: RGPS distributions of strain rates are power law tailed, i.e., exhibit "wild randomness," whereas models distributions remain in the Gaussian attraction basin, i.e., exhibit "mild randomness." (2) The models are unable to reproduce the spatial and temporal correlations of the deformation fields: In the observations, ice deformation follows spatial and temporal scaling laws that express the heterogeneity and the intermittency of deformation. These relations do not appear in simulated ice deformation. Mean deformation in models is almost scale independent. The statistical properties of ice deformation are a signature of the ice mechanical behavior. The present work therefore suggests that the mechanical framework currently used by models is inappropriate. A different modeling framework based on elastic interactions could improve the representation of the statistical and scaling properties of ice deformation.

Adaptive multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model

NASA Astrophysics Data System (ADS)

Navarro, Cristóbal A.; Huang, Wei; Deng, Youjin

2016-08-01

This work presents an adaptive multi-GPU Exchange Monte Carlo approach for the simulation of the 3D Random Field Ising Model (RFIM). The design is based on a two-level parallelization. The first level, spin-level parallelism, maps the parallel computation as optimal 3D thread-blocks that simulate blocks of spins in shared memory with minimal halo surface, assuming a constant block volume. The second level, replica-level parallelism, uses multi-GPU computation to handle the simulation of an ensemble of replicas. CUDA's concurrent kernel execution feature is used in order to fill the occupancy of each GPU with many replicas, providing a performance boost that is more notorious at the smallest values of L. In addition to the two-level parallel design, the work proposes an adaptive multi-GPU approach that dynamically builds a proper temperature set free of exchange bottlenecks. The strategy is based on mid-point insertions at the temperature gaps where the exchange rate is most compromised. The extra work generated by the insertions is balanced across the GPUs independently of where the mid-point insertions were performed. Performance results show that spin-level performance is approximately two orders of magnitude faster than a single-core CPU version and one order of magnitude faster than a parallel multi-core CPU version running on 16-cores. Multi-GPU performance is highly convenient under a weak scaling setting, reaching up to 99 % efficiency as long as the number of GPUs and L increase together. The combination of the adaptive approach with the parallel multi-GPU design has extended our possibilities of simulation to sizes of L = 32 , 64 for a workstation with two GPUs. Sizes beyond L = 64 can eventually be studied using larger multi-GPU systems.

Study on the mapping of dark matter clustering from real space to redshift space

NASA Astrophysics Data System (ADS)

Zheng, Yi; Song, Yong-Seon

2016-08-01

The mapping of dark matter clustering from real space to redshift space introduces the anisotropic property to the measured density power spectrum in redshift space, known as the redshift space distortion effect. The mapping formula is intrinsically non-linear, which is complicated by the higher order polynomials due to indefinite cross correlations between the density and velocity fields, and the Finger-of-God effect due to the randomness of the peculiar velocity field. Whilst the full higher order polynomials remain unknown, the other systematics can be controlled consistently within the same order truncation in the expansion of the mapping formula, as shown in this paper. The systematic due to the unknown non-linear density and velocity fields is removed by separately measuring all terms in the expansion directly using simulations. The uncertainty caused by the velocity randomness is controlled by splitting the FoG term into two pieces, 1) the ``one-point" FoG term being independent of the separation vector between two different points, and 2) the ``correlated" FoG term appearing as an indefinite polynomials which is expanded in the same order as all other perturbative polynomials. Using 100 realizations of simulations, we find that the Gaussian FoG function with only one scale-independent free parameter works quite well, and that our new mapping formulation accurately reproduces the observed 2-dimensional density power spectrum in redshift space at the smallest scales by far, up to k~ 0.2 Mpc-1, considering the resolution of future experiments.

Effects of Uncertainties in Electric Field Boundary Conditions for Ring Current Simulations

NASA Astrophysics Data System (ADS)

Chen, Margaret W.; O'Brien, T. Paul; Lemon, Colby L.; Guild, Timothy B.

2018-01-01

Physics-based simulation results can vary widely depending on the applied boundary conditions. As a first step toward assessing the effect of boundary conditions on ring current simulations, we analyze the uncertainty of cross-polar cap potentials (CPCP) on electric field boundary conditions applied to the Rice Convection Model-Equilibrium (RCM-E). The empirical Weimer model of CPCP is chosen as the reference model and Defense Meteorological Satellite Program CPCP measurements as the reference data. Using temporal correlations from a statistical analysis of the "errors" between the reference model and data, we construct a Monte Carlo CPCP discrete time series model that can be generalized to other model boundary conditions. RCM-E simulations using electric field boundary conditions from the reference model and from 20 randomly generated Monte Carlo discrete time series of CPCP are performed for two large storms. During the 10 August 2000 storm main phase, the proton density at 10 RE at midnight was observed to be low (< 1.4 cm-3) and the observed disturbance Dst index is bounded by the simulated Dst values. In contrast, the simulated Dst values during the recovery phases of the 10 August 2000 and 31 August 2005 storms tend to underestimate systematically the observed late Dst recovery. This suggests a need to improve the accuracy of particle loss calculations in the RCM-E model. Application of this technique can aid modelers to make efficient choices on either investing more effort on improving specification of boundary conditions or on improving descriptions of physical processes.

Self-diffusion in periodic porous media: a comparison of numerical simulation and eigenvalue methods.

PubMed

Schwartz, L M; Bergman, D J; Dunn, K J; Mitra, P P

1996-01-01

Random walk computer simulations are an important tool in understanding magnetic resonance measurements in porous media. In this paper we focus on the description of pulsed field gradient spin echo (PGSE) experiments that measure the probability, P(R,t), that a diffusing water molecule will travel a distance R in a time t. Because PGSE simulations are often limited by statistical considerations, we will see that valuable insight can be gained by working with simple periodic geometries and comparing simulation data to the results of exact eigenvalue expansions. In this connection, our attention will be focused on (1) the wavevector, k, and time dependent magnetization, M(k, t); and (2) the normalized probability, Ps(delta R, t), that a diffusing particle will return to within delta R of the origin after time t.

Parallel tempering simulation of the three-dimensional Edwards-Anderson model with compact asynchronous multispin coding on GPU

NASA Astrophysics Data System (ADS)

Fang, Ye; Feng, Sheng; Tam, Ka-Ming; Yun, Zhifeng; Moreno, Juana; Ramanujam, J.; Jarrell, Mark

2014-10-01

Monte Carlo simulations of the Ising model play an important role in the field of computational statistical physics, and they have revealed many properties of the model over the past few decades. However, the effect of frustration due to random disorder, in particular the possible spin glass phase, remains a crucial but poorly understood problem. One of the obstacles in the Monte Carlo simulation of random frustrated systems is their long relaxation time making an efficient parallel implementation on state-of-the-art computation platforms highly desirable. The Graphics Processing Unit (GPU) is such a platform that provides an opportunity to significantly enhance the computational performance and thus gain new insight into this problem. In this paper, we present optimization and tuning approaches for the CUDA implementation of the spin glass simulation on GPUs. We discuss the integration of various design alternatives, such as GPU kernel construction with minimal communication, memory tiling, and look-up tables. We present a binary data format, Compact Asynchronous Multispin Coding (CAMSC), which provides an additional 28.4% speedup compared with the traditionally used Asynchronous Multispin Coding (AMSC). Our overall design sustains a performance of 33.5 ps per spin flip attempt for simulating the three-dimensional Edwards-Anderson model with parallel tempering, which significantly improves the performance over existing GPU implementations.

On grey levels in random CAPTCHA generation

NASA Astrophysics Data System (ADS)

Newton, Fraser; Kouritzin, Michael A.

2011-06-01

A CAPTCHA is an automatically generated test designed to distinguish between humans and computer programs; specifically, they are designed to be easy for humans but difficult for computer programs to pass in order to prevent the abuse of resources by automated bots. They are commonly seen guarding webmail registration forms, online auction sites, and preventing brute force attacks on passwords. In the following, we address the question: How does adding a grey level to random CAPTCHA generation affect the utility of the CAPTCHA? We treat the problem of generating the random CAPTCHA as one of random field simulation: An initial state of background noise is evolved over time using Gibbs sampling and an efficient algorithm for generating correlated random variables. This approach has already been found to yield highly-readable yet difficult-to-crack CAPTCHAs. We detail how the requisite parameters for introducing grey levels are estimated and how we generate the random CAPTCHA. The resulting CAPTCHA will be evaluated in terms of human readability as well as its resistance to automated attacks in the forms of character segmentation and optical character recognition.

Punch Response of Gels at Different Loading Rates

DTIC Science & Technology

2014-03-01

calibration (4, 6). While similar in density, neither clay nor gelatin simulates the tissue structure of the human body accurately. Danelson et al. (7...the load response of human tissue. 2 Recent work on gelatins has shown promise in robotics, sensors, and microfluidics (9). Hydrogels ( water -based...images of a high-contrast, random pattern of speckles and a sophisticated optimization program to measure full-field deformation. Figure 1 shows an

Effect of aberration on the acoustic field in tissue harmonic imaging (THI)

NASA Astrophysics Data System (ADS)

Jing, Yuan; Cleveland, Robin

2003-10-01

A numerical simulation was used to study the impact of an aberrating layer on the generation of the fundamental and second-harmonic (SH) field in a tissue harmonic imaging scenario. The simulation used a three-dimensional time-domain code for solving the KZK equation and accounted for arbitrary spatial variations in all acoustic properties. The aberration effect was modeled by assuming that the tissue consisted of two layers where the interface has a spatial variation C that acted like an effective phase screen. Initial experiments were carried out with sinusoidal-shaped interfaces. The sinusoidal interface produced grating lobes which were at least 6 dB larger for the fundamental signal than the SH. The energy outside of the main lobe was found to increase linearly as the amplitude of the interface variation increased. The location of the grating lobes was affected by the spatial period on the interface variation. The inhomogeneous nature of tissue was modeled with an interface with a random spatial variation. With the random interface the average sidelobe level for the fundamental was -30 dB whereas the SH had an average sidelobe level of -36 dB. [Work supported by the NSF through the Center for Subsurface Sensing and Imaging Systems.

Correlations and analytical approaches to co-evolving voter models

NASA Astrophysics Data System (ADS)

Ji, M.; Xu, C.; Choi, C. W.; Hui, P. M.

2013-11-01

The difficulty in formulating analytical treatments in co-evolving networks is studied in light of the Vazquez-Eguíluz-San Miguel voter model (VM) and a modified VM (MVM) that introduces a random mutation of the opinion as a noise in the VM. The density of active links, which are links that connect the nodes of opposite opinions, is shown to be highly sensitive to both the degree k of a node and the active links n among the neighbors of a node. We test the validity in the formalism of analytical approaches and show explicitly that the assumptions behind the commonly used homogeneous pair approximation scheme in formulating a mean-field theory are the source of the theory's failure due to the strong correlations between k, n and n2. An improved approach that incorporates spatial correlation to the nearest-neighbors explicitly and a random approximation for the next-nearest neighbors is formulated for the VM and the MVM, and it gives better agreement with the simulation results. We introduce an empirical approach that quantifies the correlations more accurately and gives results in good agreement with the simulation results. The work clarifies why simply mean-field theory fails and sheds light on how to analyze the correlations in the dynamic equations that are often generated in co-evolving processes.

Magnetic Field Line Random Walk in Arbitrarily Stretched Isotropic Turbulence

NASA Astrophysics Data System (ADS)

Wongpan, P.; Ruffolo, D.; Matthaeus, W. H.; Rowlands, G.

2006-12-01

Many types of space and laboratory plasmas involve turbulent fluctuations with an approximately uniform mean magnetic field B_0, and the field line random walk plays an important role in guiding particle motions. Much of the relevant literature concerns isotropic turbulence, and has mostly been perturbative, i.e., for small fluctuations, or based on numerical simulations for specific conditions. On the other hand, solar wind turbulence is apparently anisotropic, and has been modeled as a sum of idealized two-dimensional and one dimensional (slab) components, but with the deficiency of containing no oblique wave vectors. In the present work, we address the above issues with non-perturbative analytic calculations of diffusive field line random walks for unpolarized, arbitrarily stretched isotropic turbulence, including the limits of nearly one-dimensional (highly stretched) and nearly two-dimensional (highly squashed) turbulence. We develop implicit analytic formulae for the diffusion coefficients D_x and D_z, two coupled integral equations in which D_x and D_z appear inside 3-dimensional integrals over all k-space, are solved numerically with the aid of Mathematica routines for specific cases. We can vary the parameters B0 and β, the stretching along z for constant turbulent energy. Furthermore, we obtain analytic closed-form solutions in all extreme cases. We obtain 0.54 < D_z/D_x < 2, indicating an approximately isotropic random walk even for very anisotropic (unpolarized) turbulence, a surprising result. For a given β, the diffusion coefficient vs. B0 can be described by a Padé approximant. We find quasilinear behavior at high B0 and percolative behavior at low B_0. Partially supported by a Sritrangthong Scholarship from the Faculty of Science, Mahidol University; the Thailand Research Fund; NASA Grant NNG05GG83G; and Thailand's Commission for Higher Education.

Impurity migration pattern under RF sheath potential in tokamak and the response of Plasma to RMP

NASA Astrophysics Data System (ADS)

Xiao, Xiaotao; Gui, Bin; Xia, Tianyang; Xu, Xueqiao; Sun, Youwen

2017-10-01

The migration pattern of impurity sputtered from RF guarder limiter, is simulated by a test particle module. The electric potential with RF sheath boundary condition on the guard limiter and the thermal sheath boundary condition on the divertor surface are used. The turbulence transport is implemented by random walk model. It is found the RF sheath potential enhances the impurity percentage lost at low filed side middle plane, and decreases impurity percentage drifting into core region. This beneficial effect is stronger when sheath potential is large. When turbulence transport is strong enough, their migration pattern will be dominated by transport, not by sheath potential. The Resonant Magnetic field Perturbation (RMP) is successfully applied in EAST experiment and the suppression and mitigation effect on ELM is obtained. A two field fluid model is used to simulate the plasma response to RMP in EAST geometry. The current sheet on the resonance surface is obtained initially and the resonant component of radial magnetic field is suppressed there. With plasma rotation, the Alfven resonance occurs and the current is separated into two current sheets. The simulation result will be integrated with the ELM simulations to study the effects of RMP on ELM. Prepared by LLNL under Contract DE-AC52-07NA27344 and the China Natural Science Foundation under Contract No. 11405215, 11505236 and 11675217.

Ponderomotive Acceleration in Coronal Loops

NASA Astrophysics Data System (ADS)

Dahlburg, Russell B.; Laming, J. Martin; Taylor, Brian; Obenschain, Keith

2017-08-01

Ponderomotive acceleration has been asserted to be a cause of the First Ionization Potential (FIP) effect, the by now well known enhancement in abundance by a factor of 3-4 over photospheric values of elements in the solar corona with FIP less than about 10 eV. It is shown here by means of numerical simulations that ponderomotive acceleration occurs in solar coronal loops, with the appropriate magnitude and direction, as a ``byproduct'' of coronal heating. The numerical simulations are performed with the HYPERION code, which solves the fully compressible three-dimensional magnetohydrodynamic equations including nonlinear thermal conduction and optically thin radiation. Numerical simulations of a coronal loops with an axial magnetic field from 0.005 Teslas to 0.02 Teslas and lengths from 25000 km to 75000 km are presented. In the simulations the footpoints of the axial loop magnetic field are convected by random, large-scale motions. There is a continuous formation and dissipation of field-aligned current sheets which act to heat the loop. As a consequence of coronal magnetic reconnection, small scale, high speed jets form. The familiar vortex quadrupoles form at reconnection sites. Between the magnetic footpoints and the corona the reconnection flow merges with the boundary flow. It is in this region that the ponderomotive acceleration occurs. Mirroring the character of the coronal reconnection, the ponderomotive acceleration is also found to be intermittent.

The SILCC (SImulating the LifeCycle of molecular Clouds) project - I. Chemical evolution of the supernova-driven ISM

NASA Astrophysics Data System (ADS)

Walch, S.; Girichidis, P.; Naab, T.; Gatto, A.; Glover, S. C. O.; Wünsch, R.; Klessen, R. S.; Clark, P. C.; Peters, T.; Derigs, D.; Baczynski, C.

2015-11-01

The SILCC (SImulating the Life-Cycle of molecular Clouds) project aims to self-consistently understand the small-scale structure of the interstellar medium (ISM) and its link to galaxy evolution. We simulate the evolution of the multiphase ISM in a (500 pc)2 × ±5 kpc region of a galactic disc, with a gas surface density of Σ _{_GAS} = 10 M_{⊙} pc^{-2}. The FLASH 4 simulations include an external potential, self-gravity, magnetic fields, heating and radiative cooling, time-dependent chemistry of H2 and CO considering (self-) shielding, and supernova (SN) feedback but omit shear due to galactic rotation. We explore SN explosions at different rates in high-density regions (peak), in random locations with a Gaussian distribution in the vertical direction (random), in a combination of both (mixed), or clustered in space and time (clus/clus2). Only models with self-gravity and a significant fraction of SNe that explode in low-density gas are in agreement with observations. Without self-gravity and in models with peak driving the formation of H2 is strongly suppressed. For decreasing SN rates, the H2 mass fraction increases significantly from <10 per cent for high SN rates, i.e. 0.5 dex above Kennicutt-Schmidt, to 70-85 per cent for low SN rates, i.e. 0.5 dex below KS. For an intermediate SN rate, clustered driving results in slightly more H2 than random driving due to the more coherent compression of the gas in larger bubbles. Magnetic fields have little impact on the final disc structure but affect the dense gas (n ≳ 10 cm-3) and delay H2 formation. Most of the volume is filled with hot gas (˜80 per cent within ±150 pc). For all but peak driving a vertically expanding warm component of atomic hydrogen indicates a fountain flow. We highlight that individual chemical species populate different ISM phases and cannot be accurately modelled with temperature-/density-based phase cut-offs.

Modeling the influence of preferential flow on the spatial variability and time-dependence of mineral weathering rates

DOE PAGES

Pandey, Sachin; Rajaram, Harihar

2016-12-05

Inferences of weathering rates from laboratory and field observations suggest significant scale and time-dependence. Preferential flow induced by heterogeneity (manifest as permeability variations or discrete fractures) has been suggested as one potential mechanism causing scale/time-dependence. In this paper, we present a quantitative evaluation of the influence of preferential flow on weathering rates using reactive transport modeling. Simulations were performed in discrete fracture networks (DFNs) and correlated random permeability fields (CRPFs), and compared to simulations in homogeneous permeability fields. The simulations reveal spatial variability in the weathering rate, multidimensional distribution of reactions zones, and the formation of rough weathering interfaces andmore » corestones due to preferential flow. In the homogeneous fields and CRPFs, the domain-averaged weathering rate is initially constant as long as the weathering front is contained within the domain, reflecting equilibrium-controlled behavior. The behavior in the CRPFs was influenced by macrodispersion, with more spread-out weathering profiles, an earlier departure from the initial constant rate and longer persistence of weathering. DFN simulations exhibited a sustained time-dependence resulting from the formation of diffusion-controlled weathering fronts in matrix blocks, which is consistent with the shrinking core mechanism. A significant decrease in the domain-averaged weathering rate is evident despite high remaining mineral volume fractions, but the decline does not follow a math formula dependence, characteristic of diffusion, due to network scale effects and advection-controlled behavior near the inflow boundary. Finally, the DFN simulations also reveal relatively constant horizontally averaged weathering rates over a significant depth range, challenging the very notion of a weathering front.« less

Modeling the influence of preferential flow on the spatial variability and time-dependence of mineral weathering rates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pandey, Sachin; Rajaram, Harihar

Inferences of weathering rates from laboratory and field observations suggest significant scale and time-dependence. Preferential flow induced by heterogeneity (manifest as permeability variations or discrete fractures) has been suggested as one potential mechanism causing scale/time-dependence. In this paper, we present a quantitative evaluation of the influence of preferential flow on weathering rates using reactive transport modeling. Simulations were performed in discrete fracture networks (DFNs) and correlated random permeability fields (CRPFs), and compared to simulations in homogeneous permeability fields. The simulations reveal spatial variability in the weathering rate, multidimensional distribution of reactions zones, and the formation of rough weathering interfaces andmore » corestones due to preferential flow. In the homogeneous fields and CRPFs, the domain-averaged weathering rate is initially constant as long as the weathering front is contained within the domain, reflecting equilibrium-controlled behavior. The behavior in the CRPFs was influenced by macrodispersion, with more spread-out weathering profiles, an earlier departure from the initial constant rate and longer persistence of weathering. DFN simulations exhibited a sustained time-dependence resulting from the formation of diffusion-controlled weathering fronts in matrix blocks, which is consistent with the shrinking core mechanism. A significant decrease in the domain-averaged weathering rate is evident despite high remaining mineral volume fractions, but the decline does not follow a math formula dependence, characteristic of diffusion, due to network scale effects and advection-controlled behavior near the inflow boundary. Finally, the DFN simulations also reveal relatively constant horizontally averaged weathering rates over a significant depth range, challenging the very notion of a weathering front.« less

Forced magnetohydrodynamic turbulence in a uniform external magnetic field

NASA Technical Reports Server (NTRS)

Hossain, M.; Vahala, G.; Montgomery, D.

1985-01-01

Two-dimensional dissipative MHD turbulence is randomly driven at small spatial scales and is studied by numerical simulation in the presence of a strong uniform external magnetic field. A behavior is observed which is apparently distinct from the inverse cascade which prevails in the absence of an external magnetic field. The magnetic spectrum becomes dominated by the three longest wavelength Alfven waves in the system allowed by the boundary conditions: those which, in a box size of edge 2 pi, have wave numbers (kx, ky) = (1, 1), and (1, -1), where the external magnetic field is in the x direction. At any given instant, one of these three modes dominates the vector potential spectrum, but they do not constitute a resonantly coupled triad. Rather, they are apparently coupled by the smaller-scale turbulence.

Forced MHD turbulence in a uniform external magnetic field

NASA Technical Reports Server (NTRS)

Hossain, M.; Vahala, G.; Montgomery, D.

1985-01-01

Two-dimensional dissipative MHD turbulence is randomly driven at small spatial scales and is studied by numerical simulation in the presence of a strong uniform external magnetic field. A behavior is observed which is apparently distinct from the inverse cascade which prevails in the absence of an external magnetic field. The magnetic spectrum becomes dominated by the three longest wavelength Alfven waves in the system allowed by the boundary conditions: those which, in a box size of edge 2 pi, have wave numbers (kx' ky) = (1, 1), and (1, -1), where the external magnetic field is in the x direction. At any given instant, one of these three modes dominates the vector potential spectrum, but they do not constitute a resonantly coupled triad. Rather, they are apparently coupled by the smaller-scale turbulence.

Reducing RANS Model Error Using Random Forest

NASA Astrophysics Data System (ADS)

Wang, Jian-Xun; Wu, Jin-Long; Xiao, Heng; Ling, Julia

2016-11-01

Reynolds-Averaged Navier-Stokes (RANS) models are still the work-horse tools in the turbulence modeling of industrial flows. However, the model discrepancy due to the inadequacy of modeled Reynolds stresses largely diminishes the reliability of simulation results. In this work we use a physics-informed machine learning approach to improve the RANS modeled Reynolds stresses and propagate them to obtain the mean velocity field. Specifically, the functional forms of Reynolds stress discrepancies with respect to mean flow features are trained based on an offline database of flows with similar characteristics. The random forest model is used to predict Reynolds stress discrepancies in new flows. Then the improved Reynolds stresses are propagated to the velocity field via RANS equations. The effects of expanding the feature space through the use of a complete basis of Galilean tensor invariants are also studied. The flow in a square duct, which is challenging for standard RANS models, is investigated to demonstrate the merit of the proposed approach. The results show that both the Reynolds stresses and the propagated velocity field are improved over the baseline RANS predictions. SAND Number: SAND2016-7437 A

A dissipative random velocity field for fully developed fluid turbulence

NASA Astrophysics Data System (ADS)

Chevillard, Laurent; Pereira, Rodrigo; Garban, Christophe

2016-11-01

We investigate the statistical properties, based on numerical simulations and analytical calculations, of a recently proposed stochastic model for the velocity field of an incompressible, homogeneous, isotropic and fully developed turbulent flow. A key step in the construction of this model is the introduction of some aspects of the vorticity stretching mechanism that governs the dynamics of fluid particles along their trajectory. An additional further phenomenological step aimed at including the long range correlated nature of turbulence makes this model depending on a single free parameter that can be estimated from experimental measurements. We confirm the realism of the model regarding the geometry of the velocity gradient tensor, the power-law behaviour of the moments of velocity increments, including the intermittent corrections, and the existence of energy transfers across scales. We quantify the dependence of these basic properties of turbulent flows on the free parameter and derive analytically the spectrum of exponents of the structure functions in a simplified non dissipative case. A perturbative expansion shows that energy transfers indeed take place, justifying the dissipative nature of this random field.

Macroscopically constrained Wang-Landau method for systems with multiple order parameters and its application to drawing complex phase diagrams

NASA Astrophysics Data System (ADS)

Chan, C. H.; Brown, G.; Rikvold, P. A.

2017-05-01

A generalized approach to Wang-Landau simulations, macroscopically constrained Wang-Landau, is proposed to simulate the density of states of a system with multiple macroscopic order parameters. The method breaks a multidimensional random-walk process in phase space into many separate, one-dimensional random-walk processes in well-defined subspaces. Each of these random walks is constrained to a different set of values of the macroscopic order parameters. When the multivariable density of states is obtained for one set of values of fieldlike model parameters, the density of states for any other values of these parameters can be obtained by a simple transformation of the total system energy. All thermodynamic quantities of the system can then be rapidly calculated at any point in the phase diagram. We demonstrate how to use the multivariable density of states to draw the phase diagram, as well as order-parameter probability distributions at specific phase points, for a model spin-crossover material: an antiferromagnetic Ising model with ferromagnetic long-range interactions. The fieldlike parameters in this model are an effective magnetic field and the strength of the long-range interaction.

Effects of Eddy Viscosity on Time Correlations in Large Eddy Simulation

NASA Technical Reports Server (NTRS)

He, Guowei; Rubinstein, R.; Wang, Lian-Ping; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

Subgrid-scale (SGS) models for large. eddy simulation (LES) have generally been evaluated by their ability to predict single-time statistics of turbulent flows such as kinetic energy and Reynolds stresses. Recent application- of large eddy simulation to the evaluation of sound sources in turbulent flows, a problem in which time, correlations determine the frequency distribution of acoustic radiation, suggest that subgrid models should also be evaluated by their ability to predict time correlations in turbulent flows. This paper compares the two-point, two-time Eulerian velocity correlation evaluated from direct numerical simulation (DNS) with that evaluated from LES, using a spectral eddy viscosity, for isotropic homogeneous turbulence. It is found that the LES fields are too coherent, in the sense that their time correlations decay more slowly than the corresponding time. correlations in the DNS fields. This observation is confirmed by theoretical estimates of time correlations using the Taylor expansion technique. Tile reason for the slower decay is that the eddy viscosity does not include the random backscatter, which decorrelates fluid motion at large scales. An effective eddy viscosity associated with time correlations is formulated, to which the eddy viscosity associated with energy transfer is a leading order approximation.

Process-based modelling of NH3 exchange with grazed grasslands

NASA Astrophysics Data System (ADS)

Móring, Andrea; Vieno, Massimo; Doherty, Ruth M.; Milford, Celia; Nemitz, Eiko; Twigg, Marsailidh M.; Horváth, László; Sutton, Mark A.

2017-09-01

In this study the GAG model, a process-based ammonia (NH3) emission model for urine patches, was extended and applied for the field scale. The new model (GAG_field) was tested over two modelling periods, for which micrometeorological NH3 flux data were available. Acknowledging uncertainties in the measurements, the model was able to simulate the main features of the observed fluxes. The temporal evolution of the simulated NH3 exchange flux was found to be dominated by NH3 emission from the urine patches, offset by simultaneous NH3 deposition to areas of the field not affected by urine. The simulations show how NH3 fluxes over a grazed field in a given day can be affected by urine patches deposited several days earlier, linked to the interaction of volatilization processes with soil pH dynamics. Sensitivity analysis showed that GAG_field was more sensitive to soil buffering capacity (β), field capacity (θfc) and permanent wilting point (θpwp) than the patch-scale model. The reason for these different sensitivities is dual. Firstly, the difference originates from the different scales. Secondly, the difference can be explained by the different initial soil pH and physical properties, which determine the maximum volume of urine that can be stored in the NH3 source layer. It was found that in the case of urine patches with a higher initial soil pH and higher initial soil water content, the sensitivity of NH3 exchange to β was stronger. Also, in the case of a higher initial soil water content, NH3 exchange was more sensitive to the changes in θfc and θpwp. The sensitivity analysis showed that the nitrogen content of urine (cN) is associated with high uncertainty in the simulated fluxes. However, model experiments based on cN values randomized from an estimated statistical distribution indicated that this uncertainty is considerably smaller in practice. Finally, GAG_field was tested with a constant soil pH of 7.5. The variation of NH3 fluxes simulated in this way showed a good agreement with those from the simulations with the original approach, accounting for a dynamically changing soil pH. These results suggest a way for model simplification when GAG_field is applied later at regional scale.

Turbulent, Extreme Multi-zone Model for Simulating Flux and Polarization Variability in Blazars

NASA Astrophysics Data System (ADS)

Marscher, Alan P.

2014-01-01

The author presents a model for variability of the flux and polarization of blazars in which turbulent plasma flowing at a relativistic speed down a jet crosses a standing conical shock. The shock compresses the plasma and accelerates electrons to energies up to γmax >~ 104 times their rest-mass energy, with the value of γmax determined by the direction of the magnetic field relative to the shock front. The turbulence is approximated in a computer code as many cells, each with a uniform magnetic field whose direction is selected randomly. The density of high-energy electrons in the plasma changes randomly with time in a manner consistent with the power spectral density of flux variations derived from observations of blazars. The variations in flux and polarization are therefore caused by continuous noise processes rather than by singular events such as explosive injection of energy at the base of the jet. Sample simulations illustrate the behavior of flux and linear polarization versus time that such a model produces. The variations in γ-ray flux generated by the code are often, but not always, correlated with those at lower frequencies, and many of the flares are sharply peaked. The mean degree of polarization of synchrotron radiation is higher and its timescale of variability shorter toward higher frequencies, while the polarization electric vector sometimes randomly executes apparent rotations. The slope of the spectral energy distribution exhibits sharper breaks than can arise solely from energy losses. All of these results correspond to properties observed in blazars.

Comparison between Simulation-based Training and Lecture-based Education in Teaching Situation Awareness. A Randomized Controlled Study.

PubMed

Lee Chang, Alfredo; Dym, Andrew A; Venegas-Borsellino, Carla; Bangar, Maneesha; Kazzi, Massoud; Lisenenkov, Dmitry; Qadir, Nida; Keene, Adam; Eisen, Lewis Ari

2017-04-01

Situation awareness has been defined as the perception of the elements in the environment within volumes of time and space, the comprehension of their meaning, and the projection of their status in the near future. Intensivists often make time-sensitive critical decisions, and loss of situation awareness can lead to errors. It has been shown that simulation-based training is superior to lecture-based training for some critical scenarios. Because the methods of training to improve situation awareness have not been well studied in the medical field, we compared the impact of simulation vs. lecture training using the Situation Awareness Global Assessment Technique (SAGAT) score. To identify an effective method for teaching situation awareness. We randomly assigned 17 critical care fellows to simulation vs. lecture training. Training consisted of eight cases on airway management, including topics such as elevated intracranial pressure, difficult airway, arrhythmia, and shock. During the testing scenario, at random times between 4 and 6 minutes into the simulation, the scenario was frozen, and the screens were blanked. Respondents then completed the 28 questions on the SAGAT scale. Sample items were categorized as Perception, Projection, and Comprehension of the situation. Results were analyzed using SPSS Version 21. Eight fellows from the simulation group and nine from the lecture group underwent simulation testing. Sixty-four SAGAT scores were recorded for the simulation group and 48 scores were recorded for the lecture group. The mean simulation vs. lecture group SAGAT score was 64.3 ± 10.1 (SD) vs. 59.7 ± 10.8 (SD) (P = 0.02). There was also a difference in the median Perception ability between the simulation vs. lecture groups (61.1 vs. 55.5, P = 0.01). There was no difference in the median Projection and Comprehension scores between the two groups (50.0 vs. 50.0, P = 0.92, and 83.3 vs. 83.3, P = 0.27). We found a significant, albeit modest, difference between simulation training and lecture training on the total SAGAT score of situation awareness mainly because of the improvement in perception ability. Simulation may be a superior method of teaching situation awareness.

Homogeneous buoyancy-generated turbulence

NASA Technical Reports Server (NTRS)

Batchelor, G. K.; Canuto, V. M.; Chasnov, J. R.

1992-01-01

Using a theoretical analysis of fundamental equations and a numerical simulation of the flow field, the statistically homogeneous motion that is generated by buoyancy forces after the creation of homogeneous random fluctuations in the density of infinite fluid at an initial instant is examined. It is shown that analytical results together with numerical results provide a comprehensive description of the 'birth, life, and death' of buoyancy-generated turbulence. Results of numerical simulations yielded the mean-square density mean-square velocity fluctuations and the associated spectra as functions of time for various initial conditions, and the time required for the mean-square density fluctuation to fall to a specified small value was estimated.

Electron heating in the exhaust of magnetic reconnection with negligible guide field

NASA Astrophysics Data System (ADS)

Wang, Shan; Chen, Li-Jen; Bessho, Naoki; Kistler, Lynn M.; Shuster, Jason R.; Guo, Ruilong

2016-03-01

Electron heating in the magnetic reconnection exhaust is investigated with particle-in-cell simulations, space observations, and theoretical analysis. Spatial variations of the electron temperature (Te) and associated velocity distribution functions (VDFs) are examined and understood in terms of particle energization and randomization processes that vary with exhaust locations. Inside the electron diffusion region (EDR), the electron temperature parallel to the magnetic field (Te∥) exhibits a local minimum and the perpendicular temperature (Te⊥) shows a maximum at the current sheet midplane. In the intermediate exhaust downstream from the EDR and far from the magnetic field pileup region, Te⊥/Te∥ is close to unity and Te is approximately uniform, but the VDFs are structured: close to the midplane, VDFs are quasi-isotropic, whereas farther away from the midplane, VDFs exhibit field-aligned beams directed toward the midplane. In the far exhaust, Te generally increases toward the midplane and the pileup region, and the corresponding VDFs show counter-streaming beams. A distinct population with low v∥ and high v⊥ is prominent in the VDFs around the midplane. Test particle results show that the magnetic curvature near the midplane produces pitch angle scattering to generate quasi-isotropic distributions in the intermediate exhaust. In the far exhaust, electrons with initial high v∥ (v⊥) are accelerated mainly through curvature (gradient-B) drift opposite to the electric field, without significant pitch angle scattering. The VDF structures predicted by simulations are observed in magnetotail reconnection measurements, indicating that the energization mechanisms captured in the reported simulations are applicable to magnetotail reconnection with negligible guide field.

Charged-particle motion in multidimensional magnetic-field turbulence

NASA Technical Reports Server (NTRS)

Giacalone, J.; Jokipii, J. R.

1994-01-01

We present a new analysis of the fundamental physics of charged-particle motion in a turbulent magnetic field using a numerical simulation. The magnetic field fluctuations are taken to be static and to have a power spectrum which is Kolmogorov. The charged particles are treated as test particles. It is shown that when the field turbulence is independent of one coordinate (i.e., k lies in a plane), the motion of these particles across the magnetic field is essentially zero, as required by theory. Consequently, the only motion across the average magnetic field direction that is allowed is that due to field-line random walk. On the other hand, when a fully three-dimensional realization of the turbulence is considered, the particles readily cross the field. Transport coefficients both along and across the ambient magnetic field are computed. This scheme provides a direct computation of the Fokker-Planck coefficients based on the motions of individual particles, and allows for comparison with analytic theory.

The use of augmented reality glasses in central line simulation: "see one, simulate many, do one competently, and teach everyone".

PubMed

Huang, Cynthia Y; Thomas, Jonathan B; Alismail, Abdullah; Cohen, Avi; Almutairi, Waleed; Daher, Noha S; Terry, Michael H; Tan, Laren D

2018-01-01

The aim of this study was to investigate the feasibility of using augmented reality (AR) glasses in central line simulation by novice operators and compare its efficacy to standard central line simulation/teaching. This was a prospective randomized controlled study enrolling 32 novice operators. Subjects were randomized on a 1:1 basis to either simulation using the augmented virtual reality glasses or simulation using conventional instruction. The study was conducted in tertiary-care urban teaching hospital. A total of 32 adult novice central line operators with no visual or auditory impairments were enrolled. Medical doctors, respiratory therapists, and sleep technicians were recruited from the medical field. The mean time for AR placement in the AR group was 71±43 s, and the time to internal jugular (IJ) cannulation was 316±112 s. There was no significant difference in median (minimum, maximum) time (seconds) to IJ cannulation for those who were in the AR group and those who were not (339 [130, 550] vs 287 [35, 475], p =0.09), respectively. There was also no significant difference between the two groups in median total procedure time (524 [329, 792] vs 469 [198, 781], p =0.29), respectively. There was a significant difference in the adherence level between the two groups favoring the AR group ( p =0.003). AR simulation of central venous catheters in manikins is feasible and efficacious in novice operators as an educational tool. Future studies are recommended in this area as it is a promising area of medical education.

Bayesian network meta-analysis for cluster randomized trials with binary outcomes.

PubMed

Uhlmann, Lorenz; Jensen, Katrin; Kieser, Meinhard

2017-06-01

Network meta-analysis is becoming a common approach to combine direct and indirect comparisons of several treatment arms. In recent research, there have been various developments and extensions of the standard methodology. Simultaneously, cluster randomized trials are experiencing an increased popularity, especially in the field of health services research, where, for example, medical practices are the units of randomization but the outcome is measured at the patient level. Combination of the results of cluster randomized trials is challenging. In this tutorial, we examine and compare different approaches for the incorporation of cluster randomized trials in a (network) meta-analysis. Furthermore, we provide practical insight on the implementation of the models. In simulation studies, it is shown that some of the examined approaches lead to unsatisfying results. However, there are alternatives which are suitable to combine cluster randomized trials in a network meta-analysis as they are unbiased and reach accurate coverage rates. In conclusion, the methodology can be extended in such a way that an adequate inclusion of the results obtained in cluster randomized trials becomes feasible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

OBSERVATIONAL SIGNATURES OF CORONAL LOOP HEATING AND COOLING DRIVEN BY FOOTPOINT SHUFFLING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dahlburg, R. B.; Taylor, B. D.; Einaudi, G.

The evolution of a coronal loop is studied by means of numerical simulations of the fully compressible three-dimensional magnetohydrodynamic equations using the HYPERION code. The footpoints of the loop magnetic field are advected by random motions. As a consequence, the magnetic field in the loop is energized and develops turbulent nonlinear dynamics characterized by the continuous formation and dissipation of field-aligned current sheets: energy is deposited at small scales where heating occurs. Dissipation is nonuniformly distributed so that only a fraction of the coronal mass and volume gets heated at any time. Temperature and density are highly structured at scalesmore » that, in the solar corona, remain observationally unresolved: the plasma of our simulated loop is multithermal, where highly dynamical hotter and cooler plasma strands are scattered throughout the loop at sub-observational scales. Numerical simulations of coronal loops of 50,000 km length and axial magnetic field intensities ranging from 0.01 to 0.04 T are presented. To connect these simulations to observations, we use the computed number densities and temperatures to synthesize the intensities expected in emission lines typically observed with the Extreme Ultraviolet Imaging Spectrometer on Hinode. These intensities are used to compute differential emission measure distributions using the Monte Carlo Markov Chain code, which are very similar to those derived from observations of solar active regions. We conclude that coronal heating is found to be strongly intermittent in space and time, with only small portions of the coronal loop being heated: in fact, at any given time, most of the corona is cooling down.« less

Virtual and Experimental Visualization of Flows in Packed Beds of Spheres Simulating Porous Media Flows

NASA Technical Reports Server (NTRS)

Hendricks, R. C.; Athavale, M. M.; Lattime, S. B.; Braun, M. J.

1998-01-01

A videotape presentation of flow in a packed bed of spheres is provided. The flow experiment consisted of three principal elements: (1) an oil tunnel 76.2 mm by 76.2 mm in cross section, (2) a packed bed of spheres in regular and irregular arrays, and (3) a flow characterization methodology, either (a) full flow field tracking (FFFT) or (b) computational fluid dynamic (CFD) simulation. The refraction indices of the oil and the test array of spheres were closely matched, and the flow was seeded with aluminum oxide particles. Planar laser light provided a two-dimensional projection of the flow field, and a traverse simulated a three-dimensional image of the entire flow field. Light focusing and reflection rendered the spheres black, permitting visualization of the planar circular interfaces in both the axial and transverse directions. Flows were observed near the wall-sphere interface and within the set of spheres. The CFD model required that a representative section of a packed bed be formed and gridded, enclosing and cutting six spheres so that symmetry conditions could be imposed at all cross-boundaries. Simulations had to be made with the flow direction at right angles to that used in the experiments, however, to take advantage of flow symmetry. Careful attention to detail was required for proper gridding. The flow field was three-dimensional and complex to describe, yet the most prominent finding was flow threads, as computed in the representative 'cube' of spheres with face symmetry and conclusively demonstrated experimentally herein. Random packing and bed voids tended to disrupt the laminar flow, creating vortices.

Phase-only asymmetric optical cryptosystem based on random modulus decomposition

NASA Astrophysics Data System (ADS)

Xu, Hongfeng; Xu, Wenhui; Wang, Shuaihua; Wu, Shaofan

2018-06-01

We propose a phase-only asymmetric optical cryptosystem based on random modulus decomposition (RMD). The cryptosystem is presented for effectively improving the capacity to resist various attacks, including the attack of iterative algorithms. On the one hand, RMD and phase encoding are combined to remove the constraints that can be used in the attacking process. On the other hand, the security keys (geometrical parameters) introduced by Fresnel transform can increase the key variety and enlarge the key space simultaneously. Numerical simulation results demonstrate the strong feasibility, security and robustness of the proposed cryptosystem. This cryptosystem will open up many new opportunities in the application fields of optical encryption and authentication.

Fast Physically Accurate Rendering of Multimodal Signatures of Distributed Fracture in Heterogeneous Materials.

PubMed

Visell, Yon

2015-04-01

This paper proposes a fast, physically accurate method for synthesizing multimodal, acoustic and haptic, signatures of distributed fracture in quasi-brittle heterogeneous materials, such as wood, granular media, or other fiber composites. Fracture processes in these materials are challenging to simulate with existing methods, due to the prevalence of large numbers of disordered, quasi-random spatial degrees of freedom, representing the complex physical state of a sample over the geometric volume of interest. Here, I develop an algorithm for simulating such processes, building on a class of statistical lattice models of fracture that have been widely investigated in the physics literature. This algorithm is enabled through a recently published mathematical construction based on the inverse transform method of random number sampling. It yields a purely time domain stochastic jump process representing stress fluctuations in the medium. The latter can be readily extended by a mean field approximation that captures the averaged constitutive (stress-strain) behavior of the material. Numerical simulations and interactive examples demonstrate the ability of these algorithms to generate physically plausible acoustic and haptic signatures of fracture in complex, natural materials interactively at audio sampling rates.

First Demonstration of a Coronal Mass Ejection Driven by Helicity Condensation

NASA Astrophysics Data System (ADS)

Dahlin, J. T.; Antiochos, S. K.; DeVore, C. R.

2017-12-01

Understanding the mechanism for CMEs/eruptive flares is one of the most important problems in all space science. Two classes of theories have been proposed: ideal processes such as the torus instability, or magnetic reconnection as in the breakout model. Previous simulations of eruptions have used special assumptions, such as a particular initial condition ripe for instability and/or particular boundary conditions designed to induce eruption. We report on a simulation in which the initial state is the minimum-energy potential field, and the system is driven solely by the small-scale random motions observed for photospheric convection. The only requirement on the system is that the flows are sufficiently complex to induce pervasive and random reconnection throughout the volume, as expected for coronal heating, and a net helicity is injected into the corona, in agreement with the observed hemispheric helicity preference. We find that as a result of a turbulent-like cascade, the helicity "condenses" onto a polarity inversion line forming a filament channel, which eventually erupts explosively. We discuss the implications of this fully self-consistent eruption simulation for understanding CMEs/flares and for interpreting coronal observations. This work was supported by the NASA LWS and SR Programs.

Liquid water breakthrough location distances on a gas diffusion layer of polymer electrolyte membrane fuel cells

NASA Astrophysics Data System (ADS)

Yu, Junliang; Froning, Dieter; Reimer, Uwe; Lehnert, Werner

2018-06-01

The lattice Boltzmann method is adopted to simulate the three dimensional dynamic process of liquid water breaking through the gas diffusion layer (GDL) in the polymer electrolyte membrane fuel cell. 22 micro-structures of Toray GDL are built based on a stochastic geometry model. It is found that more than one breakthrough locations are formed randomly on the GDL surface. Breakthrough location distance (BLD) are analyzed statistically in two ways. The distribution is evaluated statistically by the Lilliefors test. It is concluded that the BLD can be described by the normal distribution with certain statistic characteristics. Information of the shortest neighbor breakthrough location distance can be the input modeling setups on the cell-scale simulations in the field of fuel cell simulation.

Comparison of texture synthesis methods for content generation in ultrasound simulation for training

NASA Astrophysics Data System (ADS)

Mattausch, Oliver; Ren, Elizabeth; Bajka, Michael; Vanhoey, Kenneth; Goksel, Orcun

2017-03-01

Navigation and interpretation of ultrasound (US) images require substantial expertise, the training of which can be aided by virtual-reality simulators. However, a major challenge in creating plausible simulated US images is the generation of realistic ultrasound speckle. Since typical ultrasound speckle exhibits many properties of Markov Random Fields, it is conceivable to use texture synthesis for generating plausible US appearance. In this work, we investigate popular classes of texture synthesis methods for generating realistic US content. In a user study, we evaluate their performance for reproducing homogeneous tissue regions in B-mode US images from small image samples of similar tissue and report the best-performing synthesis methods. We further show that regression trees can be used on speckle texture features to learn a predictor for US realism.

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

Feasibility of conductivity imaging using subject eddy currents induced by switching of MRI gradients.

PubMed

Oran, Omer Faruk; Ider, Yusuf Ziya

2017-05-01

To investigate the feasibility of low-frequency conductivity imaging based on measuring the magnetic field due to subject eddy currents induced by switching of MRI z-gradients. We developed a simulation model for calculating subject eddy currents and the magnetic fields they generate (subject eddy fields). The inverse problem of obtaining conductivity distribution from subject eddy fields was formulated as a convection-reaction partial differential equation. For measuring subject eddy fields, a modified spin-echo pulse sequence was used to determine the contribution of subject eddy fields to MR phase images. In the simulations, successful conductivity reconstructions were obtained by solving the derived convection-reaction equation, suggesting that the proposed reconstruction algorithm performs well under ideal conditions. However, the level of the calculated phase due to the subject eddy field in a representative object indicates that this phase is below the noise level and cannot be measured with an uncertainty sufficiently low for accurate conductivity reconstruction. Furthermore, some artifacts other than random noise were observed in the measured phases, which are discussed in relation to the effects of system imperfections during readout. Low-frequency conductivity imaging does not seem feasible using basic pulse sequences such as spin-echo on a clinical MRI scanner. Magn Reson Med 77:1926-1937, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Formation and evolution of magnetised filaments in wind-swept turbulent clumps

NASA Astrophysics Data System (ADS)

Banda-Barragan, Wladimir Eduardo; Federrath, Christoph; Crocker, Roland M.; Bicknell, Geoffrey Vincent; Parkin, Elliot Ross

2015-08-01

Using high-resolution three-dimensional simulations, we examine the formation and evolution of filamentary structures arising from magnetohydrodynamic interactions between supersonic winds and turbulent clumps in the interstellar medium. Previous numerical studies assumed homogenous density profiles, null velocity fields, and uniformly distributed magnetic fields as the initial conditions for interstellar clumps. Here, we have, for the first time, incorporated fractal clumps with log-normal density distributions, random velocity fields and turbulent magnetic fields (superimposed on top of a uniform background field). Disruptive processes, instigated by dynamical instabilities and akin to those observed in simulations with uniform media, lead to stripping of clump material and the subsequent formation of filamentary tails. The evolution of filaments in uniform and turbulent models is, however, radically different as evidenced by comparisons of global quantities in both scenarios. We show, for example, that turbulent clumps produce tails with higher velocity dispersions, increased gas mixing, greater kinetic energy, and lower plasma beta than their uniform counterparts. We attribute the observed differences to: 1) the turbulence-driven enhanced growth of dynamical instabilities (e.g. Kelvin-Helmholtz and Rayleigh-Taylor instabilities) at fluid interfaces, and 2) the localised amplification of magnetic fields caused by the stretching of field lines trapped in the numerous surface deformations of fractal clumps. We briefly discuss the implications of this work to the physics of the optical filaments observed in the starburst galaxy M82.

General simulation algorithm for autocorrelated binary processes.

PubMed

Serinaldi, Francesco; Lombardo, Federico

2017-02-01

The apparent ubiquity of binary random processes in physics and many other fields has attracted considerable attention from the modeling community. However, generation of binary sequences with prescribed autocorrelation is a challenging task owing to the discrete nature of the marginal distributions, which makes the application of classical spectral techniques problematic. We show that such methods can effectively be used if we focus on the parent continuous process of beta distributed transition probabilities rather than on the target binary process. This change of paradigm results in a simulation procedure effectively embedding a spectrum-based iterative amplitude-adjusted Fourier transform method devised for continuous processes. The proposed algorithm is fully general, requires minimal assumptions, and can easily simulate binary signals with power-law and exponentially decaying autocorrelation functions corresponding, for instance, to Hurst-Kolmogorov and Markov processes. An application to rainfall intermittency shows that the proposed algorithm can also simulate surrogate data preserving the empirical autocorrelation.

A Weather Radar Simulator for the Evaluation of Polarimetric Phased Array Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byrd, Andrew D.; Ivic, Igor R.; Palmer, Robert D.

A radar simulator capable of generating time series data for a polarimetric phased array weather radar has been designed and implemented. The received signals are composed from a high-resolution numerical prediction weather model. Thousands of scattering centers, each with an independent randomly generated Doppler spectrum, populate the field of view of the radar. The moments of the scattering center spectra are derived from the numerical weather model, and the scattering center positions are updated based on the three-dimensional wind field. In order to accurately emulate the effects of the system-induced cross-polar contamination, the array is modeled using a complete setmore » of dual-polarization radiation patterns. The simulator offers reconfigurable element patterns and positions as well as access to independent time series data for each element, resulting in easy implementation of any beamforming method. It also allows for arbitrary waveform designs and is able to model the effects of quantization on waveform performance. Simultaneous, alternating, quasi-simultaneous, and pulse-to-pulse phase coded modes of polarimetric signal transmission have been implemented. This framework allows for realistic emulation of the effects of cross-polar fields on weather observations, as well as the evaluation of possible techniques for the mitigation of those effects.« less

Simulation of the Effects of Random Measurement Errors

ERIC Educational Resources Information Center

Kinsella, I. A.; Hannaidh, P. B. O.

1978-01-01

Describes a simulation method for measurement of errors that requires calculators and tables of random digits. Each student simulates the random behaviour of the component variables in the function and by combining the results of all students, the outline of the sampling distribution of the function can be obtained. (GA)

Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

PubMed

Nie, Jingxin; Xue, Zhong; Liu, Tianming; Young, Geoffrey S; Setayesh, Kian; Guo, Lei; Wong, Stephen T C

2009-09-01

A variety of algorithms have been proposed for brain tumor segmentation from multi-channel sequences, however, most of them require isotropic or pseudo-isotropic resolution of the MR images. Although co-registration and interpolation of low-resolution sequences, such as T2-weighted images, onto the space of the high-resolution image, such as T1-weighted image, can be performed prior to the segmentation, the results are usually limited by partial volume effects due to interpolation of low-resolution images. To improve the quality of tumor segmentation in clinical applications where low-resolution sequences are commonly used together with high-resolution images, we propose the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization (SHE) approach for both automated tumor and enhanced-tumor segmentation. SHE incorporates the spatial interpolation accuracy of low-resolution images into the optimization procedure of the Hidden Markov Random Field (HMRF) to segment tumor using multi-channel MR images with different resolutions, e.g., high-resolution T1-weighted and low-resolution T2-weighted images. In experiments, we evaluated this algorithm using a set of simulated multi-channel brain MR images with known ground-truth tissue segmentation and also applied it to a dataset of MR images obtained during clinical trials of brain tumor chemotherapy. The results show that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms.

Enhanced dielectric standoff and mechanical failure in field-structured composites

NASA Astrophysics Data System (ADS)

Martin, James E.; Tigges, Chris P.; Anderson, Robert A.; Odinek, Judy

1999-09-01

We report dielectric breakdown experiments on electric-field-structured composites of high-dielectric-constant BaTiO3 particles in an epoxy resin. These experiments show a significant increase in the dielectric standoff strength perpendicular to the field structuring direction, relative to control samples consisting of randomly dispersed particles. To understand the relation of this observation to microstructure, we apply a simple resistor-short breakdown model to three-dimensional composite structures generated from a dynamical simulation. In this breakdown model the composite material is assumed to conduct primarily through particle contacts, so the simulated structures are mapped onto a resistor network where the center of mass of each particle is a node that is connected to neighboring nodes by resistors of fixed resistance that irreversibly short to perfect conductors when the current reaches a threshold value. This model gives relative breakdown voltages that are in good agreement with experimental results. Finally, we consider a primitive model of the mechanical strength of a field-structured composite material, which is a current-driven, conductor-insulator fuse model. This model leads to a macroscopic fusing behavior and can be related to mechanical failure of the composite.

EVOLUTION OF FAST MAGNETOACOUSTIC PULSES IN RANDOMLY STRUCTURED CORONAL PLASMAS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, D.; Li, B.; Pascoe, D. J.

2015-02-01

We investigate the evolution of fast magnetoacoustic pulses in randomly structured plasmas, in the context of large-scale propagating waves in the solar atmosphere. We perform one-dimensional numerical simulations of fast wave pulses propagating perpendicular to a constant magnetic field in a low-β plasma with a random density profile across the field. Both linear and nonlinear regimes are considered. We study how the evolution of the pulse amplitude and width depends on their initial values and the parameters of the random structuring. Acting as a dispersive medium, a randomly structured plasma causes amplitude attenuation and width broadening of the fast wavemore » pulses. After the passage of the main pulse, secondary propagating and standing fast waves appear. Width evolution of both linear and nonlinear pulses can be well approximated by linear functions; however, narrow pulses may have zero or negative broadening. This arises because narrow pulses are prone to splitting, while broad pulses usually deviate less from their initial Gaussian shape and form ripple structures on top of the main pulse. Linear pulses decay at an almost constant rate, while nonlinear pulses decay exponentially. A pulse interacts most efficiently with a random medium with a correlation length of about half of the initial pulse width. This detailed model of fast wave pulses propagating in highly structured media substantiates the interpretation of EIT waves as fast magnetoacoustic waves. Evolution of a fast pulse provides us with a novel method to diagnose the sub-resolution filamentation of the solar atmosphere.« less

EVOLUTION OF THE MAGNETIC FIELD LINE DIFFUSION COEFFICIENT AND NON-GAUSSIAN STATISTICS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snodin, A. P.; Ruffolo, D.; Matthaeus, W. H.

The magnetic field line random walk (FLRW) plays an important role in the transport of energy and particles in turbulent plasmas. For magnetic fluctuations that are transverse or almost transverse to a large-scale mean magnetic field, theories describing the FLRW usually predict asymptotic diffusion of magnetic field lines perpendicular to the mean field. Such theories often depend on the assumption that one can relate the Lagrangian and Eulerian statistics of the magnetic field via Corrsin’s hypothesis, and additionally take the distribution of magnetic field line displacements to be Gaussian. Here we take an ordinary differential equation (ODE) model with thesemore » underlying assumptions and test how well it describes the evolution of the magnetic field line diffusion coefficient in 2D+slab magnetic turbulence, by comparisons to computer simulations that do not involve such assumptions. In addition, we directly test the accuracy of the Corrsin approximation to the Lagrangian correlation. Over much of the studied parameter space we find that the ODE model is in fairly good agreement with computer simulations, in terms of both the evolution and asymptotic values of the diffusion coefficient. When there is poor agreement, we show that this can be largely attributed to the failure of Corrsin’s hypothesis rather than the assumption of Gaussian statistics of field line displacements. The degree of non-Gaussianity, which we measure in terms of the kurtosis, appears to be an indicator of how well Corrsin’s approximation works.« less

Effective pore-scale dispersion upscaling with a correlated continuous time random walk approach

NASA Astrophysics Data System (ADS)

Le Borgne, T.; Bolster, D.; Dentz, M.; de Anna, P.; Tartakovsky, A.

2011-12-01

We investigate the upscaling of dispersion from a pore-scale analysis of Lagrangian velocities. A key challenge in the upscaling procedure is to relate the temporal evolution of spreading to the pore-scale velocity field properties. We test the hypothesis that one can represent Lagrangian velocities at the pore scale as a Markov process in space. The resulting effective transport model is a continuous time random walk (CTRW) characterized by a correlated random time increment, here denoted as correlated CTRW. We consider a simplified sinusoidal wavy channel model as well as a more complex heterogeneous pore space. For both systems, the predictions of the correlated CTRW model, with parameters defined from the velocity field properties (both distribution and correlation), are found to be in good agreement with results from direct pore-scale simulations over preasymptotic and asymptotic times. In this framework, the nontrivial dependence of dispersion on the pore boundary fluctuations is shown to be related to the competition between distribution and correlation effects. In particular, explicit inclusion of spatial velocity correlation in the effective CTRW model is found to be important to represent incomplete mixing in the pore throats.

Analysis of reliable sub-ns spin-torque switching under transverse bias magnetic fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

D'Aquino, M., E-mail: daquino@uniparthenope.it; Perna, S.; Serpico, C.

2015-05-07

The switching process of a magnetic spin-valve nanosystem subject to spin-polarized current pulses is considered. The dependence of the switching probability on the current pulse duration is investigated. The further application of a transverse field along the intermediate anisotropy axis of the particle is used to control the quasi-random relaxation of magnetization to the reversed magnetization state. The critical current amplitudes to realize the switching are determined by studying the phase portrait of the Landau-Lifshtz-Slonczewski dynamics. Macrospin numerical simulations are in good agreement with the theoretical prediction and demonstrate reliable switching even for very short (below 100 ps) current pulses.

Eulerian Mapping Closure Approach for Probability Density Function of Concentration in Shear Flows

NASA Technical Reports Server (NTRS)

He, Guowei; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

The Eulerian mapping closure approach is developed for uncertainty propagation in computational fluid mechanics. The approach is used to study the Probability Density Function (PDF) for the concentration of species advected by a random shear flow. An analytical argument shows that fluctuation of the concentration field at one point in space is non-Gaussian and exhibits stretched exponential form. An Eulerian mapping approach provides an appropriate approximation to both convection and diffusion terms and leads to a closed mapping equation. The results obtained describe the evolution of the initial Gaussian field, which is in agreement with direct numerical simulations.

Fluid dynamics during Random Positioning Machine micro-gravity experiments

NASA Astrophysics Data System (ADS)

Leguy, Carole A. D.; Delfos, René; Pourquie, Mathieu J. B. M.; Poelma, Christian; Westerweel, Jerry; van Loon, Jack J. W. A.

2017-06-01

A Random Positioning Machine (RPM) is a device used to study the role of gravity on biological systems. This is accomplished through continuous reorientation of the sample such that the net influence of gravity is randomized over time. The aim of this study is to predict fluid flow behavior during such RPM simulated microgravity studies, which may explain differences found between RPM and space flight experiments. An analytical solution is given for a cylinder as a model for an experimental container. Then, a dual-axis rotating frame is used to mimic the motion characteristics of an RPM with sinusoidal rotation frequencies of 0.2 Hz and 0.1 Hz while Particle Image Velocimetry is used to measure the velocity field inside a flask. To reproduce the same experiment numerically, a Direct Numerical Simulation model is used. The analytical model predicts that an increase in the Womersley number leads to higher shear stresses at the cylinder wall and decrease in fluid angular velocity inside the cylinder. The experimental results show that periodic single-axis rotation induces a fluid motion parallel to the wall and that a complex flow is observed for two-axis rotation with a maximum wall shear stress of 8.0 mPa (80 mdyne /cm2). The experimental and numerical results show that oscillatory motion inside an RPM induces flow motion that can, depending on the experimental samples, reduce the quality of the simulated microgravity. Thus, it is crucial to determine the appropriate oscillatory frequency of the axes to design biological experiments.

Gravitational and magnetic field variations synergize to cause subtle variations in the global transcriptional state of Arabidopsis in vitro callus cultures

PubMed Central

2012-01-01

Background Biological systems respond to changes in both the Earth's magnetic and gravitational fields, but as experiments in space are expensive and infrequent, Earth-based simulation techniques are required. A high gradient magnetic field can be used to levitate biological material, thereby simulating microgravity and can also create environments with a reduced or an enhanced level of gravity (g), although special attention should be paid to the possible effects of the magnetic field (B) itself. Results Using diamagnetic levitation, we exposed Arabidopsis thaliana in vitro callus cultures to five environments with different levels of effective gravity and magnetic field strengths. The environments included levitation, i.e. simulated μg* (close to 0 g* at B = 10.1 T), intermediate g* (0.1 g* at B = 14.7 T) and enhanced gravity levels (1.9 g* at B = 14.7 T and 2 g* at B = 10.1 T) plus an internal 1 g* control (B = 16.5 T). The asterisk denotes the presence of the background magnetic field, as opposed to the effective gravity environments in the absence of an applied magnetic field, created using a Random Position Machine (simulated μg) and a Large Diameter Centrifuge (2 g). Microarray analysis indicates that changes in the overall gene expression of cultured cells exposed to these unusual environments barely reach significance using an FDR algorithm. However, it was found that gravitational and magnetic fields produce synergistic variations in the steady state of the transcriptional profile of plants. Transcriptomic results confirm that high gradient magnetic fields (i.e. to create μg* and 2 g* conditions) have a significant effect, mainly on structural, abiotic stress genes and secondary metabolism genes, but these subtle gravitational effects are only observable using clustering methodologies. Conclusions A detailed microarray dataset analysis, based on clustering of similarly expressed genes (GEDI software), can detect underlying global-scale responses, which cannot be detected by means of individual gene expression techniques using raw or corrected p values (FDR). A subtle, but consistent, genome-scale response to hypogravity environments was found, which was opposite to the response in a hypergravity environment. PMID:22435851

Beamformed nearfield imaging of a simulated coronary artery containing a stenosis.

PubMed

Owsley, N L; Hull, A J

1998-12-01

This paper is concerned with the potential for the detection and location of an artery containing a partial blockage by exploiting the space-time properties of the shear wave field in the surrounding elastic soft tissue. As a demonstration of feasibility, an array of piezoelectric film vibration sensors is placed on the free surface of a urethane mold that contains a surgical tube. Inside the surgical tube is a nylon constriction that inhibits the water flowing through the tube. A turbulent field develops in and downstream from the blockage, creating a randomly fluctuating pressure on the inner wall of the tube. This force produces shear and compressional wave energy in the urethane. After the array is used to sample the dominant shear wave space-time energy field at low frequencies, a nearfield (i.e., focused) beamforming process then images the energy distribution in the three-dimensional solid. Experiments and numerical simulations are included to demonstrate the potential of this noninvasive procedure for the early identification of vascular blockages-the typical precursor of serious arterial disease in the human heart.

Mapping Health Data: Improved Privacy Protection With Donut Method Geomasking

PubMed Central

Hampton, Kristen H.; Fitch, Molly K.; Allshouse, William B.; Doherty, Irene A.; Gesink, Dionne C.; Leone, Peter A.; Serre, Marc L.; Miller, William C.

2010-01-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest. PMID:20817785

Mapping health data: improved privacy protection with donut method geomasking.

PubMed

Hampton, Kristen H; Fitch, Molly K; Allshouse, William B; Doherty, Irene A; Gesink, Dionne C; Leone, Peter A; Serre, Marc L; Miller, William C

2010-11-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest.

Dual Dynamically Orthogonal approximation of incompressible Navier Stokes equations with random boundary conditions

NASA Astrophysics Data System (ADS)

Musharbash, Eleonora; Nobile, Fabio

2018-02-01

In this paper we propose a method for the strong imposition of random Dirichlet boundary conditions in the Dynamical Low Rank (DLR) approximation of parabolic PDEs and, in particular, incompressible Navier Stokes equations. We show that the DLR variational principle can be set in the constrained manifold of all S rank random fields with a prescribed value on the boundary, expressed in low rank format, with rank smaller then S. We characterize the tangent space to the constrained manifold by means of a Dual Dynamically Orthogonal (Dual DO) formulation, in which the stochastic modes are kept orthonormal and the deterministic modes satisfy suitable boundary conditions, consistent with the original problem. The Dual DO formulation is also convenient to include the incompressibility constraint, when dealing with incompressible Navier Stokes equations. We show the performance of the proposed Dual DO approximation on two numerical test cases: the classical benchmark of a laminar flow around a cylinder with random inflow velocity, and a biomedical application for simulating blood flow in realistic carotid artery reconstructed from MRI data with random inflow conditions coming from Doppler measurements.

Study on the mapping of dark matter clustering from real space to redshift space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Yi; Song, Yong-Seon, E-mail: yizheng@kasi.re.kr, E-mail: ysong@kasi.re.kr

The mapping of dark matter clustering from real space to redshift space introduces the anisotropic property to the measured density power spectrum in redshift space, known as the redshift space distortion effect. The mapping formula is intrinsically non-linear, which is complicated by the higher order polynomials due to indefinite cross correlations between the density and velocity fields, and the Finger-of-God effect due to the randomness of the peculiar velocity field. Whilst the full higher order polynomials remain unknown, the other systematics can be controlled consistently within the same order truncation in the expansion of the mapping formula, as shown inmore » this paper. The systematic due to the unknown non-linear density and velocity fields is removed by separately measuring all terms in the expansion directly using simulations. The uncertainty caused by the velocity randomness is controlled by splitting the FoG term into two pieces, 1) the ''one-point' FoG term being independent of the separation vector between two different points, and 2) the ''correlated' FoG term appearing as an indefinite polynomials which is expanded in the same order as all other perturbative polynomials. Using 100 realizations of simulations, we find that the Gaussian FoG function with only one scale-independent free parameter works quite well, and that our new mapping formulation accurately reproduces the observed 2-dimensional density power spectrum in redshift space at the smallest scales by far, up to k ∼ 0.2 Mpc{sup -1}, considering the resolution of future experiments.« less

Modelling of squall with the generalised kinetic equation

NASA Astrophysics Data System (ADS)

Annenkov, Sergei; Shrira, Victor

2014-05-01

We study the long-term evolution of random wind waves using the new generalised kinetic equation (GKE). The GKE derivation [1] does not assume the quasi-stationarity of a random wave field. In contrast with the Hasselmann kinetic equation, the GKE can describe fast spectral changes occurring when a wave field is driven out of a quasi-equilibrium state by a fast increase or decrease of wind, or by other factors. In these cases, a random wave field evolves on the dynamic timescale typical of coherent wave processes, rather than on the kinetic timescale predicted by the conventional statistical theory. Besides that, the generalised theory allows to trace the evolution of higher statistical moments of the field, notably the kurtosis, which is important for assessing the risk of freak waves and other applications. A new efficient and highly parallelised algorithm for the numerical simulation of the generalised kinetic equation is presented and discussed. Unlike in the case of the Hasselmann equation, the algorithm takes into account all (resonant and non-resonant) nonlinear wave interactions, but only approximately resonant interactions contribute to the spectral evolution. However, counter-intuitively, all interactions contribute to the kurtosis. Without forcing or dissipation, the algorithm is shown to conserve the relevant integrals. We show that under steady wind forcing the wave field evolution predicted by the GKE is close to the predictions of the conventional statistical theory, which is applicable in this case. In particular, we demonstrate the known long-term asymptotics for the evolution of the spectrum. When the wind forcing is not steady (in the simplest case, an instant increase or decrease of wind occurs), the generalised theory is the only way to study the spectral evolution, apart from the direct numerical simulation. The focus of the work is a detailed analysis of the fast evolution after an instant change of forcing, and of the subsequent transition to the new quasi-stationary state of a wave field. It is shown that both increase and decrease of wind lead to a significant transient increase of the dynamic kurtosis, although these changes remain small compared to the changes of the other component of the kurtosis, which is due to bound harmonics. A special consideration is given to the case of the squall, i.e. an instant and large (by a factor of 2-4) increase of wind, which lasts for O(102) characteristic wave periods. We show that fast adjustment processes lead to the formation of a transient spectrum, which has a considerably narrower peak than the spectra developed under a steady forcing. These transient spectra differ qualitatively from those predicted by the Hasselmann kinetic equation under the squall with the same parameters. 1. S.Annenkov, V.Shrira (2006) Role of non-resonant interactions in evolution of nonlinear random water wave fields, J. Fluid Mech. 561, 181-207.

Two-dimensional Topology of the Two-Degree Field Galaxy Redshift Survey

NASA Astrophysics Data System (ADS)

Hoyle, Fiona; Vogeley, Michael S.; Gott, J. Richard, III

2002-05-01

We study the topology of the publicly available data released by the Two Degree Field Galaxy Redshift Survey team (2dF GRS). The 2dF GRS data contain over 100,000 galaxy redshifts with a magnitude limit of bJ=19.45 and is the largest such survey to date. The data lie over a wide range of right ascension (75° strips) but only within a narrow range of declination (10° and 15° strips). This allows measurements of the two-dimensional genus to be made. We find that the genus curves of the north Galactic pole (NGP) and south Galactic pole (SGP) are slightly different. The NGP displays a slight meatball shift topology, whereas the SGP displays a bubble-like topology. The current SGP data also have a slightly higher genus amplitude. In both cases, a slight excess of overdense regions is found over underdense regions. We assess the significance of these features using mock catalogs drawn from the Virgo Consortium's Hubble volume ΛCDM z=0 simulation. We find that differences between the NGP and SGP genus curves are only significant at the 1 σ level. The average genus curve of the 2dF GRS agrees well with that extracted from the ΛCDM mock catalogs. We also use the simulations to assess how the current incompleteness of the survey (the strips are not completely filled in) affects the measurement of the genus and find that we are not sensitive to the geometry; there are enough data in the current sample to trace the isolated high- and low-density regions. We compare the amplitude of the 2dF GRS genus curve to the amplitude of the genus curve of a Gaussian random field that we construct to have the same power spectrum as the 2dF GRS. In previous three-dimensional analyses, it was found that the genus curve of observed samples was lower than the Gaussian random field curve, presumably because of high-order correlations present in the data. However, we find that the 2dF GRS genus curve has an amplitude that is slightly higher than that of the power-spectrum-matched Gaussian random field. We suggest that in two dimensions the genus measurement is less sensitive to nonlinear effects because of the effective smoothing over the thickness of the slice.

Atomistic modeling of thermomechanical properties of SWNT/Epoxy nanocomposites

NASA Astrophysics Data System (ADS)

Fasanella, Nicholas; Sundararaghavan, Veera

2015-09-01

Molecular dynamics simulations are performed to compute thermomechanical properties of cured epoxy resins reinforced with pristine and covalently functionalized carbon nanotubes. A DGEBA-DDS epoxy network was built using the ‘dendrimer’ growth approach where 75% of available epoxy sites were cross-linked. The epoxy model is verified through comparisons to experiments, and simulations are performed on nanotube reinforced cross-linked epoxy matrix using the CVFF force field in LAMMPS. Full stiffness matrices and linear coefficient of thermal expansion vectors are obtained for the nanocomposite. Large increases in stiffness and large decreases in thermal expansion were seen along the direction of the nanotube for both nanocomposite systems when compared to neat epoxy. The direction transverse to nanotube saw a 40% increase in stiffness due to covalent functionalization over neat epoxy at 1 K whereas the pristine nanotube system only saw a 7% increase due to van der Waals effects. The functionalized SWNT/epoxy nanocomposite showed an additional 42% decrease in thermal expansion along the nanotube direction when compared to the pristine SWNT/epoxy nanocomposite. The stiffness matrices are rotated over every possible orientation to simulate the effects of an isotropic system of randomly oriented nanotubes in the epoxy. The randomly oriented covalently functionalized SWNT/Epoxy nanocomposites showed substantial improvements over the plain epoxy in terms of higher stiffness (200% increase) and lower thermal expansion (32% reduction). Through MD simulations, we develop means to build simulation cells, perform annealing to reach correct densities, compute thermomechanical properties and compare with experiments.

Simulation of Cooling and Pressure Effects on Inflated Pahoehoe Lava Flows

NASA Technical Reports Server (NTRS)

Glaze, Lori S.; Baloga, Stephen M.

2016-01-01

Pahoehoe lobes are often emplaced by the advance of discrete toes accompanied by inflation of the lobe surface. Many random effects complicate modeling lobe emplacement, such as the location and orientation of toe breakouts, their dimensions, mechanical strength of the crust, micro-topography and a host of other factors. Models that treat the movement of lava parcels as a random walk have explained some of the overall features of emplacement. However, cooling of the surface and internal pressurization of the fluid interior has not been modeled. This work reports lobe simulations that explicitly incorporate 1) cooling of surface lava parcels, 2) the propensity of breakouts to occur at warmer margins that are mechanically weaker than cooler ones, and 3) the influence of internal pressurization associated with inflation. The surface temperature is interpreted as a surrogate for the mechanic strength of the crust at each location and is used to determine the probability of a lava parcel transfer from that location. When only surface temperature is considered, the morphology and dimensions of simulated lobes are indistinguishable from equiprobable simulations. However, inflation within a lobe transmits pressure to all connected fluid locations with the warmer margins being most susceptible to breakouts and expansion. Simulations accounting for internal pressurization feature morphologies and dimensions that are dramatically different from the equiprobable and temperature-dependent models. Even on flat subsurfaces the pressure-dependent model produces elongate lobes with distinct directionality. Observables such as topographic profiles, aspect ratios, and maximum extents should be readily distinguishable in the field.

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

NASA Technical Reports Server (NTRS)

Costes, Sylvain V.; Ponomarev, Artem; Chen, James L.; Cucinotta, Francis A.; Barcellos-Hoff, Helen

2007-01-01

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

Brain tumor segmentation in 3D MRIs using an improved Markov random field model

NASA Astrophysics Data System (ADS)

Yousefi, Sahar; Azmi, Reza; Zahedi, Morteza

2011-10-01

Markov Random Field (MRF) models have been recently suggested for MRI brain segmentation by a large number of researchers. By employing Markovianity, which represents the local property, MRF models are able to solve a global optimization problem locally. But they still have a heavy computation burden, especially when they use stochastic relaxation schemes such as Simulated Annealing (SA). In this paper, a new 3D-MRF model is put forward to raise the speed of the convergence. Although, search procedure of SA is fairly localized and prevents from exploring the same diversity of solutions, it suffers from several limitations. In comparison, Genetic Algorithm (GA) has a good capability of global researching but it is weak in hill climbing. Our proposed algorithm combines SA and an improved GA (IGA) to optimize the solution which speeds up the computation time. What is more, this proposed algorithm outperforms the traditional 2D-MRF in quality of the solution.

A multiscale Markov random field model in wavelet domain for image segmentation

NASA Astrophysics Data System (ADS)

Dai, Peng; Cheng, Yu; Wang, Shengchun; Du, Xinyu; Wu, Dan

2017-07-01

The human vision system has abilities for feature detection, learning and selective attention with some properties of hierarchy and bidirectional connection in the form of neural population. In this paper, a multiscale Markov random field model in the wavelet domain is proposed by mimicking some image processing functions of vision system. For an input scene, our model provides its sparse representations using wavelet transforms and extracts its topological organization using MRF. In addition, the hierarchy property of vision system is simulated using a pyramid framework in our model. There are two information flows in our model, i.e., a bottom-up procedure to extract input features and a top-down procedure to provide feedback controls. The two procedures are controlled simply by two pyramidal parameters, and some Gestalt laws are also integrated implicitly. Equipped with such biological inspired properties, our model can be used to accomplish different image segmentation tasks, such as edge detection and region segmentation.

Effect of antifreeze protein on heterogeneous ice nucleation based on a two-dimensional random-field Ising model

NASA Astrophysics Data System (ADS)

Dong, Zhen; Wang, Jianjun; Zhou, Xin

2017-05-01

Antifreeze proteins (AFPs) are the key biomolecules that protect many species from suffering the extreme conditions. Their unique properties of antifreezing provide the potential of a wide range of applications. Inspired by the present experimental approaches of creating an antifreeze surface by coating AFPs, here we present a two-dimensional random-field lattice Ising model to study the effect of AFPs on heterogeneous ice nucleation. The model shows that both the size and the free-energy effect of individual AFPs and their surface coverage dominate the antifreeze capacity of an AFP-coated surface. The simulation results are consistent with the recent experiments qualitatively, revealing the origin of the surprisingly low antifreeze capacity of an AFP-coated surface when the coverage is not particularly high as shown in experiment. These results will hopefully deepen our understanding of the antifreeze effects and thus be potentially useful for designing novel antifreeze coating materials based on biomolecules.

Branched flow and caustics in random media with magnetic fields

NASA Astrophysics Data System (ADS)

Metzger, Jakob; Fleischmann, Ragnar; Geisel, Theo

2009-03-01

Classical particles as well as quantum mechanical waves exhibit complex behaviour when propagating through random media. One of the dominant features of the dynamics in correlated, weak disorder potentials is the branching of the flow. This can be observed in several physical systems, most notably in the electron flow in two-dimensional electron gases [1], and has also been used to describe the formation of freak waves [2]. We present advances in the theoretical understanding and numerical simulation of classical branched flows in magnetic fields. In particular, we study branching statistics and branch density profiles. Our results have direct consequences for experiments which measure transport properties in electronic systems [3].[1] e.g. M. A. Topinka et al., Nature 410, 183 (2001), M. P. Jura et al., Nature Physics 3, 841 (2007)[2] E. J. Heller, L. Kaplan and A. Dahlen, J. Geophys. Res., 113, C09023 (2008)[3] J. J. Metzger, R. Fleischmann and T. Geisel, in preparation

Choice of optical system is critical for the security of double random phase encryption systems

NASA Astrophysics Data System (ADS)

Muniraj, Inbarasan; Guo, Changliang; Malallah, Ra'ed; Cassidy, Derek; Zhao, Liang; Ryle, James P.; Healy, John J.; Sheridan, John T.

2017-06-01

The linear canonical transform (LCT) is used in modeling a coherent light-field propagation through first-order optical systems. Recently, a generic optical system, known as the quadratic phase encoding system (QPES), for encrypting a two-dimensional image has been reported. In such systems, two random phase keys and the individual LCT parameters (α,β,γ) serve as secret keys of the cryptosystem. It is important that such encryption systems also satisfy some dynamic security properties. We, therefore, examine such systems using two cryptographic evaluation methods, the avalanche effect and bit independence criterion, which indicate the degree of security of the cryptographic algorithms using QPES. We compared our simulation results with the conventional Fourier and the Fresnel transform-based double random phase encryption (DRPE) systems. The results show that the LCT-based DRPE has an excellent avalanche and bit independence characteristics compared to the conventional Fourier and Fresnel-based encryption systems.

Topological signatures of interstellar magnetic fields - I. Betti numbers and persistence diagrams

NASA Astrophysics Data System (ADS)

Makarenko, Irina; Shukurov, Anvar; Henderson, Robin; Rodrigues, Luiz F. S.; Bushby, Paul; Fletcher, Andrew

2018-04-01

The interstellar medium (ISM) is a magnetized system in which transonic or supersonic turbulence is driven by supernova explosions. This leads to the production of intermittent, filamentary structures in the ISM gas density, whilst the associated dynamo action also produces intermittent magnetic fields. The traditional theory of random functions, restricted to second-order statistical moments (or power spectra), does not adequately describe such systems. We apply topological data analysis (TDA), sensitive to all statistical moments and independent of the assumption of Gaussian statistics, to the gas density fluctuations in a magnetohydrodynamic simulation of the multiphase ISM. This simulation admits dynamo action, so produces physically realistic magnetic fields. The topology of the gas distribution, with and without magnetic fields, is quantified in terms of Betti numbers and persistence diagrams. Like the more standard correlation analysis, TDA shows that the ISM gas density is sensitive to the presence of magnetic fields. However, TDA gives us important additional information that cannot be obtained from correlation functions. In particular, the Betti numbers per correlation cell are shown to be physically informative. Magnetic fields make the ISM more homogeneous, reducing the abundance of both isolated gas clouds and cavities, with a stronger effect on the cavities. Remarkably, the modification of the gas distribution by magnetic fields is captured by the Betti numbers even in regions more than 300 pc from the mid-plane, where the magnetic field is weaker and correlation analysis fails to detect any signatures of magnetic effects.

Numerical Simulation of Electromagnetic Field Variation in the Lithosphere-Atmosphere-Ionosphere Associated with Seismogenic Process in a Curvature Coordinate System

NASA Astrophysics Data System (ADS)

Liu, L.; Zhao, Z.; Wang, Y.; Huang, Q.

2013-12-01

The lithosphere-atmosphere- ionosphere (LAI) system formed an electromagnetic (EM) cavity that hosts the EM field excited by electric currents generated by lightning and other natural sources. There have also been numerous reports on variations of the EM field existing in LAI system prior to some significance earthquakes. We simulated the EM field in the lithosphere-ionosphere waveguide with a whole-earth model using a curvature coordinate by the hybrid pseudo-spectral and finite difference time domain method. Considering the seismogensis as a fully coupled seismoelectric process, we simulate the seismic wave and the EM wave in this 2D model. In the model we have observed the excitation of the Schumann Resonance (SR) as the background EM field generated by randomly placed electric-current impulses within the lowest 10 kilometers of the atmosphere. The diurnal variation and the latitude-dependence in ion concentration in the ionosphere are included in the model. After the SR reaching a steady state, an electric impulse is introduced in the shallow lithosphere to mimic the seismogenic process (pre-, co- and post-seismic) to assess the possible precursory effects on SR strength and frequency. The modeling results can explain the observed fact of why SR has a much more sensitive response to continental earthquakes, and much less response to oceanic events. The fundamental reason is simply due to the shielding effect of the conductive ocean that prevents effective radiation of the seismoelectric signals from oceanic earthquake events into the LAI waveguide.

Spontaneous emergence of rogue waves in partially coherent waves: A quantitative experimental comparison between hydrodynamics and optics

NASA Astrophysics Data System (ADS)

El Koussaifi, R.; Tikan, A.; Toffoli, A.; Randoux, S.; Suret, P.; Onorato, M.

2018-01-01

Rogue waves are extreme and rare fluctuations of the wave field that have been discussed in many physical systems. Their presence substantially influences the statistical properties of a partially coherent wave field, i.e., a wave field characterized by a finite band spectrum with random Fourier phases. Their understanding is fundamental for the design of ships and offshore platforms. In many meteorological conditions waves in the ocean are characterized by the so-called Joint North Sea Wave Project (JONSWAP) spectrum. Here we compare two unique experimental results: the first one has been performed in a 270 m wave tank and the other in optical fibers. In both cases, waves characterized by a JONSWAP spectrum and random Fourier phases have been launched at the input of the experimental device. The quantitative comparison, based on an appropriate scaling of the two experiments, shows a very good agreement between the statistics in hydrodynamics and optics. Spontaneous emergence of heavy tails in the probability density function of the wave amplitude is observed in both systems. The results demonstrate the universal features of rogue waves and provide a fundamental and explicit bridge between two important fields of research. Numerical simulations are also compared with experimental results.

Spontaneous emergence of rogue waves in partially coherent waves: A quantitative experimental comparison between hydrodynamics and optics.

PubMed

El Koussaifi, R; Tikan, A; Toffoli, A; Randoux, S; Suret, P; Onorato, M

2018-01-01

Rogue waves are extreme and rare fluctuations of the wave field that have been discussed in many physical systems. Their presence substantially influences the statistical properties of a partially coherent wave field, i.e., a wave field characterized by a finite band spectrum with random Fourier phases. Their understanding is fundamental for the design of ships and offshore platforms. In many meteorological conditions waves in the ocean are characterized by the so-called Joint North Sea Wave Project (JONSWAP) spectrum. Here we compare two unique experimental results: the first one has been performed in a 270 m wave tank and the other in optical fibers. In both cases, waves characterized by a JONSWAP spectrum and random Fourier phases have been launched at the input of the experimental device. The quantitative comparison, based on an appropriate scaling of the two experiments, shows a very good agreement between the statistics in hydrodynamics and optics. Spontaneous emergence of heavy tails in the probability density function of the wave amplitude is observed in both systems. The results demonstrate the universal features of rogue waves and provide a fundamental and explicit bridge between two important fields of research. Numerical simulations are also compared with experimental results.

Broken Ergodicity in MHD Turbulence in a Spherical Domain

NASA Technical Reports Server (NTRS)

Shebalin, John V.; wang, Yifan

2011-01-01

Broken ergodicity (BE) occurs in Fourier method numerical simulations of ideal, homogeneous, incompressible magnetohydrodynamic (MHD) turbulence. Although naive statistical theory predicts that Fourier coefficients of fluid velocity and magnetic field are zero-mean random variables, numerical simulations clearly show that low-wave-number coefficients have non-zero mean values that can be very large compared to the associated standard deviation. In other words, large-scale coherent structure (i.e., broken ergodicity) in homogeneous MHD turbulence can spontaneously grow out of random initial conditions. Eigenanalysis of the modal covariance matrices in the probability density functions of ideal statistical theory leads to a theoretical explanation of observed BE in homogeneous MHD turbulence. Since dissipation is minimal at the largest scales, BE is also relevant for resistive magnetofluids, as evidenced in numerical simulations. Here, we move beyond model magnetofluids confined by periodic boxes to examine BE in rotating magnetofluids in spherical domains using spherical harmonic expansions along with suitable boundary conditions. We present theoretical results for 3-D and 2-D spherical models and also present computational results from dynamical simulations of 2-D MHD turbulence on a rotating spherical surface. MHD turbulence on a 2-D sphere is affected by Coriolus forces, while MHD turbulence on a 2-D plane is not, so that 2-D spherical models are a useful (and simpler) intermediate stage on the path to understanding the much more complex 3-D spherical case.

Modeling the migration of platinum nanoparticles on surfaces using a kinetic Monte Carlo approach

DOE PAGES

Li, Lin; Plessow, Philipp N.; Rieger, Michael; ...

2017-02-15

We propose a kinetic Monte Carlo (kMC) model for simulating the movement of platinum particles on supports, based on atom-by-atom diffusion on the surface of the particle. The proposed model was able to reproduce equilibrium cluster shapes predicted using Wulff-construction. The diffusivity of platinum particles was simulated both purely based on random motion and assisted using an external field that causes a drift velocity. The overall particle diffusivity increases with temperature; however, the extracted activation barrier appears to be temperature independent. Additionally, this barrier was found to increase with particle size, as well as, with the adhesion between the particlemore » and the support.« less

Sustained currents in coupled diffusive systems

NASA Astrophysics Data System (ADS)

Larralde, Hernán; Sanders, David P.

2014-08-01

Coupling two diffusive systems may give rise to a nonequilibrium stationary state (NESS) with a non-trivial persistent, circulating current. We study a simple example that is exactly soluble, consisting of random walkers with different biases towards a reflecting boundary, modelling, for example, Brownian particles with different charge states in an electric field. We obtain analytical expressions for the concentrations and currents in the NESS for this model, and exhibit the main features of the system by numerical simulation.

SU-E-T-292: Sensitivity of Fractionated Lung IMPT Treatments to Setup Uncertainties and Motion Effects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dowdell, S; Grassberger, C; Paganetti, H

2014-06-01

Purpose: Evaluate the sensitivity of intensity-modulated proton therapy (IMPT) lung treatments to systematic and random setup uncertainties combined with motion effects. Methods: Treatment plans with single-field homogeneity restricted to ±20% (IMPT-20%) were compared to plans with no restriction (IMPT-full). 4D Monte Carlo simulations were performed for 10 lung patients using the patient CT geometry with either ±5mm systematic or random setup uncertainties applied over a 35 × 2.5Gy(RBE) fractionated treatment course. Intra-fraction, inter-field and inter-fraction motions were investigated. 50 fractionated treatments with systematic or random setup uncertainties applied to each fraction were generated for both IMPT delivery methods and threemore » energy-dependent spot sizes (big spots - BS σ=18-9mm, intermediate spots - IS σ=11-5mm, small spots - SS σ=4-2mm). These results were compared to a Monte Carlo recalculation of the original treatment plan, with results presented as the difference in EUD (ΔEUD), V{sub 95} (ΔV{sub 95}) and target homogeneity (ΔD{sub 1}–D{sub 99}) between the 4D simulations and the Monte Carlo calculation on the planning CT. Results: The standard deviations in the ΔEUD were 1.95±0.47(BS), 1.85±0.66(IS) and 1.31±0.35(SS) times higher in IMPT-full compared to IMPT-20% when ±5mm systematic setup uncertainties were applied. The ΔV{sub 95} variations were also 1.53±0.26(BS), 1.60±0.50(IS) and 1.38±0.38(SS) times higher for IMPT-full. For random setup uncertainties, the standard deviations of the ΔEUD from 50 simulated fractionated treatments were 1.94±0.90(BS), 2.13±1.08(IS) and 1.45±0.57(SS) times higher in IMPTfull compared to IMPT-20%. For all spot sizes considered, the ΔD{sub 1}-D{sub 99} coincided within the uncertainty limits for the two IMPT delivery methods, with the mean value always higher for IMPT-full. Statistical analysis showed significant differences between the IMPT-full and IMPT-20% dose distributions for the majority of scenarios studied. Conclusion: Lung IMPT-full treatments are more sensitive to both systematic and random setup uncertainties compared to IMPT-20%. This work was supported by the NIH R01 CA111590.« less

The importance of fluctuations in fluid mixing.

PubMed

Kadau, Kai; Rosenblatt, Charles; Barber, John L; Germann, Timothy C; Huang, Zhibin; Carlès, Pierre; Alder, Berni J

2007-05-08

A ubiquitous example of fluid mixing is the Rayleigh-Taylor instability, in which a heavy fluid initially sits atop a light fluid in a gravitational field. The subsequent development of the unstable interface between the two fluids is marked by several stages. At first, each interface mode grows exponentially with time before transitioning to a nonlinear regime characterized by more complex hydrodynamic mixing. Unfortunately, traditional continuum modeling of this process has generally been in poor agreement with experiment. Here, we indicate that the natural, random fluctuations of the flow field present in any fluid, which are neglected in continuum models, can lead to qualitatively and quantitatively better agreement with experiment. We performed billion-particle atomistic simulations and magnetic levitation experiments with unprecedented control of initial interface conditions. A comparison between our simulations and experiments reveals good agreement in terms of the growth rate of the mixing front as well as the new observation of droplet breakup at later times. These results improve our understanding of many fluid processes, including interface phenomena that occur, for example, in supernovae, the detachment of droplets from a faucet, and ink jet printing. Such instabilities are also relevant to the possible energy source of inertial confinement fusion, in which a millimeter-sized capsule is imploded to initiate nuclear fusion reactions between deuterium and tritium. Our results suggest that the applicability of continuum models would be greatly enhanced by explicitly including the effects of random fluctuations.

Computational Study of the Blood Flow in Three Types of 3D Hollow Fiber Membrane Bundles

PubMed Central

Zhang, Jiafeng; Chen, Xiaobing; Ding, Jun; Fraser, Katharine H.; Ertan Taskin, M.; Griffith, Bartley P.; Wu, Zhongjun J.

2013-01-01

The goal of this study is to develop a computational fluid dynamics (CFD) modeling approach to better estimate the blood flow dynamics in the bundles of the hollow fiber membrane based medical devices (i.e., blood oxygenators, artificial lungs, and hemodialyzers). Three representative types of arrays, square, diagonal, and random with the porosity value of 0.55, were studied. In addition, a 3D array with the same porosity was studied. The flow fields between the individual fibers in these arrays at selected Reynolds numbers (Re) were simulated with CFD modeling. Hemolysis is not significant in the fiber bundles but the platelet activation may be essential. For each type of array, the average wall shear stress is linearly proportional to the Re. For the same Re but different arrays, the average wall shear stress also exhibits a linear dependency on the pressure difference across arrays, while Darcy′s law prescribes a power-law relationship, therefore, underestimating the shear stress level. For the same Re, the average wall shear stress of the diagonal array is approximately 3.1, 1.8, and 2.0 times larger than that of the square, random, and 3D arrays, respectively. A coefficient C is suggested to correlate the CFD predicted data with the analytical solution, and C is 1.16, 1.51, and 2.05 for the square, random, and diagonal arrays in this paper, respectively. It is worth noting that C is strongly dependent on the array geometrical properties, whereas it is weakly dependent on the flow field. Additionally, the 3D fiber bundle simulation results show that the three-dimensional effect is not negligible. Specifically, velocity and shear stress distribution can vary significantly along the fiber axial direction. PMID:24141394

Observational Signatures of Coronal Heating

NASA Astrophysics Data System (ADS)

Dahlburg, R. B.; Einaudi, G.; Ugarte-Urra, I.; Warren, H. P.; Rappazzo, A. F.; Velli, M.; Taylor, B.

2016-12-01

Recent research on observational signatures of turbulent heating of a coronal loop will be discussed. The evolution of the loop is is studied by means of numericalsimulations of the fully compressible three-dimensionalmagnetohydrodynamic equations using the HYPERION code. HYPERION calculates the full energy cycle involving footpoint convection, magnetic reconnection,nonlinear thermal conduction and optically thin radiation.The footpoints of the loop magnetic field are convected by random photospheric motions. As a consequence the magnetic field in the loop is energized and develops turbulent nonlinear dynamics characterized by the continuous formation and dissipation of field-aligned current sheets: energy is deposited at small scales where heating occurs. Dissipation is non-uniformly distributed so that only a fraction of thecoronal mass and volume gets heated at any time. Temperature and density are highly structured at scales which, in the solar corona, remain observationally unresolved: the plasma of the simulated loop is multi-thermal, where highly dynamical hotter and cooler plasma strands arescattered throughout the loop at sub-observational scales. Typical simulated coronal loops are 50000 km length and have axial magnetic field intensities ranging from 0.01 to 0.04 Tesla.To connect these simulations to observations the computed numberdensities and temperatures are used to synthesize the intensities expected inemission lines typically observed with the Extreme ultraviolet Imaging Spectrometer(EIS) on Hinode. These intensities are then employed to compute differentialemission measure distributions, which are found to be very similar to those derivedfrom observations of solar active regions.

The use of augmented reality glasses in central line simulation: “see one, simulate many, do one competently, and teach everyone”

PubMed Central

Huang, Cynthia Y; Thomas, Jonathan B; Alismail, Abdullah; Cohen, Avi; Almutairi, Waleed; Daher, Noha S; Terry, Michael H; Tan, Laren D

2018-01-01

Objective The aim of this study was to investigate the feasibility of using augmented reality (AR) glasses in central line simulation by novice operators and compare its efficacy to standard central line simulation/teaching. Design This was a prospective randomized controlled study enrolling 32 novice operators. Subjects were randomized on a 1:1 basis to either simulation using the augmented virtual reality glasses or simulation using conventional instruction. Setting The study was conducted in tertiary-care urban teaching hospital. Subjects A total of 32 adult novice central line operators with no visual or auditory impairments were enrolled. Medical doctors, respiratory therapists, and sleep technicians were recruited from the medical field. Measurements and main results The mean time for AR placement in the AR group was 71±43 s, and the time to internal jugular (IJ) cannulation was 316±112 s. There was no significant difference in median (minimum, maximum) time (seconds) to IJ cannulation for those who were in the AR group and those who were not (339 [130, 550] vs 287 [35, 475], p=0.09), respectively. There was also no significant difference between the two groups in median total procedure time (524 [329, 792] vs 469 [198, 781], p=0.29), respectively. There was a significant difference in the adherence level between the two groups favoring the AR group (p=0.003). Conclusion AR simulation of central venous catheters in manikins is feasible and efficacious in novice operators as an educational tool. Future studies are recommended in this area as it is a promising area of medical education. PMID:29785148

Construction of Solar-Wind-Like Magnetic Fields

NASA Technical Reports Server (NTRS)

Roberts, Dana Aaron

2012-01-01

Fluctuations in the solar wind fields tend to not only have velocities and magnetic fields correlated in the sense consistent with Alfven waves traveling from the Sun, but they also have the magnitude of the magnetic field remarkably constant despite their being broadband. This paper provides, for the first time, a method for constructing fields with nearly constant magnetic field, zero divergence, and with any specified power spectrum for the fluctuations of the components of the field. Every wave vector, k, is associated with two polarizations the relative phases of these can be chosen to minimize the variance of the field magnitude while retaining the\\random character of the fields. The method is applied to a case with one spatial coordinate that demonstrates good agreement with observed time series and power spectra of the magnetic field in the solar wind, as well as with the distribution of the angles of rapid changes (discontinuities), thus showing a deep connection between two seemingly unrelated issues. It is suggested that using this construction will lead to more realistic simulations of solar wind turbulence and of the propagation of energetic particles.

Computational Model Prediction and Biological Validation Using Simplified Mixed Field Exposures for the Development of a GCR Reference Field

NASA Technical Reports Server (NTRS)

Hada, M.; Rhone, J.; Beitman, A.; Saganti, P.; Plante, I.; Ponomarev, A.; Slaba, T.; Patel, Z.

2018-01-01

The yield of chromosomal aberrations has been shown to increase in the lymphocytes of astronauts after long-duration missions of several months in space. Chromosome exchanges, especially translocations, are positively correlated with many cancers and are therefore a potential biomarker of cancer risk associated with radiation exposure. Although extensive studies have been carried out on the induction of chromosomal aberrations by low- and high-LET radiation in human lymphocytes, fibroblasts, and epithelial cells exposed in vitro, there is a lack of data on chromosome aberrations induced by low dose-rate chronic exposure and mixed field beams such as those expected in space. Chromosome aberration studies at NSRL will provide the biological validation needed to extend the computational models over a broader range of experimental conditions (more complicated mixed fields leading up to the galactic cosmic rays (GCR) simulator), helping to reduce uncertainties in radiation quality effects and dose-rate dependence in cancer risk models. These models can then be used to answer some of the open questions regarding requirements for a full GCR reference field, including particle type and number, energy, dose rate, and delivery order. In this study, we designed a simplified mixed field beam with a combination of proton, helium, oxygen, and iron ions with shielding or proton, helium, oxygen, and titanium without shielding. Human fibroblasts cells were irradiated with these mixed field beam as well as each single beam with acute and chronic dose rate, and chromosome aberrations (CA) were measured with 3-color fluorescent in situ hybridization (FISH) chromosome painting methods. Frequency and type of CA induced with acute dose rate and chronic dose rates with single and mixed field beam will be discussed. A computational chromosome and radiation-induced DNA damage model, BDSTRACKS (Biological Damage by Stochastic Tracks), was updated to simulate various types of CA induced by acute exposures of the mixed field beams used for the experiments. The chromosomes were simulated by a polymer random walk algorithm with restrictions to their respective domains in the nucleus [1]. The stochastic dose to the nucleus was calculated with the code RITRACKS [2]. Irradiation of a target volume by a mixed field of ions was implemented within RITRACKs, and the fields of ions can be delivered over specific periods of time, allowing the simulation of dose-rate effects. Similarly, particles of various types and energies extracted from a pre-calculated spectra of galactic cosmic rays (GCR) can be used in RITRACKS. The number and spatial location of DSBs (DNA double-strand breaks) were calculated in BDSTRACKS using the simulated chromosomes and local (voxel) dose. Assuming that DSBs led to chromosome breaks, and simulating the rejoining of damaged chromosomes occurring during repair, BDSTRACKS produces the yield of various types of chromosome aberrations as a function of time (only final yields are presented). A comparison between experimental and simulation results will be shown.

Broken Ergodicity in Ideal, Homogeneous, Incompressible Turbulence

NASA Technical Reports Server (NTRS)

Morin, Lee; Shebalin, John; Fu, Terry; Nguyen, Phu; Shum, Victor

2010-01-01

We discuss the statistical mechanics of numerical models of ideal homogeneous, incompressible turbulence and their relevance for dissipative fluids and magnetofluids. These numerical models are based on Fourier series and the relevant statistical theory predicts that Fourier coefficients of fluid velocity and magnetic fields (if present) are zero-mean random variables. However, numerical simulations clearly show that certain coefficients have a non-zero mean value that can be very large compared to the associated standard deviation. We explain this phenomena in terms of broken ergodicity', which is defined to occur when dynamical behavior does not match ensemble predictions on very long time-scales. We review the theoretical basis of broken ergodicity, apply it to 2-D and 3-D fluid and magnetohydrodynamic simulations of homogeneous turbulence, and show new results from simulations using GPU (graphical processing unit) computers.

Numerical simulation of turbulence and terahertz magnetosonic waves generation in collisionless plasmas

NASA Astrophysics Data System (ADS)

Kumar, Narender; Singh, Ram Kishor; Sharma, Swati; Uma, R.; Sharma, R. P.

2018-01-01

This paper presents numerical simulations of laser beam (x-mode) coupling with a magnetosonic wave (MSW) in a collisionless plasma. The coupling arises through ponderomotive non-linearity. The pump beam has been perturbed by a periodic perturbation that leads to the nonlinear evolution of the laser beam. It is observed that the frequency spectra of the MSW have peaks at terahertz frequencies. The simulation results show quite complex localized structures that grow with time. The ensemble averaged power spectrum has also been studied which indicates that the spectral index follows an approximate scaling of the order of ˜ k-2.1 at large scales and scaling of the order of ˜ k-3.6 at smaller scales. The results indicate considerable randomness in the spatial structure of the magnetic field profile which gives sufficient indication of turbulence.

A general approach to the electronic spin relaxation of Gd(III) complexes in solutions. Monte Carlo simulations beyond the Redfield limit

NASA Astrophysics Data System (ADS)

Rast, S.; Fries, P. H.; Belorizky, E.; Borel, A.; Helm, L.; Merbach, A. E.

2001-10-01

The time correlation functions of the electronic spin components of a metal ion without orbital degeneracy in solution are computed. The approach is based on the numerical solution of the time-dependent Schrödinger equation for a stochastic perturbing Hamiltonian which is simulated by a Monte Carlo algorithm using discrete time steps. The perturbing Hamiltonian is quite general, including the superposition of both the static mean crystal field contribution in the molecular frame and the usual transient ligand field term. The Hamiltonian of the static crystal field can involve the terms of all orders, which are invariant under the local group of the average geometry of the complex. In the laboratory frame, the random rotation of the complex is the only source of modulation of this Hamiltonian, whereas an additional Ornstein-Uhlenbeck process is needed to describe the time fluctuations of the Hamiltonian of the transient crystal field. A numerical procedure for computing the electronic paramagnetic resonance (EPR) spectra is proposed and discussed. For the [Gd(H2O)8]3+ octa-aqua ion and the [Gd(DOTA)(H2O)]- complex [DOTA=1,4,7,10-tetrakis(carboxymethyl)-1,4,7,10-tetraazacyclo dodecane] in water, the predictions of the Redfield relaxation theory are compared with those of the Monte Carlo approach. The Redfield approximation is shown to be accurate for all temperatures and for electronic resonance frequencies at and above X-band, justifying the previous interpretations of EPR spectra. At lower frequencies the transverse and longitudinal relaxation functions derived from the Redfield approximation display significantly faster decays than the corresponding simulated functions. The practical interest of this simulation approach is underlined.

Drop Spreading with Random Viscosity

NASA Astrophysics Data System (ADS)

Xu, Feng; Jensen, Oliver

2016-11-01

Airway mucus acts as a barrier to protect the lung. However as a biological material, its physical properties are known imperfectly and can be spatially heterogeneous. In this study we assess the impact of these uncertainties on the rate of spreading of a drop (representing an inhaled aerosol) over a mucus film. We model the film as Newtonian, having a viscosity that depends linearly on the concentration of a passive solute (a crude proxy for mucin proteins). Given an initial random solute (and hence viscosity) distribution, described as a Gaussian random field with a given correlation structure, we seek to quantify the uncertainties in outcomes as the drop spreads. Using lubrication theory, we describe the spreading of the drop in terms of a system of coupled nonlinear PDEs governing the evolution of film height and the vertically-averaged solute concentration. We perform Monte Carlo simulations to predict the variability in the drop centre location and width (1D) or area (2D). We show how simulation results are well described (at much lower computational cost) by a low-order model using a weak disorder expansion. Our results show for example how variability in the drop location is a non-monotonic function of the solute correlation length increases. Engineering and Physical Sciences Research Council.

The formation of magnetic silicide Fe3Si clusters during ion implantation

NASA Astrophysics Data System (ADS)

Balakirev, N.; Zhikharev, V.; Gumarov, G.

2014-05-01

A simple two-dimensional model of the formation of magnetic silicide Fe3Si clusters during high-dose Fe ion implantation into silicon has been proposed and the cluster growth process has been computer simulated. The model takes into account the interaction between the cluster magnetization and magnetic moments of Fe atoms random walking in the implanted layer. If the clusters are formed in the presence of the external magnetic field parallel to the implanted layer, the model predicts the elongation of the growing cluster in the field direction. It has been proposed that the cluster elongation results in the uniaxial magnetic anisotropy in the plane of the implanted layer, which is observed in iron silicide films ion-beam synthesized in the external magnetic field.

Simulation approach for the evaluation of tracking accuracy in radiotherapy: a preliminary study.

PubMed

Tanaka, Rie; Ichikawa, Katsuhiro; Mori, Shinichiro; Sanada, Sigeru

2013-01-01

Real-time tumor tracking in external radiotherapy can be achieved by diagnostic (kV) X-ray imaging with a dynamic flat-panel detector (FPD). It is important to keep the patient dose as low as possible while maintaining tracking accuracy. A simulation approach would be helpful to optimize the imaging conditions. This study was performed to develop a computer simulation platform based on a noise property of the imaging system for the evaluation of tracking accuracy at any noise level. Flat-field images were obtained using a direct-type dynamic FPD, and noise power spectrum (NPS) analysis was performed. The relationship between incident quantum number and pixel value was addressed, and a conversion function was created. The pixel values were converted into a map of quantum number using the conversion function, and the map was then input into the random number generator to simulate image noise. Simulation images were provided at different noise levels by changing the incident quantum numbers. Subsequently, an implanted marker was tracked automatically and the maximum tracking errors were calculated at different noise levels. The results indicated that the maximum tracking error increased with decreasing incident quantum number in flat-field images with an implanted marker. In addition, the range of errors increased with decreasing incident quantum number. The present method could be used to determine the relationship between image noise and tracking accuracy. The results indicated that the simulation approach would aid in determining exposure dose conditions according to the necessary tracking accuracy.

A model for bacterial colonization of sinking aggregates.

PubMed

Bearon, R N

2007-01-01

Sinking aggregates provide important nutrient-rich environments for marine bacteria. Quantifying the rate at which motile bacteria colonize such aggregations is important in understanding the microbial loop in the pelagic food web. In this paper, a simple analytical model is presented to predict the rate at which bacteria undergoing a random walk encounter a sinking aggregate. The model incorporates the flow field generated by the sinking aggregate, the swimming behavior of the bacteria, and the interaction of the flow with the swimming behavior. An expression for the encounter rate is computed in the limit of large Péclet number when the random walk can be approximated by a diffusion process. Comparison with an individual-based numerical simulation is also given.

Simulation study of localization of electromagnetic waves in two-dimensional random dipolar systems.

PubMed

Wang, Ken Kang-Hsin; Ye, Zhen

2003-12-01

We study the propagation and scattering of electromagnetic waves by random arrays of dipolar cylinders in a uniform medium. A set of self-consistent equations, incorporating all orders of multiple scattering of the electromagnetic waves, is derived from first principles and then solved numerically for electromagnetic fields. For certain ranges of frequencies, spatially localized electromagnetic waves appear in such a simple but realistic disordered system. Dependence of localization on the frequency, radiation damping, and filling factor is shown. The spatial behavior of the total, coherent, and diffusive waves is explored in detail, and found to comply with a physical intuitive picture. A phase diagram characterizing localization is presented, in agreement with previous investigations on other systems.

Nonparametric estimation of plant density by the distance method

USGS Publications Warehouse

Patil, S.A.; Burnham, K.P.; Kovner, J.L.

1979-01-01

A relation between the plant density and the probability density function of the nearest neighbor distance (squared) from a random point is established under fairly broad conditions. Based upon this relationship, a nonparametric estimator for the plant density is developed and presented in terms of order statistics. Consistency and asymptotic normality of the estimator are discussed. An interval estimator for the density is obtained. The modifications of this estimator and its variance are given when the distribution is truncated. Simulation results are presented for regular, random and aggregated populations to illustrate the nonparametric estimator and its variance. A numerical example from field data is given. Merits and deficiencies of the estimator are discussed with regard to its robustness and variance.

Mean-field equations for neuronal networks with arbitrary degree distributions.

PubMed

Nykamp, Duane Q; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex

2017-04-01

The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.

Influence of anisotropy on percolation and jamming of linear k-mers on square lattice with defects

NASA Astrophysics Data System (ADS)

Tarasevich, Yu Yu; Laptev, V. V.; Burmistrov, A. S.; Shinyaeva, T. S.

2015-09-01

By means of the Monte Carlo simulation, we study the layers produced by the random sequential adsorption of the linear rigid objects (k-mers also known as rigid or stiff rods, sticks, needles) onto the square lattice with defects in the presence of an external field. The value of k varies from 2 to 32. The point defects randomly and uniformly placed on the substrate hinder adsorption of the elongated objects. The external field affects isotropic deposition of the particles, consequently the deposited layers are anisotropic. We study the influence of the defect concentration, the length of the objects, and the external field on the percolation threshold and the jamming concentration. Our main findings are (i) the critical defect concentration at which the percolation never occurs even at jammed state decreases for short k-mers (k < 16) and increases for long k-mers (k > 16) as anisotropy increases, (ii) the corresponding critical k-mer concentration decreases with anisotropy growth, (iii) the jamming concentration decreases drastically with growth of k-mer length for any anisotropy, (iv) for short k-mers, the percolation threshold is almost insensitive to the defect concentration for any anisotropy.

Mean-field equations for neuronal networks with arbitrary degree distributions

NASA Astrophysics Data System (ADS)

Nykamp, Duane Q.; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex

2017-04-01

The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

Random Telegraph Signal Amplitudes in Sub 100 nm (Decanano) MOSFETs: A 3D 'Atomistic' Simulation Study

NASA Technical Reports Server (NTRS)

Asenov, Asen; Balasubramaniam, R.; Brown, A. R.; Davies, J. H.; Saini, Subhash

2000-01-01

In this paper we use 3D simulations to study the amplitudes of random telegraph signals (RTS) associated with the trapping of a single carrier in interface states in the channel of sub 100 nm (decanano) MOSFETs. Both simulations using continuous doping charge and random discrete dopants in the active region of the MOSFETs are presented. We have studied the dependence of the RTS amplitudes on the position of the trapped charge in the channel and on the device design parameters. We have observed a significant increase in the maximum RTS amplitude when discrete random dopants are employed in the simulations.

The cosmological principle is not in the sky

NASA Astrophysics Data System (ADS)

Park, Chan-Gyung; Hyun, Hwasu; Noh, Hyerim; Hwang, Jai-chan

2017-08-01

The homogeneity of matter distribution at large scales, known as the cosmological principle, is a central assumption in the standard cosmological model. The case is testable though, thus no longer needs to be a principle. Here we perform a test for spatial homogeneity using the Sloan Digital Sky Survey Luminous Red Galaxies (LRG) sample by counting galaxies within a specified volume with the radius scale varying up to 300 h-1 Mpc. We directly confront the large-scale structure data with the definition of spatial homogeneity by comparing the averages and dispersions of galaxy number counts with allowed ranges of the random distribution with homogeneity. The LRG sample shows significantly larger dispersions of number counts than the random catalogues up to 300 h-1 Mpc scale, and even the average is located far outside the range allowed in the random distribution; the deviations are statistically impossible to be realized in the random distribution. This implies that the cosmological principle does not hold even at such large scales. The same analysis of mock galaxies derived from the N-body simulation, however, suggests that the LRG sample is consistent with the current paradigm of cosmology, thus the simulation is also not homogeneous in that scale. We conclude that the cosmological principle is neither in the observed sky nor demanded to be there by the standard cosmological world model. This reveals the nature of the cosmological principle adopted in the modern cosmology paradigm, and opens a new field of research in theoretical cosmology.

SMURFLite: combining simplified Markov random fields with simulated evolution improves remote homology detection for beta-structural proteins into the twilight zone.

PubMed

Daniels, Noah M; Hosur, Raghavendra; Berger, Bonnie; Cowen, Lenore J

2012-05-01

One of the most successful methods to date for recognizing protein sequences that are evolutionarily related has been profile hidden Markov models (HMMs). However, these models do not capture pairwise statistical preferences of residues that are hydrogen bonded in beta sheets. These dependencies have been partially captured in the HMM setting by simulated evolution in the training phase and can be fully captured by Markov random fields (MRFs). However, the MRFs can be computationally prohibitive when beta strands are interleaved in complex topologies. We introduce SMURFLite, a method that combines both simplified MRFs and simulated evolution to substantially improve remote homology detection for beta structures. Unlike previous MRF-based methods, SMURFLite is computationally feasible on any beta-structural motif. We test SMURFLite on all propeller and barrel folds in the mainly-beta class of the SCOP hierarchy in stringent cross-validation experiments. We show a mean 26% (median 16%) improvement in area under curve (AUC) for beta-structural motif recognition as compared with HMMER (a well-known HMM method) and a mean 33% (median 19%) improvement as compared with RAPTOR (a well-known threading method) and even a mean 18% (median 10%) improvement in AUC over HHPred (a profile-profile HMM method), despite HHpred's use of extensive additional training data. We demonstrate SMURFLite's ability to scale to whole genomes by running a SMURFLite library of 207 beta-structural SCOP superfamilies against the entire genome of Thermotoga maritima, and make over a 100 new fold predictions. Availability and implementaion: A webserver that runs SMURFLite is available at: http://smurf.cs.tufts.edu/smurflite/

Temporal behavior of the effective diffusion coefficients for transport in heterogeneous saturated aquifers

NASA Astrophysics Data System (ADS)

Suciu, N.; Vamos, C.; Vereecken, H.; Vanderborght, J.; Hardelauf, H.

2003-04-01

When the small scale transport is modeled by a Wiener process and the large scale heterogeneity by a random velocity field, the effective coefficients, Deff, can be decomposed as sums between the local coefficient, D, a contribution of the random advection, Dadv, and a contribution of the randomness of the trajectory of plume center of mass, Dcm: Deff=D+Dadv-Dcm. The coefficient Dadv is similar to that introduced by Taylor in 1921, and more recent works associate it with the thermodynamic equilibrium. The ``ergodic hypothesis'' says that over large time intervals Dcm vanishes and the effect of the heterogeneity is described by Dadv=Deff-D. In this work we investigate numerically the long time behavior of the effective coefficients as well as the validity of the ergodic hypothesis. The transport in every realization of the velocity field is modeled with the Global Random Walk Algorithm, which is able to track as many particles as necessary to achieve a statistically reliable simulation of the process. Averages over realizations are further used to estimate mean coefficients and standard deviations. In order to remain in the frame of most of the theoretical approaches, the velocity field was generated in a linear approximation and the logarithm of the hydraulic conductivity was taken to be exponential decaying correlated with variance equal to 0.1. Our results show that even in these idealized conditions, the effective coefficients tend to asymptotic constant values only when the plume travels thousands of correlations lengths (while the first order theories usually predict Fickian behavior after tens of correlations lengths) and that the ergodicity conditions are still far from being met.

Scaling Laws for NanoFET Sensors

NASA Astrophysics Data System (ADS)

Wei, Qi-Huo; Zhou, Fu-Shan

2008-03-01

In this paper, we report our numerical studies of the scaling laws for nanoplate field-effect transistor (FET) sensors by simplifying the nanoplates as random resistor networks. Nanowire/tube FETs are included as the limiting cases where the device width goes small. Computer simulations show that the field effect strength exerted by the binding molecules has significant impact on the scaling behaviors. When the field effect strength is small, nanoFETs have little size and shape dependence. In contrast, when the field-effect strength becomes stronger, there exists a lower detection threshold for charge accumulation FETs and an upper detection threshold for charge depletion FET sensors. At these thresholds, the nanoFET devices undergo a transition between low and large sensitivities. These thresholds may set the detection limits of nanoFET sensors. We propose to eliminate these detection thresholds by employing devices with very short source-drain distance and large width.

A three-dimensional simulation of transition and early turbulence in a time-developing mixing layer

NASA Technical Reports Server (NTRS)

Cain, A. B.; Reynolds, W. C.; Ferziger, J. H.

1981-01-01

The physics of the transition and early turbulence regimes in the time developing mixing layer was investigated. The sensitivity of the mixing layer to the disturbance field of the initial condition is considered. The growth of the momentum thickness, the mean velocity profile, the turbulence kinetic energy, the Reynolds stresses, the anisotropy tensor, and particle track pictures of computations are all examined in an effort to better understand the physics of these regimes. The amplitude, spectrum shape, and random phases of the initial disturbance field were varied. A scheme of generating discrete orthogonal function expansions on some nonuniform grids was developed. All cases address the early or near field of the mixing layer. The most significant result shows that the secondary instability of the mixing layer is produced by spanwise variations in the straining field of the primary vortex structures.

Neutrality and evolvability of designed protein sequences

NASA Astrophysics Data System (ADS)

Bhattacherjee, Arnab; Biswas, Parbati

2010-07-01

The effect of foldability on protein’s evolvability is analyzed by a two-prong approach consisting of a self-consistent mean-field theory and Monte Carlo simulations. Theory and simulation models representing protein sequences with binary patterning of amino acid residues compatible with a particular foldability criteria are used. This generalized foldability criterion is derived using the high temperature cumulant expansion approximating the free energy of folding. The effect of cumulative point mutations on these designed proteins is studied under neutral condition. The robustness, protein’s ability to tolerate random point mutations is determined with a selective pressure of stability (ΔΔG) for the theory designed sequences, which are found to be more robust than that of Monte Carlo and mean-field-biased Monte Carlo generated sequences. The results show that this foldability criterion selects viable protein sequences more effectively compared to the Monte Carlo method, which has a marked effect on how the selective pressure shapes the evolutionary sequence space. These observations may impact de novo sequence design and its applications in protein engineering.

Managing numerical errors in random sequential adsorption

NASA Astrophysics Data System (ADS)

Cieśla, Michał; Nowak, Aleksandra

2016-09-01

Aim of this study is to examine the influence of a finite surface size and a finite simulation time on a packing fraction estimated using random sequential adsorption simulations. The goal of particular interest is providing hints on simulation setup to achieve desired level of accuracy. The analysis is based on properties of saturated random packing of disks on continuous and flat surfaces of different sizes.

Determination of Turboprop Reduction Gearbox System Fatigue Life and Reliability

NASA Technical Reports Server (NTRS)

Zaretsky, Erwin V.; Lewicki, David G.; Savage, Michael; Vlcek, Brian L.

2007-01-01

Two computational models to determine the fatigue life and reliability of a commercial turboprop gearbox are compared with each other and with field data. These models are (1) Monte Carlo simulation of randomly selected lives of individual bearings and gears comprising the system and (2) two-parameter Weibull distribution function for bearings and gears comprising the system using strict-series system reliability to combine the calculated individual component lives in the gearbox. The Monte Carlo simulation included the virtual testing of 744,450 gearboxes. Two sets of field data were obtained from 64 gearboxes that were first-run to removal for cause, were refurbished and placed back in service, and then were second-run until removal for cause. A series of equations were empirically developed from the Monte Carlo simulation to determine the statistical variation in predicted life and Weibull slope as a function of the number of gearboxes failed. The resultant L(sub 10) life from the field data was 5,627 hr. From strict-series system reliability, the predicted L(sub 10) life was 774 hr. From the Monte Carlo simulation, the median value for the L(sub 10) gearbox lives equaled 757 hr. Half of the gearbox L(sub 10) lives will be less than this value and the other half more. The resultant L(sub 10) life of the second-run (refurbished) gearboxes was 1,334 hr. The apparent load-life exponent p for the roller bearings is 5.2. Were the bearing lives to be recalculated with a load-life exponent p equal to 5.2, the predicted L(sub 10) life of the gearbox would be equal to the actual life obtained in the field. The component failure distribution of the gearbox from the Monte Carlo simulation was nearly identical to that using the strict-series system reliability analysis, proving the compatibility of these methods.

Integration of crosswell seismic data for simulating porosity in a heterogeneous carbonate aquifer

NASA Astrophysics Data System (ADS)

Emery, Xavier; Parra, Jorge

2013-11-01

A challenge for the geostatistical simulation of subsurface properties in mining, petroleum and groundwater applications is the integration of well logs and seismic measurements, which can provide information on geological heterogeneities at a wide range of scales. This paper presents a case study conducted at the Port Mayaca aquifer, located in western Martin County, Florida, in which it is of interest to simulate porosity, based on porosity logs at two wells and high-resolution crosswell seismic measurements of P-wave impedance. To this end, porosity and impedance are transformed into cross-correlated Gaussian random fields, using local transformations. The model parameters (transformation functions, mean values and correlation structure of the transformed fields) are inferred and checked against the data. Multiple realizations of porosity can then be constructed conditionally to the impedance information in the interwell region, which allow identifying one low-porosity structure and two to three flow units that connect the two wells, mapping heterogeneities within these units and visually assessing fluid paths in the aquifer. In particular, the results suggest that the paths in the lower flow units, formed by a network of heterogeneous conduits, are not as smooth as in the upper flow unit.

Wind turbine rotor blade monitoring using digital image correlation: a comparison to aeroelastic simulations of a multi-megawatt wind turbine

NASA Astrophysics Data System (ADS)

Winstroth, J.; Schoen, L.; Ernst, B.; Seume, J. R.

2014-06-01

Optical full-field measurement methods such as Digital Image Correlation (DIC) provide a new opportunity for measuring deformations and vibrations with high spatial and temporal resolution. However, application to full-scale wind turbines is not trivial. Elaborate preparation of the experiment is vital and sophisticated post processing of the DIC results essential. In the present study, a rotor blade of a 3.2 MW wind turbine is equipped with a random black-and-white dot pattern at four different radial positions. Two cameras are located in front of the wind turbine and the response of the rotor blade is monitored using DIC for different turbine operations. In addition, a Light Detection and Ranging (LiDAR) system is used in order to measure the wind conditions. Wind fields are created based on the LiDAR measurements and used to perform aeroelastic simulations of the wind turbine by means of advanced multibody codes. The results from the optical DIC system appear plausible when checked against common and expected results. In addition, the comparison of relative out-ofplane blade deflections shows good agreement between DIC results and aeroelastic simulations.

Simulation of foulant bioparticle topography based on Gaussian process and its implications for interface behavior research

NASA Astrophysics Data System (ADS)

Zhao, Leihong; Qu, Xiaolu; Lin, Hongjun; Yu, Genying; Liao, Bao-Qiang

2018-03-01

Simulation of randomly rough bioparticle surface is crucial to better understand and control interface behaviors and membrane fouling. Pursuing literature indicated a lack of effective method for simulating random rough bioparticle surface. In this study, a new method which combines Gaussian distribution, Fourier transform, spectrum method and coordinate transformation was proposed to simulate surface topography of foulant bioparticles in a membrane bioreactor (MBR). The natural surface of a foulant bioparticle was found to be irregular and randomly rough. The topography simulated by the new method was quite similar to that of real foulant bioparticles. Moreover, the simulated topography of foulant bioparticles was critically affected by parameters correlation length (l) and root mean square (σ). The new method proposed in this study shows notable superiority over the conventional methods for simulation of randomly rough foulant bioparticles. The ease, facility and fitness of the new method point towards potential applications in interface behaviors and membrane fouling research.

Direct construction of mesoscopic models from microscopic simulations

NASA Astrophysics Data System (ADS)

Lei, Huan; Caswell, Bruce; Karniadakis, George Em

2010-02-01

Starting from microscopic molecular-dynamics (MD) simulations of constrained Lennard-Jones (LJ) clusters (with constant radius of gyration Rg ), we construct two mesoscopic models [Langevin dynamics and dissipative particle dynamics (DPD)] by coarse graining the LJ clusters into single particles. Both static and dynamic properties of the coarse-grained models are investigated and compared with the MD results. The effective mean force field is computed as a function of the intercluster distance, and the corresponding potential scales linearly with the number of particles per cluster and the temperature. We verify that the mean force field can reproduce the equation of state of the atomistic systems within a wide density range but the radial distribution function only within the dilute and the semidilute regime. The friction force coefficients for both models are computed directly from the time-correlation function of the random force field of the microscopic system. For high density or a large cluster size the friction force is overestimated and the diffusivity underestimated due to the omission of many-body effects as a result of the assumed pairwise form of the coarse-grained force field. When the many-body effect is not as pronounced (e.g., smaller Rg or semidilute system), the DPD model can reproduce the dynamic properties of the MD system.

Numerical Study of g-Jitter Induced Double-Diffusive Convection

NASA Technical Reports Server (NTRS)

Shu, Y.; Li, B. Q.; deGroh, Henry C.

2001-01-01

A finite element study is presented of double-diffusive convection driven by g-jitter in a microgravity environment. Mathematical formulations are presented and extensive simulations are carried out for g-jitter induced fluid flow, temperature distribution, and solutal transport in an alloy system under consideration for space flights. Computations include the use of idealized single-frequency and multi-frequency g-jitter as well as the real g-jitter data taken during an actual Space Shuttle fight. Little correlation is seen between these velocity components for the g-jitter components studied. The temperature field is basically undisturbed by convection because of a small Pr number for the fluid. The disturbance of the concentration field, however, is pronounced, and the local variation of the concentration follows the velocity oscillation in time. It is found that although the concentration field varies in both position and time, the local concentration gradient remains approximately constant in time. Numerical study further indicates that with an increase in g-jitter force (or amplitude), the nonlinear convective effects become much more obvious, which in turn drastically change the concentration fields. The simulated results computed using the g-jitter data taken during space flights show that both the velocity and concentration become random, following approximately the same pattern as the g-jitter perturbations.

A study of the influence of conductive paths and their directions in randomly generated conductor network.

NASA Astrophysics Data System (ADS)

Mandolesi, E.; Moorkamp, M.; Jones, A. G.

2014-12-01

Most electromagnetic (EM) geophysical methods focus on the electrical conductivity of rocks and sediments to determine the geological structure of the subsurface. Electric conductivity itself is measured in the laboratory with a wide range of instruments and techniques. These measurements seldom return a compatible result. The presence of partially-interconnected random pathways of electrically conductive materials in resistive hosts has been studied for decades, and recently with increasing interest. To comprehend which conductive mechanism scales from the microstructures up to field electrical conductivity measurements, two main branch of studies have been undertaken: statistical probability of having a conductive pathways and mixing laws. Several numerical approaches have been tested to understand the effects of interconnected pathways of conductors at field scale. Usually these studies were restricted in two ways: the sources are considered constant in time (i.e., DC) and the domain is, with few exception, two-dimensional. We simulated the effects of time-varying EM sources on the conductivity measured on the surface of a three-dimensional randomly generated body embedded in an uniform host by using electromagnetic induction equations. We modelled a two-phase mixture of resistive and conductive elements with the goal of comparing the conductivity measured on field scale with the one proper of the elements constituting the random rock, and to test how the internal structures influence the directionality of the responses. Moreover, we modelled data from randomly generated bodies characterized by coherent internal structures, to check the effect of the named structures on the anisotropy of the effective conductivity. We compared these values with the electrical conductivity limits predicted by Hashin-Shtrikman bounds and the effective conductivity predicted by the Archie's law, both cast in its classic form and in an updated that allow to take in account two materials. The same analysis was done for both the resistive and the conductive conductivity values for the anisotropic case.

The Statistical Power of the Cluster Randomized Block Design with Matched Pairs--A Simulation Study

ERIC Educational Resources Information Center

Dong, Nianbo; Lipsey, Mark

2010-01-01

This study uses simulation techniques to examine the statistical power of the group- randomized design and the matched-pair (MP) randomized block design under various parameter combinations. Both nearest neighbor matching and random matching are used for the MP design. The power of each design for any parameter combination was calculated from…

Effect of angular momentum alignment and strong magnetic fields on the formation of protostellar discs

NASA Astrophysics Data System (ADS)

Gray, William J.; McKee, Christopher F.; Klein, Richard I.

2018-01-01

Star-forming molecular clouds are observed to be both highly magnetized and turbulent. Consequently, the formation of protostellar discs is largely dependent on the complex interaction between gravity, magnetic fields, and turbulence. Studies of non-turbulent protostellar disc formation with realistic magnetic fields have shown that these fields are efficient in removing angular momentum from the forming discs, preventing their formation. However, once turbulence is included, discs can form in even highly magnetized clouds, although the precise mechanism remains uncertain. Here, we present several high-resolution simulations of turbulent, realistically magnetized, high-mass molecular clouds with both aligned and random turbulence to study the role that turbulence, misalignment, and magnetic fields have on the formation of protostellar discs. We find that when the turbulence is artificially aligned so that the angular momentum is parallel to the initial uniform field, no rotationally supported discs are formed, regardless of the initial turbulent energy. We conclude that turbulence and the associated misalignment between the angular momentum and the magnetic field are crucial in the formation of protostellar discs in the presence of realistic magnetic fields.

Large-scale modeling of rain fields from a rain cell deterministic model

NASA Astrophysics Data System (ADS)

FéRal, Laurent; Sauvageot, Henri; Castanet, Laurent; Lemorton, JoëL.; Cornet, FréDéRic; Leconte, Katia

2006-04-01

A methodology to simulate two-dimensional rain rate fields at large scale (1000 × 1000 km2, the scale of a satellite telecommunication beam or a terrestrial fixed broadband wireless access network) is proposed. It relies on a rain rate field cellular decomposition. At small scale (˜20 × 20 km2), the rain field is split up into its macroscopic components, the rain cells, described by the Hybrid Cell (HYCELL) cellular model. At midscale (˜150 × 150 km2), the rain field results from the conglomeration of rain cells modeled by HYCELL. To account for the rain cell spatial distribution at midscale, the latter is modeled by a doubly aggregative isotropic random walk, the optimal parameterization of which is derived from radar observations at midscale. The extension of the simulation area from the midscale to the large scale (1000 × 1000 km2) requires the modeling of the weather frontal area. The latter is first modeled by a Gaussian field with anisotropic covariance function. The Gaussian field is then turned into a binary field, giving the large-scale locations over which it is raining. This transformation requires the definition of the rain occupation rate over large-scale areas. Its probability distribution is determined from observations by the French operational radar network ARAMIS. The coupling with the rain field modeling at midscale is immediate whenever the large-scale field is split up into midscale subareas. The rain field thus generated accounts for the local CDF at each point, defining a structure spatially correlated at small scale, midscale, and large scale. It is then suggested that this approach be used by system designers to evaluate diversity gain, terrestrial path attenuation, or slant path attenuation for different azimuth and elevation angle directions.

Probabilistic models for reactive behaviour in heterogeneous condensed phase media

NASA Astrophysics Data System (ADS)

Baer, M. R.; Gartling, D. K.; DesJardin, P. E.

2012-02-01

This work presents statistically-based models to describe reactive behaviour in heterogeneous energetic materials. Mesoscale effects are incorporated in continuum-level reactive flow descriptions using probability density functions (pdfs) that are associated with thermodynamic and mechanical states. A generalised approach is presented that includes multimaterial behaviour by treating the volume fraction as a random kinematic variable. Model simplifications are then sought to reduce the complexity of the description without compromising the statistical approach. Reactive behaviour is first considered for non-deformable media having a random temperature field as an initial state. A pdf transport relationship is derived and an approximate moment approach is incorporated in finite element analysis to model an example application whereby a heated fragment impacts a reactive heterogeneous material which leads to a delayed cook-off event. Modelling is then extended to include deformation effects associated with shock loading of a heterogeneous medium whereby random variables of strain, strain-rate and temperature are considered. A demonstrative mesoscale simulation of a non-ideal explosive is discussed that illustrates the joint statistical nature of the strain and temperature fields during shock loading to motivate the probabilistic approach. This modelling is derived in a Lagrangian framework that can be incorporated in continuum-level shock physics analysis. Future work will consider particle-based methods for a numerical implementation of this modelling approach.

Functional response and capture timing in an individual-based model: predation by northern squawfish (Ptychocheilus oregonensis) on juvenile salmonids in the Columbia River

USGS Publications Warehouse

Petersen, James H.; DeAngelis, Donald L.

1992-01-01

The behavior of individual northern squawfish (Ptychocheilus oregonensis) preying on juvenile salmonids was modeled to address questions about capture rate and the timing of prey captures (random versus contagious). Prey density, predator weight, prey weight, temperature, and diel feeding pattern were first incorporated into predation equations analogous to Holling Type 2 and Type 3 functional response models. Type 2 and Type 3 equations fit field data from the Columbia River equally well, and both models predicted predation rates on five of seven independent dates. Selecting a functional response type may be complicated by variable predation rates, analytical methods, and assumptions of the model equations. Using the Type 2 functional response, random versus contagious timing of prey capture was tested using two related models. ln the simpler model, salmon captures were assumed to be controlled by a Poisson renewal process; in the second model, several salmon captures were assumed to occur during brief "feeding bouts", modeled with a compound Poisson process. Salmon captures by individual northern squawfish were clustered through time, rather than random, based on comparison of model simulations and field data. The contagious-feeding result suggests that salmonids may be encountered as patches or schools in the river.

Use of simulated data sets to evaluate the fidelity of metagenomic processing methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavromatis, K; Ivanova, N; Barry, Kerrie

2007-01-01

Metagenomics is a rapidly emerging field of research for studying microbial communities. To evaluate methods presently used to process metagenomic sequences, we constructed three simulated data sets of varying complexity by combining sequencing reads randomly selected from 113 isolate genomes. These data sets were designed to model real metagenomes in terms of complexity and phylogenetic composition. We assembled sampled reads using three commonly used genome assemblers (Phrap, Arachne and JAZZ), and predicted genes using two popular gene-finding pipelines (fgenesb and CRITICA/GLIMMER). The phylogenetic origins of the assembled contigs were predicted using one sequence similarity-based ( blast hit distribution) and twomore » sequence composition-based (PhyloPythia, oligonucleotide frequencies) binning methods. We explored the effects of the simulated community structure and method combinations on the fidelity of each processing step by comparison to the corresponding isolate genomes. The simulated data sets are available online to facilitate standardized benchmarking of tools for metagenomic analysis.« less

Use of simulated data sets to evaluate the fidelity of Metagenomicprocessing methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavromatis, Konstantinos; Ivanova, Natalia; Barry, Kerri

2006-12-01

Metagenomics is a rapidly emerging field of research for studying microbial communities. To evaluate methods presently used to process metagenomic sequences, we constructed three simulated data sets of varying complexity by combining sequencing reads randomly selected from 113 isolate genomes. These data sets were designed to model real metagenomes in terms of complexity and phylogenetic composition. We assembled sampled reads using three commonly used genome assemblers (Phrap, Arachne and JAZZ), and predicted genes using two popular gene finding pipelines (fgenesb and CRITICA/GLIMMER). The phylogenetic origins of the assembled contigs were predicted using one sequence similarity--based (blast hit distribution) and twomore » sequence composition--based (PhyloPythia, oligonucleotide frequencies) binning methods. We explored the effects of the simulated community structure and method combinations on the fidelity of each processing step by comparison to the corresponding isolate genomes. The simulated data sets are available online to facilitate standardized benchmarking of tools for metagenomic analysis.« less

FDTD simulations of localization and enhancements on fractal plasmonics nanostructures.

PubMed

Buil, Stéphanie; Laverdant, Julien; Berini, Bruno; Maso, Pierre; Hermier, Jean-Pierre; Quélin, Xavier

2012-05-21

A parallelized 3D FDTD (Finite-Difference Time-Domain) solver has been used to study the near-field electromagnetic intensity upon plasmonics nanostructures. The studied structures are obtained from AFM (Atomic Force Microscopy) topography measured on real disordered gold layers deposited by thermal evaporation under ultra-high vacuum. The simulation results obtained with these 3D metallic nanostructures are in good agreement with previous experimental results: the localization of the electromagnetic intensity in subwavelength areas ("hot spots") is demonstrated; the spectral and polarization dependences of the position of these "hot spots" are also satisfactory; the enhancement factors obtained are realistic compared to the experimental ones. These results could be useful to further our understanding of the electromagnetic behavior of random metal layers.

Switching Phenomena

NASA Astrophysics Data System (ADS)

Stanley, H. E.; Buldyrev, S. V.; Franzese, G.; Havlin, S.; Mallamace, F.; Mazza, M. G.; Kumar, P.; Plerou, V.; Preis, T.; Stokely, K.; Xu, L.

One challenge of biology, medicine, and economics is that the systems treated by these serious scientific disciplines can suddenly "switch" from one behavior to another, even though they possess no perfect metronome in time. As if by magic, out of nothing but randomness one finds remarkably fine-tuned processes in time. The past century has, philosophically, been concerned with placing aside the human tendency to see the universe as a fine-tuned machine. Here we will address the challenge of uncovering how, through randomness (albeit, as we shall see, strongly correlated randomness), one can arrive at some of the many temporal patterns in physics, economics, and medicine and even begin to characterize the switching phenomena that enable a system to pass from one state to another. We discuss some applications of correlated randomness to understanding switching phenomena in various fields. Specifically, we present evidence from experiments and from computer simulations supporting the hypothesis that water's anomalies are related to a switching point (which is not unlike the "tipping point" immortalized by Malcolm Gladwell), and that the bubbles in economic phenomena that occur on all scales are not "outliers" (another Gladwell immortalization).

Statistics of backscatter radar return from vegetation

NASA Technical Reports Server (NTRS)

Karam, M. A.; Chen, K. S.; Fung, A. K.

1992-01-01

The statistical characteristics of radar return from vegetation targets are investigated through a simulation study based upon the first-order scattered field. For simulation purposes, the vegetation targets are modeled as a layer of randomly oriented and spaced finite cylinders, needles, or discs, or a combination of them. The finite cylinder is used to represent a branch or a trunk, the needle for a stem or a coniferous leaf, and the disc for a decidous leaf. For a plane wave illuminating a vegetation canopy, simulation results show that the signal returned from a layer of disc- or needle-shaped leaves follows the Gamma distribution, and that the signal returned from a layer of branches resembles the log normal distribution. The Gamma distribution also represents the signal returned from a layer of a mixture of branches and leaves regardless of the leaf shapes. Results also indicate that the polarization state does not have a significant impact on signal distribution.

PLASMA TURBULENCE AND KINETIC INSTABILITIES AT ION SCALES IN THE EXPANDING SOLAR WIND

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hellinger, Petr; Trávnícek, Pavel M.; Matteini, Lorenzo

The relationship between a decaying strong turbulence and kinetic instabilities in a slowly expanding plasma is investigated using two-dimensional (2D) hybrid expanding box simulations. We impose an initial ambient magnetic field perpendicular to the simulation box, and we start with a spectrum of large-scale, linearly polarized, random-phase Alfvénic fluctuations that have energy equipartition between kinetic and magnetic fluctuations and vanishing correlation between the two fields. A turbulent cascade rapidly develops; magnetic field fluctuations exhibit a power-law spectrum at large scales and a steeper spectrum at ion scales. The turbulent cascade leads to an overall anisotropic proton heating, protons are heatedmore » in the perpendicular direction, and, initially, also in the parallel direction. The imposed expansion leads to generation of a large parallel proton temperature anisotropy which is at later stages partly reduced by turbulence. The turbulent heating is not sufficient to overcome the expansion-driven perpendicular cooling and the system eventually drives the oblique firehose instability in a form of localized nonlinear wave packets which efficiently reduce the parallel temperature anisotropy. This work demonstrates that kinetic instabilities may coexist with strong plasma turbulence even in a constrained 2D regime.« less

Effect of Aperture Field Variability, Flow Rate, and Ionic Strength on Colloid Transport in Single Fractures: Laboratory-Scale Experiments and Numerical Simulation

NASA Astrophysics Data System (ADS)

Zheng, Q.; Dickson, S.; Guo, Y.

2007-12-01

A good understanding of the physico-chemical processes (i.e., advection, dispersion, attachment/detachment, straining, sedimentation etc.) governing colloid transport in fractured media is imperative in order to develop appropriate bioremediation and/or bioaugmentation strategies for contaminated fractured aquifers, form management plans for groundwater resources to prevent pathogen contamination, and identify suitable radioactive waste disposal sites. However, research in this field is still in its infancy due to the complex heterogeneous nature of fractured media and the resulting difficulty in characterizing this media. The goal of this research is to investigate the effects of aperture field variability, flow rate and ionic strength on colloid transport processes in well characterized single fractures. A combination of laboratory-scale experiments, numerical simulations, and imaging techniques were employed to achieve this goal. Transparent replicas were cast from natural rock fractures, and a light transmission technique was employed to measure their aperture fields directly. The surface properties of the synthetic fractures were characterized by measuring the zeta-potential under different ionic strengths. A 33 (3 increased to the power of 3) factorial experiment was implemented to investigate the influence of aperture field variability, flow rate, and ionic strength on different colloid transport processes in the laboratory-scale fractures, specifically dispersion and attachment/detachment. A fluorescent stain technique was employed to photograph the colloid transport processes, and an analytical solution to the one-dimensional transport equation was fit to the colloid breakthrough curves to calculate the average transport velocity, dispersion coefficient, and attachment/detachment coefficient. The Reynolds equation was solved to obtain the flow field in the measured aperture fields, and the random walk particle tracking technique was employed to model the colloid transport experiments. The images clearly show the development of preferential pathways for colloid transport in the different aperture fields and under different flow conditions. Additionally, a correlation between colloid deposition and fracture wall topography was identified. This presentation will demonstrate (1) differential transport between colloid and solute in single fractures, and the relationship between differential transport and aperture field statistics; (2) the relationship between the colloid dispersion coefficient and aperture field statistics; and (3) the relationship between attachment/detachment, aperture field statistics, fracture wall topography, flow rate, and ionic strength. In addition, this presentation will provide insight into the application of the random walk particle tracking technique for modeling colloid transport in variable-aperture fractures.

Driving reconnection in sheared magnetic configurations with forced fluctuations

NASA Astrophysics Data System (ADS)

Pongkitiwanichakul, Peera; Makwana, Kirit D.; Ruffolo, David

2018-02-01

We investigate reconnection of magnetic field lines in sheared magnetic field configurations due to fluctuations driven by random forcing by means of numerical simulations. The simulations are performed with an incompressible, pseudo-spectral magnetohydrodynamics code in 2D where we take thick, resistively decaying, current-sheet like sheared magnetic configurations which do not reconnect spontaneously. We describe and test the forcing that is introduced in the momentum equation to drive fluctuations. It is found that the forcing does not change the rate of decay; however, it adds and removes energy faster in the presence of the magnetic shear structure compared to when it has decayed away. We observe that such a forcing can induce magnetic reconnection due to field line wandering leading to the formation of magnetic islands and O-points. These reconnecting field lines spread out as the current sheet decays with time. A semi-empirical formula is derived which reasonably explains the formation and spread of O-points. We find that reconnection spreads faster with stronger forcing and longer correlation time of forcing, while the wavenumber of forcing does not have a significant effect. When the field line wandering becomes large enough, the neighboring current sheets with opposite polarity start interacting, and then the magnetic field is rapidly annihilated. This work is useful to understand how forced fluctuations can drive reconnection in large scale current structures in space and astrophysical plasmas that are not susceptible to reconnection.

Microwave remote sensing and radar polarization signatures of natural fields

NASA Technical Reports Server (NTRS)

Mo, Tsan

1989-01-01

Theoretical models developed for simulation of microwave remote sensing of the Earth surface from airborne/spaceborne sensors are described. Theoretical model calculations were performed and the results were compared with data of field measurements. Data studied included polarimetric images at the frequencies of P band, L band, and C band, acquired with airborne polarimeters over a agricultural field test site. Radar polarization signatures from bare soil surfaces and from tree covered fields were obtained from the data. The models developed in this report include: (1) Small perturbation model of wave scatterings from randomly rough surfaces, (2) Physical optics model, (3) Geometrical optics model, and (4) Electromagnetic wave scattering from dielectric cylinders of finite lengths, which replace the trees and branches in the modeling of tree covered field. Additionally, a three-layer emissivity model for passive sensing of a vegetation covered soil surface is also developed. The effects of surface roughness, soil moisture contents, and tree parameters on the polarization signatures were investigated.

On the upstream boundary of electron foreshocks in the solar wind

NASA Technical Reports Server (NTRS)

Zimbardo, G.; Veltri, P.

1995-01-01

The upstream boundary of electron foreshocks is defined as the path of the fastest electrons reflected by collisionless shocks and moving along the magnetic field in the solar wind. Considerable levels of magnetic fluctuations are found in these regions of the solar wind, and their effect is to create both a broadening and a fine structure of the electron foreshock boundary. The magnetic structure is studied by means of a 3-D numerical simulation of a turbulent magnetic field. Enhanced, anomalous diffusion is found, (Delta x(exp 2)) varies as s(sup alpha), where alpha is greater than 1 for typical values of the parameters (here, Delta x(exp 2) is the mean square width of the tangent magnetic surface and s is the field line length). This corresponds to a Levy flight regime for the magnetic field line random walk, and allows very efficient electron propagation perpendicular to the magnetic field. Implications on the observations of planetary foreshocks and of the termination shock foreshock are considered.

Effect of spin transfer torque on domain wall motion regimes in [Co/Ni] superlattice wires

NASA Astrophysics Data System (ADS)

Le Gall, S.; Vernier, N.; Montaigne, F.; Thiaville, A.; Sampaio, J.; Ravelosona, D.; Mangin, S.; Andrieu, S.; Hauet, T.

2017-05-01

The combined effect of magnetic field and current on domain wall motion is investigated in epitaxial [Co/Ni] microwires. Both thermally activated and flow regimes are found to be strongly affected by current. All experimental data can be understood by taking into account both adiabatic and nonadiabatic components of the spin transfer torque, the parameters of which are extracted. In the precessional flow regime, it is shown that the domain wall can move in the electron flow direction against a strong applied field, as previously observed. In addition, for a large range of applied magnetic field and injected current, a stochastic domain wall displacement after each pulse is observed. Two-dimensional micromagnetic simulations, including some disorder, show a random fluctuation of the domain wall position that qualitatively matches the experimental results.

Free-energy landscape of the villin headpiece in an all-atom force field.

PubMed

Herges, Thomas; Wenzel, Wolfgang

2005-04-01

We investigate the landscape of the internal free-energy of the 36 amino acid villin headpiece with a modified basin hopping method in the all-atom force field PFF01, which was previously used to predictively fold several helical proteins with atomic resolution. We identify near native conformations of the protein as the global optimum of the force field. More than half of the twenty best simulations started from random initial conditions converge to the folding funnel of the native conformation, but several competing low-energy metastable conformations were observed. From 76,000 independently generated conformations we derived a decoy tree which illustrates the topological structure of the entire low-energy part of the free-energy landscape and characterizes the ensemble of metastable conformations. These emerge as similar in secondary content, but differ in tertiary arrangement.

Correcting Biases in a lower resolution global circulation model with data assimilation

NASA Astrophysics Data System (ADS)

Canter, Martin; Barth, Alexander

2016-04-01

With this work, we aim at developping a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias. First, through a preliminary run, we estimate the bias of the model and its possible sources. Then, we establish a forcing term which is directly added inside the model's equations. We create an ensemble of runs and consider the forcing term as a control variable during the assimilation of observations. We then use this analysed forcing term to correct the bias of the model. Since the forcing is added inside the model, it acts as a source term, unlike external forcings such as wind. This procedure has been developed and successfully tested with a twin experiment on a Lorenz 95 model. It is currently being applied and tested on the sea ice ocean NEMO LIM model, which is used in the PredAntar project. NEMO LIM is a global and low resolution (2 degrees) coupled model (hydrodynamic model and sea ice model) with long time steps allowing simulations over several decades. Due to its low resolution, the model is subject to bias in area where strong currents are present. We aim at correcting this bias by using perturbed current fields from higher resolution models and randomly generated perturbations. The random perturbations need to be constrained in order to respect the physical properties of the ocean, and not create unwanted phenomena. To construct those random perturbations, we first create a random field with the Diva tool (Data-Interpolating Variational Analysis). Using a cost function, this tool penalizes abrupt variations in the field, while using a custom correlation length. It also decouples disconnected areas based on topography. Then, we filter the field to smoothen it and remove small scale variations. We use this field as a random stream function, and take its derivatives to get zonal and meridional velocity fields. We also constrain the stream function along the coasts in order not to have currents perpendicular to the coast. The randomly generated stochastic forcing are then directly injected into the NEMO LIM model's equations in order to force the model at each timestep, and not only during the assimilation step. Results from a twin experiment will be presented. This method is being applied to a real case, with observations on the sea surface height available from the mean dynamic topography of CNES (Centre national d'études spatiales). The model, the bias correction, and more extensive forcings, in particular with a three dimensional structure and a time-varying component, will also be presented.

Simulation of the geomagnetic field experienced by the International Space Station in its revolution around the Earth: Effects on psychophysiological responses to affective picture viewing

NASA Astrophysics Data System (ADS)

Del Seppia, C.; Mezzasalma, L.; Messerotti, M.; Cordelli, A.; Ghione, S.

2006-02-01

There is evidence suggesting that exposure to an abnormal magnetic environment may produce psychophysiological effects related to abnormalities in responses to stress. This may be of relevance for space medicine where astronauts are exposed to a magnetic field different from that exerted by the Earth. Aim of this study was to assess how the exposure of the head to a magnetic field simulating the one encountered by the International Space Station (ISS) during a single orbit (90 min) around the Earth affects the cardiovascular and psychophysiological parameters. Twenty-four human volunteers were studied double blindly in random order under sham and magnetic exposure. During exposure, the persons were shown a set of pictures of different emotional content while subjective self-rating, skin conductance (SC), blood pressure (BP), and heart rate (HR) were measured. In addition, BP, HR, and tooth pain threshold were assessed before and after exposure. While subjects were under magnetic exposure, skin conductance was strongly differentiated (F|2,36 = 22.927; p = 0.0001), being high during emotionally involving (positive and negative) pictures and low during neutral pictures. Conversely, when subjects were under sham exposure, no significant differences were observed. There was, however, a trend for higher heart rate during picture viewing under magnetic exposure as compared to sham exposure. No effects were found for the other variables. These results suggest that an abnormal magnetic field that simulates the one encountered by ISS orbiting around the Earth may enhance autonomic response to emotional stimuli.

Simulations of Lateral Transport and Dropout Structure of Energetic Particles from Impulsive Solar Flares

NASA Astrophysics Data System (ADS)

Tooprakai, P.; Seripienlert, A.; Ruffolo, D.; Chuychai, P.; Matthaeus, W. H.

2016-11-01

We simulate trajectories of energetic particles from impulsive solar flares for 2D+slab models of magnetic turbulence in spherical geometry to study dropout features, I.e., sharp, repeated changes in the particle density. Among random-phase realizations of two-dimensional (2D) turbulence, a spherical harmonic expansion can generate homogeneous turbulence over a sphere, but a 2D fast Fourier transform (FFT) locally mapped onto the lateral coordinates in the region of interest is much faster computationally, and we show that the results are qualitatively similar. We then use the 2D FFT field as input to a 2D MHD simulation, which dynamically generates realistic features of turbulence such as coherent structures. The magnetic field lines and particles spread non-diffusively (ballistically) to a patchy distribution reaching up to 25° from the injection longitude and latitude at r ˜ 1 au. This dropout pattern in field line trajectories has sharper features in the case of the more realistic 2D MHD model, in better qualitative agreement with observations. The initial dropout pattern in particle trajectories is relatively insensitive to particle energy, though the energy affects the pattern’s evolution with time. We make predictions for future observations of solar particles near the Sun (e.g., at 0.25 au), for which we expect a sharp pulse of outgoing particles along the dropout pattern, followed by backscattering that first remains close to the dropout pattern and later exhibits cross-field transport to a distribution that is more diffusive, yet mostly contained within the dropout pattern found at greater distances.

Tensor of effective susceptibility in random magnetic composites: Application to two-dimensional and three-dimensional cases

NASA Astrophysics Data System (ADS)

Posnansky, Oleg P.

2018-05-01

The measuring of dynamic magnetic susceptibility by nuclear magnetic resonance is used for revealing information about the internal structure of various magnetoactive composites. The response of such material on the applied external static and time-varying magnetic fields encodes intrinsic dynamic correlations and depends on links between macroscopic effective susceptibility and structure on the microscopic scale. In the current work we carried out computational analysis of the frequency dependent dynamic magnetic susceptibility and demonstrated its dependence on the microscopic architectural elements while also considering Euclidean dimensionality. The proposed numerical method is efficient in the simulation of nuclear magnetic resonance experiments in two- and three-dimensional random magnetic media by choosing and modeling the influence of the concentration of components and internal hierarchical characteristics of physical parameters.

Metasurfaced Reverberation Chamber.

PubMed

Sun, Hengyi; Li, Zhuo; Gu, Changqing; Xu, Qian; Chen, Xinlei; Sun, Yunhe; Lu, Shengchen; Martin, Ferran

2018-01-25

The concept of metasurfaced reverberation chamber (RC) is introduced in this paper. It is shown that by coating the chamber wall with a rotating 1-bit random coding metasurface, it is possible to enlarge the test zone of the RC while maintaining the field uniformity as good as that in a traditional RC with mechanical stirrers. A 1-bit random coding diffusion metasurface is designed to obtain all-direction backscattering under normal incidence. Three specific cases are studied for comparisons, including a (traditional) mechanical stirrer RC, a mechanical stirrer RC with a fixed diffusion metasurface, and a RC with a rotating diffusion metasurface. Simulation results show that the compact rotating diffusion metasurface can act as a stirrer with good stirring efficiency. By using such rotating diffusion metasurface, the test region of the RC can be greatly extended.

High-density magnetoresistive random access memory operating at ultralow voltage at room temperature.

PubMed

Hu, Jia-Mian; Li, Zheng; Chen, Long-Qing; Nan, Ce-Wen

2011-11-22

The main bottlenecks limiting the practical applications of current magnetoresistive random access memory (MRAM) technology are its low storage density and high writing energy consumption. Although a number of proposals have been reported for voltage-controlled memory device in recent years, none of them simultaneously satisfy the important device attributes: high storage capacity, low power consumption and room temperature operation. Here we present, using phase-field simulations, a simple and new pathway towards high-performance MRAMs that display significant improvements over existing MRAM technologies or proposed concepts. The proposed nanoscale MRAM device simultaneously exhibits ultrahigh storage capacity of up to 88 Gb inch(-2), ultralow power dissipation as low as 0.16 fJ per bit and room temperature high-speed operation below 10 ns.

High-density magnetoresistive random access memory operating at ultralow voltage at room temperature

PubMed Central

Hu, Jia-Mian; Li, Zheng; Chen, Long-Qing; Nan, Ce-Wen

2011-01-01

The main bottlenecks limiting the practical applications of current magnetoresistive random access memory (MRAM) technology are its low storage density and high writing energy consumption. Although a number of proposals have been reported for voltage-controlled memory device in recent years, none of them simultaneously satisfy the important device attributes: high storage capacity, low power consumption and room temperature operation. Here we present, using phase-field simulations, a simple and new pathway towards high-performance MRAMs that display significant improvements over existing MRAM technologies or proposed concepts. The proposed nanoscale MRAM device simultaneously exhibits ultrahigh storage capacity of up to 88 Gb inch−2, ultralow power dissipation as low as 0.16 fJ per bit and room temperature high-speed operation below 10 ns. PMID:22109527

Generating log-normal mock catalog of galaxies in redshift space

NASA Astrophysics Data System (ADS)

Agrawal, Aniket; Makiya, Ryu; Chiang, Chi-Ting; Jeong, Donghui; Saito, Shun; Komatsu, Eiichiro

2017-10-01

We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear bias relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.

New description of charged particle propagation in random magnetic fields

NASA Technical Reports Server (NTRS)

Earl, James A.

1994-01-01

When charged particles spiral along a large constant magnetic field, their trajectories are scattered by random components that are superposed on the guiding field. In the simplest analysis of this situation, scattering causes the particles to diffuse parallel to the guiding field. At the next level of approximation, moving pulses that correspond to a coherent mode of propagation are present, but they are represented by delta-functions whose infinitely narrow width makes no sense physically and is inconsistent with the finite duration of coherent pulses observed in solar energetic particle events. To derive a more realistic description, the transport problem is formulated in terms of 4 x 4 matrices, which derive from a representation of the particle distribution function in terms of eigenfunctions of the scattering operator, and which lead to useful approximations that give explicit predictions of the detailed evolution not only of the coherent pulses, but also of the diffusive wake. More specifically, the new description embodies a simple convolution of a narrow Gaussian with the solutions above that involve delta-functions, but with a slightly reduced coherent velocity. The validity of these approximations, which can easily be calculated on a desktop computer, has been exhaustively confirmed by comparison with results of Monte Carlo simulations which kept track of 50 million particles and which were carried out on the Maspar computer at Goddard Space Flight Center.

Metabolic changes in four beat gaited horses after field marcha simulation.

PubMed

Wanderley, E K; Manso Filho, H C; Manso, H E C C C; Santiago, T A; McKeever, K H

2010-11-01

Mangalarga-Marchador is a popular 4-gaited Brazilian horse breed; however, there is little information about their metabolic and physiological response to exercise. To measure physiological and metabolic responses of the Mangalarga-Marchador to a simulated marcha field test and to compare these responses between 2 types of marcha gaits (picada and batida). Thirteen horses were used in the study and randomly assigned to either the picada or batida gait for the simulated marcha field test (speed ∼ 3.2 m/s; 30 min; load ∼ 80 kg). Included body composition, heart rate (HR), respiratory rate (RR), glucose (GLUC), lactate (LACT), packed cell volume (PCV), total plasma protein (TPP), albumin, urea, creatinine, total and HDL cholesterol, triglycerides, creatine kinase, alanine, glutamate and glutamine (GLN). Measurements were obtained pretest (control/fasting), immediately after simulation (T(0)), and 15 (T(15)), 30 (T(30)) and 240 (T(240)) min after the simulation. Lactate (LACT) was measured at T(0), T(15) and T(30). Data were analysed using ANOVA, Tukey's test and t tests with significance set at P < 0.05. Significant acute changes were observed in HR, RR, [GLUC], [LACT], [TPP], PCV and [GLN] (P<0.05) relative to control. Heart rate fell below 60 beats/min at T(15) and RR recovered to pretest values by T(240). Significant increases in [GLUC], [LACT], PCV and [TPP] and a decrease in [GLN] were observed at T(0). Treatment and interaction effects were also observed between marcha types and time of sampling for HR, RF, PCV, and [LACT] (P < 0.05). These parameters were large in picada. The simulation of field-test produced changes in some physiological and blood parameters in marcha horses, with some degree of dehydration during recovery period. Also, it was demonstrated that picada horses spend more energy when compared with batida horses at the the same speed. Batida horses spend less energy when compared with picada horses, which will need special attention in their training and nutritional management. © 2010 EVJ Ltd.

Effects of valerian on subjective sedation, field sobriety testing and driving simulator performance.

PubMed

Thomas, Kelan; Canedo, Joanne; Perry, Paul J; Doroudgar, Shadi; Lopes, Ingrid; Chuang, Hannah Mae; Bohnert, Kimberly

2016-07-01

The availability of herbal medicines over-the-counter (OTC) has increased the use of natural products for self-treatment. Valerian has been used to effectively treat generalized anxiety disorder and insomnia. Studies suggest that valerenic acid may increase gamma-aminobutyric acid (GABA) modulation in the brain. Benzodiazepines have a similar mechanism of action and have been linked to an increased risk of hospitalizations due to traffic accidents. Despite the risk of somnolence, the safety of driving while under the influence of valerian remains unknown. The purpose of the study was to determine the effects of a one-time valerian 1600mg dose on subjective sedation effects, standardized field sobriety testing (SFST) and driving simulator performance parameters. The study design was a randomized, placebo-controlled, double-blind, cross-over trial. For each session, participants received either a dose of valerian or placebo. The outcome measures included a simple visual reaction test (SVRT), subjective sleepiness scales, SFST performance scores, and driving simulator performance parameters. There were no significant differences in the SVRT or sleepiness scales between placebo and valerian exposures, but the study may have been underpowered. SFST total and individual test failure rates were not significantly different between the two exposures. The driving simulator performance parameters were equivalent between the two exposure conditions. A one-time valerian 1600mg dose, often used to treat insomnia, does not appear to impair driving simulator performance after acute ingestion. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predictive uncertainty analysis of a saltwater intrusion model using null-space Monte Carlo

USGS Publications Warehouse

Herckenrath, Daan; Langevin, Christian D.; Doherty, John

2011-01-01

Because of the extensive computational burden and perhaps a lack of awareness of existing methods, rigorous uncertainty analyses are rarely conducted for variable-density flow and transport models. For this reason, a recently developed null-space Monte Carlo (NSMC) method for quantifying prediction uncertainty was tested for a synthetic saltwater intrusion model patterned after the Henry problem. Saltwater intrusion caused by a reduction in fresh groundwater discharge was simulated for 1000 randomly generated hydraulic conductivity distributions, representing a mildly heterogeneous aquifer. From these 1000 simulations, the hydraulic conductivity distribution giving rise to the most extreme case of saltwater intrusion was selected and was assumed to represent the "true" system. Head and salinity values from this true model were then extracted and used as observations for subsequent model calibration. Random noise was added to the observations to approximate realistic field conditions. The NSMC method was used to calculate 1000 calibration-constrained parameter fields. If the dimensionality of the solution space was set appropriately, the estimated uncertainty range from the NSMC analysis encompassed the truth. Several variants of the method were implemented to investigate their effect on the efficiency of the NSMC method. Reducing the dimensionality of the null-space for the processing of the random parameter sets did not result in any significant gains in efficiency and compromised the ability of the NSMC method to encompass the true prediction value. The addition of intrapilot point heterogeneity to the NSMC process was also tested. According to a variogram comparison, this provided the same scale of heterogeneity that was used to generate the truth. However, incorporation of intrapilot point variability did not make a noticeable difference to the uncertainty of the prediction. With this higher level of heterogeneity, however, the computational burden of generating calibration-constrained parameter fields approximately doubled. Predictive uncertainty variance computed through the NSMC method was compared with that computed through linear analysis. The results were in good agreement, with the NSMC method estimate showing a slightly smaller range of prediction uncertainty than was calculated by the linear method. Copyright 2011 by the American Geophysical Union.

Sampling procedures for throughfall monitoring: A simulation study

NASA Astrophysics Data System (ADS)

Zimmermann, Beate; Zimmermann, Alexander; Lark, Richard Murray; Elsenbeer, Helmut

2010-01-01

What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events.

The importance of fluctuations in fluid mixing

PubMed Central

Kadau, Kai; Rosenblatt, Charles; Barber, John L.; Germann, Timothy C.; Huang, Zhibin; Carlès, Pierre; Alder, Berni J.

2007-01-01

A ubiquitous example of fluid mixing is the Rayleigh–Taylor instability, in which a heavy fluid initially sits atop a light fluid in a gravitational field. The subsequent development of the unstable interface between the two fluids is marked by several stages. At first, each interface mode grows exponentially with time before transitioning to a nonlinear regime characterized by more complex hydrodynamic mixing. Unfortunately, traditional continuum modeling of this process has generally been in poor agreement with experiment. Here, we indicate that the natural, random fluctuations of the flow field present in any fluid, which are neglected in continuum models, can lead to qualitatively and quantitatively better agreement with experiment. We performed billion-particle atomistic simulations and magnetic levitation experiments with unprecedented control of initial interface conditions. A comparison between our simulations and experiments reveals good agreement in terms of the growth rate of the mixing front as well as the new observation of droplet breakup at later times. These results improve our understanding of many fluid processes, including interface phenomena that occur, for example, in supernovae, the detachment of droplets from a faucet, and ink jet printing. Such instabilities are also relevant to the possible energy source of inertial confinement fusion, in which a millimeter-sized capsule is imploded to initiate nuclear fusion reactions between deuterium and tritium. Our results suggest that the applicability of continuum models would be greatly enhanced by explicitly including the effects of random fluctuations. PMID:17470811

Multiple Point Statistics algorithm based on direct sampling and multi-resolution images

NASA Astrophysics Data System (ADS)

Julien, S.; Renard, P.; Chugunova, T.

2017-12-01

Multiple Point Statistics (MPS) has become popular for more than one decade in Earth Sciences, because these methods allow to generate random fields reproducing highly complex spatial features given in a conceptual model, the training image, while classical geostatistics techniques based on bi-point statistics (covariance or variogram) fail to generate realistic models. Among MPS methods, the direct sampling consists in borrowing patterns from the training image to populate a simulation grid. This latter is sequentially filled by visiting each of these nodes in a random order, and then the patterns, whose the number of nodes is fixed, become narrower during the simulation process, as the simulation grid is more densely informed. Hence, large scale structures are caught in the beginning of the simulation and small scale ones in the end. However, MPS may mix spatial characteristics distinguishable at different scales in the training image, and then loose the spatial arrangement of different structures. To overcome this limitation, we propose to perform MPS simulation using a decomposition of the training image in a set of images at multiple resolutions. Applying a Gaussian kernel onto the training image (convolution) results in a lower resolution image, and iterating this process, a pyramid of images depicting fewer details at each level is built, as it can be done in image processing for example to lighten the space storage of a photography. The direct sampling is then employed to simulate the lowest resolution level, and then to simulate each level, up to the finest resolution, conditioned to the level one rank coarser. This scheme helps reproduce the spatial structures at any scale of the training image and then generate more realistic models. We illustrate the method with aerial photographies (satellite images) and natural textures. Indeed, these kinds of images often display typical structures at different scales and are well-suited for MPS simulation techniques.

Two spatial light modulator system for laboratory simulation of random beam propagation in random media.

PubMed

Wang, Fei; Toselli, Italo; Korotkova, Olga

2016-02-10

An optical system consisting of a laser source and two independent consecutive phase-only spatial light modulators (SLMs) is shown to accurately simulate a generated random beam (first SLM) after interaction with a stationary random medium (second SLM). To illustrate the range of possibilities, a recently introduced class of random optical frames is examined on propagation in free space and several weak turbulent channels with Kolmogorov and non-Kolmogorov statistics.

Random Walk Particle Tracking For Multiphase Heat Transfer

NASA Astrophysics Data System (ADS)

Lattanzi, Aaron; Yin, Xiaolong; Hrenya, Christine

2017-11-01

As computing capabilities have advanced, direct numerical simulation (DNS) has become a highly effective tool for quantitatively predicting the heat transfer within multiphase flows. Here we utilize a hybrid DNS framework that couples the lattice Boltzmann method (LBM) to the random walk particle tracking (RWPT) algorithm. The main challenge of such a hybrid is that discontinuous fields pose a significant challenge to the RWPT framework and special attention must be given to the handling of interfaces. We derive a method for addressing discontinuities in the diffusivity field, arising at the interface between two phases. Analytical means are utilized to develop an interfacial tracer balance and modify the RWPT algorithm. By expanding the modulus of the stochastic (diffusive) step and only allowing a subset of the tracers within the high diffusivity medium to undergo a diffusive step, the correct equilibrium state can be restored (globally homogeneous tracer distribution). The new RWPT algorithm is implemented within the SUSP3D code and verified against a variety of systems: effective diffusivity of a static gas-solids mixture, hot sphere in unbounded diffusion, cooling sphere in unbounded diffusion, and uniform flow past a hot sphere.

Random gauge models of the superconductor-insulator transition in two-dimensional disordered superconductors

NASA Astrophysics Data System (ADS)

Granato, Enzo

2017-11-01

We study numerically the superconductor-insulator transition in two-dimensional inhomogeneous superconductors with gauge disorder, described by four different quantum rotor models: a gauge glass, a flux glass, a binary phase glass, and a Gaussian phase glass. The first two models describe the combined effect of geometrical disorder in the array of local superconducting islands and a uniform external magnetic field, while the last two describe the effects of random negative Josephson-junction couplings or π junctions. Monte Carlo simulations in the path-integral representation of the models are used to determine the critical exponents and the universal conductivity at the quantum phase transition. The gauge- and flux-glass models display the same critical behavior, within the estimated numerical uncertainties. Similar agreement is found for the binary and Gaussian phase-glass models. Despite the different symmetries and disorder correlations, we find that the universal conductivity of these models is approximately the same. In particular, the ratio of this value to that of the pure model agrees with recent experiments on nanohole thin-film superconductors in a magnetic field, in the large disorder limit.

[The new magnetic therapy TAMMEF in the treatment of simple shoulder pain].

PubMed

Battisti, E; Bianciardi, L; Albanese, A; Piazza, E; Rigato, M; Galassi, G; Giordano, N

2007-01-01

Numerous studies have demonstrated the utility of extremely low frequencies (ELF) electromagnetic fields in the treatment of pain. Moreover, the effects of these fields seems to depend on their respective codes (frequency, intensity, waveform). In our study we want to assess the effects of the TAMMEF (Therapeutic Application of a Musically Modulated Electromagnetic Field) system, whose field is piloted by a musical signal and its parameters (frequency, intensity, waveform) are modified in time, randomly varying within the respective ranges, so that all possible codes can occur during a single application. Sixty subjects, affected by shoulder periarthritis were enrolled in the study and randomly divided into three groups of 20 patients each: A exposed to TAMMEF, B exposed to ELF, C exposed to a simulated field. All subjects underwent a cycle of 15 daily sessions of 30 minutes each and a clinical examination upon enrollment, after 7 days of therapy, at the end of the cycle and at a follow-up 30 days later. All the patients of groups A and B completed the therapy without the appearance of side effects: they presented a significant improvement of the subjective pain and the functional limitation, which remained stable at the follow-up examination. In group C, there was no improvement of the pain symptoms or articular functionality. This study suggests that the TAMMEF system is efficacious in the control of pain symptoms and in the reduction of functional limitation in patients with shoulder periarthritis. Moreover, the effects of the TAMMEF system cover those produced by the ELF field.

Channel doping concentration and cell program state dependence on random telegraph noise spatial and statistical distribution in 30 nm NAND flash memory

NASA Astrophysics Data System (ADS)

Tomita, Toshihiro; Miyaji, Kousuke

2015-04-01

The dependence of spatial and statistical distribution of random telegraph noise (RTN) in a 30 nm NAND flash memory on channel doping concentration NA and cell program state Vth is comprehensively investigated using three-dimensional Monte Carlo device simulation considering random dopant fluctuation (RDF). It is found that single trap RTN amplitude ΔVth is larger at the center of the channel region in the NAND flash memory, which is closer to the jellium (uniform) doping results since NA is relatively low to suppress junction leakage current. In addition, ΔVth peak at the center of the channel decreases in the higher Vth state due to the current concentration at the shallow trench isolation (STI) edges induced by the high vertical electrical field through the fringing capacitance between the channel and control gate. In such cases, ΔVth distribution slope λ cannot be determined by only considering RDF and single trap.

Distribution law of the Dirac eigenmodes in QCD

NASA Astrophysics Data System (ADS)

Catillo, Marco; Glozman, Leonid Ya.

2018-04-01

The near-zero modes of the Dirac operator are connected to spontaneous breaking of chiral symmetry in QCD (SBCS) via the Banks-Casher relation. At the same time, the distribution of the near-zero modes is well described by the Random Matrix Theory (RMT) with the Gaussian Unitary Ensemble (GUE). Then, it has become a standard lore that a randomness, as observed through distributions of the near-zero modes of the Dirac operator, is a consequence of SBCS. The higher-lying modes of the Dirac operator are not affected by SBCS and are sensitive to confinement physics and related SU(2)CS and SU(2NF) symmetries. We study the distribution of the near-zero and higher-lying eigenmodes of the overlap Dirac operator within NF = 2 dynamical simulations. We find that both the distributions of the near-zero and higher-lying modes are perfectly described by GUE of RMT. This means that randomness, while consistent with SBCS, is not a consequence of SBCS and is linked to the confining chromo-electric field.

Probability Distributions for Random Quantum Operations

NASA Astrophysics Data System (ADS)

Schultz, Kevin

Motivated by uncertainty quantification and inference of quantum information systems, in this work we draw connections between the notions of random quantum states and operations in quantum information with probability distributions commonly encountered in the field of orientation statistics. This approach identifies natural sample spaces and probability distributions upon these spaces that can be used in the analysis, simulation, and inference of quantum information systems. The theory of exponential families on Stiefel manifolds provides the appropriate generalization to the classical case. Furthermore, this viewpoint motivates a number of additional questions into the convex geometry of quantum operations relative to both the differential geometry of Stiefel manifolds as well as the information geometry of exponential families defined upon them. In particular, we draw on results from convex geometry to characterize which quantum operations can be represented as the average of a random quantum operation. This project was supported by the Intelligence Advanced Research Projects Activity via Department of Interior National Business Center Contract Number 2012-12050800010.

Stimulus-Dependent State Transition between Synchronized Oscillation and Randomly Repetitive Burst in a Model Cerebellar Granular Layer

PubMed Central

Tanaka, Shigeru; Nagao, Soichi; Nishino, Tetsuro

2011-01-01

Information processing of the cerebellar granular layer composed of granule and Golgi cells is regarded as an important first step toward the cerebellar computation. Our previous theoretical studies have shown that granule cells can exhibit random alternation between burst and silent modes, which provides a basis of population representation of the passage-of-time (POT) from the onset of external input stimuli. On the other hand, another computational study has reported that granule cells can exhibit synchronized oscillation of activity, as consistent with observed oscillation in local field potential recorded from the granular layer while animals keep still. Here we have a question of whether an identical network model can explain these distinct dynamics. In the present study, we carried out computer simulations based on a spiking network model of the granular layer varying two parameters: the strength of a current injected to granule cells and the concentration of Mg2+ which controls the conductance of NMDA channels assumed on the Golgi cell dendrites. The simulations showed that cells in the granular layer can switch activity states between synchronized oscillation and random burst-silent alternation depending on the two parameters. For higher Mg2+ concentration and a weaker injected current, granule and Golgi cells elicited spikes synchronously (synchronized oscillation state). In contrast, for lower Mg2+ concentration and a stronger injected current, those cells showed the random burst-silent alternation (POT-representing state). It is suggested that NMDA channels on the Golgi cell dendrites play an important role for determining how the granular layer works in response to external input. PMID:21779155

Electrogastrographic and autonomic responses during oculovestibular recoupling in flight simulation.

PubMed

Cevette, Michael J; Pradhan, Gaurav N; Cocco, Daniela; Crowell, Michael D; Galea, Anna M; Bartlett, Jennifer; Stepanek, Jan

2014-01-01

Simulator sickness causes vestibulo-autonomic responses that increase sympathetic activity and decrease parasympathetic activity. The purpose of the study was to quantify these responses through electrogastrography and cardiac interbeat intervals during flight simulation. There were 29 subjects that were randomly assigned to 2 parallel arms: (1) oculovestibular recoupling, where galvanic vestibular stimulation was synchronous with the visual field; and (2) control. Electrogastrography and interbeat interval data were collected during baseline, simulation, and post-simulation periods. A simulator sickness questionnaire was administered. Statistically significant differences were observed in percentage of recording time with the dominant frequency of electrogastrography in normogastric and bradygastric domains between the oculovestibular recoupling and control groups. Normogastria was dominant during simulation in the oculovestibular recoupling group. In the control group, the percentage of recording time with the dominant frequency decreased by 22% in normogastria and increased by 20% in bradygastria. The percentage change of the dominant power instability coefficient from baseline to simulation was 26% in the oculovestibular recoupling group vs. 108% in the control group. The power of high-frequency components for interbeat intervals did not change significantly in the oculovestibular recoupling group and was decreased during simulation in the control group. Electrogastrography and interbeat intervals are sensitive indices of autonomic changes in subjects undergoing flight simulation. These data demonstrate the potential of oculovestibular recoupling to stabilize gastric activity and cardiac autonomic changes altered during simulator and motion sickness.

Magnetic domain wall engineering in a nanoscale permalloy junction

NASA Astrophysics Data System (ADS)

Wang, Junlin; Zhang, Xichao; Lu, Xianyang; Zhang, Jason; Yan, Yu; Ling, Hua; Wu, Jing; Zhou, Yan; Xu, Yongbing

2017-08-01

Nanoscale magnetic junctions provide a useful approach to act as building blocks for magnetoresistive random access memories (MRAM), where one of the key issues is to control the magnetic domain configuration. Here, we study the domain structure and the magnetic switching in the Permalloy (Fe20Ni80) nanoscale magnetic junctions with different thicknesses by using micromagnetic simulations. It is found that both the 90-° and 45-° domain walls can be formed between the junctions and the wire arms depending on the thickness of the device. The magnetic switching fields show distinct thickness dependencies with a broad peak varying from 7 nm to 22 nm depending on the junction sizes, and the large magnetic switching fields favor the stability of the MRAM operation.

Effects of drain bias on the statistical variation of double-gate tunnel field-effect transistors

NASA Astrophysics Data System (ADS)

Choi, Woo Young

2017-04-01

The effects of drain bias on the statistical variation of double-gate (DG) tunnel field-effect transistors (TFETs) are discussed in comparison with DG metal-oxide-semiconductor FETs (MOSFETs). Statistical variation corresponds to the variation of threshold voltage (V th), subthreshold swing (SS), and drain-induced barrier thinning (DIBT). The unique statistical variation characteristics of DG TFETs and DG MOSFETs with the variation of drain bias are analyzed by using full three-dimensional technology computer-aided design (TCAD) simulation in terms of the three dominant variation sources: line-edge roughness (LER), random dopant fluctuation (RDF) and workfunction variation (WFV). It is observed than DG TFETs suffer from less severe statistical variation as drain voltage increases unlike DG MOSFETs.

Attofarad resolution capacitance-voltage measurement of nanometer scale field effect transistors utilizing ambient noise.

PubMed

Gokirmak, Ali; Inaltekin, Hazer; Tiwari, Sandip

2009-08-19

A high resolution capacitance-voltage (C-V) characterization technique, enabling direct measurement of electronic properties at the nanoscale in devices such as nanowire field effect transistors (FETs) through the use of random fluctuations, is described. The minimum noise level required for achieving sub-aF (10(-18) F) resolution, the leveraging of stochastic resonance, and the effect of higher levels of noise are illustrated through simulations. The non-linear DeltaC(gate-source/drain)-V(gate) response of FETs is utilized to determine the inversion layer capacitance (C(inv)) and carrier mobility. The technique is demonstrated by extracting the carrier concentration and effective electron mobility in a nanoscale Si FET with C(inv) = 60 aF.

Modeling epidemic spread with awareness and heterogeneous transmission rates in networks.

PubMed

Shang, Yilun

2013-06-01

During an epidemic outbreak in a human population, susceptibility to infection can be reduced by raising awareness of the disease. In this paper, we investigate the effects of three forms of awareness (i.e., contact, local, and global) on the spread of a disease in a random network. Connectivity-correlated transmission rates are assumed. By using the mean-field theory and numerical simulation, we show that both local and contact awareness can raise the epidemic thresholds while the global awareness cannot, which mirrors the recent results of Wu et al. The obtained results point out that individual behaviors in the presence of an infectious disease has a great influence on the epidemic dynamics. Our method enriches mean-field analysis in epidemic models.

Domino model for geomagnetic field reversals.

PubMed

Mori, N; Schmitt, D; Wicht, J; Ferriz-Mas, A; Mouri, H; Nakamichi, A; Morikawa, M

2013-01-01

We solve the equations of motion of a one-dimensional planar Heisenberg (or Vaks-Larkin) model consisting of a system of interacting macrospins aligned along a ring. Each spin has unit length and is described by its angle with respect to the rotational axis. The orientation of the spins can vary in time due to spin-spin interaction and random forcing. We statistically describe the behavior of the sum of all spins for different parameters. The term "domino model" in the title refers to the interaction among the spins. We compare the model results with geomagnetic field reversals and dynamo simulations and find strikingly similar behavior. The aggregate of all spins keeps the same direction for a long time and, once in a while, begins flipping to change the orientation by almost 180 degrees (mimicking a geomagnetic reversal) or to move back to the original direction (mimicking an excursion). Most of the time the spins are aligned or antialigned and deviate only slightly with respect to the rotational axis (mimicking the secular variation of the geomagnetic pole with respect to the geographic pole). Reversals are fast compared to the times in between and they occur at random times, both in the model and in the case of the Earth's magnetic field.

Building a virtual simulation platform for quasistatic breast ultrasound elastography using open source software: A preliminary investigation.

PubMed

Wang, Yu; Helminen, Emily; Jiang, Jingfeng

2015-09-01

Quasistatic ultrasound elastography (QUE) is being used to augment in vivo characterization of breast lesions. Results from early clinical trials indicated that there was a lack of confidence in image interpretation. Such confidence can only be gained through rigorous imaging tests using complex, heterogeneous but known media. The objective of this study is to build a virtual breast QUE simulation platform in the public domain that can be used not only for innovative QUE research but also for rigorous imaging tests. The main thrust of this work is to streamline biomedical ultrasound simulations by leveraging existing open source software packages including Field II (ultrasound simulator), VTK (geometrical visualization and processing), FEBio [finite element (FE) analysis], and Tetgen (mesh generator). However, integration of these open source packages is nontrivial and requires interdisciplinary knowledge. In the first step, a virtual breast model containing complex anatomical geometries was created through a novel combination of image-based landmark structures and randomly distributed (small) structures. Image-based landmark structures were based on data from the NIH Visible Human Project. Subsequently, an unstructured FE-mesh was created by Tetgen. In the second step, randomly positioned point scatterers were placed within the meshed breast model through an octree-based algorithm to make a virtual breast ultrasound phantom. In the third step, an ultrasound simulator (Field II) was used to interrogate the virtual breast phantom to obtain simulated ultrasound echo data. Of note, tissue deformation generated using a FE-simulator (FEBio) was the basis of deforming the original virtual breast phantom in order to obtain the postdeformation breast phantom for subsequent ultrasound simulations. Using the procedures described above, a full cycle of QUE simulations involving complex and highly heterogeneous virtual breast phantoms can be accomplished for the first time. Representative examples were used to demonstrate capabilities of this virtual simulation platform. In the first set of three ultrasound simulation examples, three heterogeneous volumes of interest were selected from a virtual breast ultrasound phantom to perform sophisticated ultrasound simulations. These resultant B-mode images realistically represented the underlying complex but known media. In the second set of three QUE examples, advanced applications in QUE were simulated. The first QUE example was to show breast tumors with complex shapes and/or compositions. The resultant strain images showed complex patterns that were normally seen in freehand clinical ultrasound data. The second and third QUE examples demonstrated (deformation-dependent) nonlinear strain imaging and time-dependent strain imaging, respectively. The proposed virtual QUE platform was implemented and successfully tested in this study. Through show-case examples, the proposed work has demonstrated its capabilities of creating sophisticated QUE data in a way that cannot be done through the manufacture of physical tissue-mimicking phantoms and other software. This open software architecture will soon be made available in the public domain and can be readily adapted to meet specific needs of different research groups to drive innovations in QUE.

Uncertainty Analysis of Sonic Boom Levels Measured in a Simulator at NASA Langley

NASA Technical Reports Server (NTRS)

Rathsam, Jonathan; Ely, Jeffry W.

2012-01-01

A sonic boom simulator has been constructed at NASA Langley Research Center for testing the human response to sonic booms heard indoors. Like all measured quantities, sonic boom levels in the simulator are subject to systematic and random errors. To quantify these errors, and their net influence on the measurement result, a formal uncertainty analysis is conducted. Knowledge of the measurement uncertainty, or range of values attributable to the quantity being measured, enables reliable comparisons among measurements at different locations in the simulator as well as comparisons with field data or laboratory data from other simulators. The analysis reported here accounts for acoustic excitation from two sets of loudspeakers: one loudspeaker set at the facility exterior that reproduces the exterior sonic boom waveform and a second set of interior loudspeakers for reproducing indoor rattle sounds. The analysis also addresses the effect of pressure fluctuations generated when exterior doors of the building housing the simulator are opened. An uncertainty budget is assembled to document each uncertainty component, its sensitivity coefficient, and the combined standard uncertainty. The latter quantity will be reported alongside measurement results in future research reports to indicate data reliability.

Image-Based Modeling Reveals Dynamic Redistribution of DNA Damage into Nuclear Sub-Domains

PubMed Central

Costes, Sylvain V; Ponomarev, Artem; Chen, James L; Nguyen, David; Cucinotta, Francis A; Barcellos-Hoff, Mary Helen

2007-01-01

Several proteins involved in the response to DNA double strand breaks (DSB) form microscopically visible nuclear domains, or foci, after exposure to ionizing radiation. Radiation-induced foci (RIF) are believed to be located where DNA damage occurs. To test this assumption, we analyzed the spatial distribution of 53BP1, phosphorylated ATM, and γH2AX RIF in cells irradiated with high linear energy transfer (LET) radiation and low LET. Since energy is randomly deposited along high-LET particle paths, RIF along these paths should also be randomly distributed. The probability to induce DSB can be derived from DNA fragment data measured experimentally by pulsed-field gel electrophoresis. We used this probability in Monte Carlo simulations to predict DSB locations in synthetic nuclei geometrically described by a complete set of human chromosomes, taking into account microscope optics from real experiments. As expected, simulations produced DNA-weighted random (Poisson) distributions. In contrast, the distributions of RIF obtained as early as 5 min after exposure to high LET (1 GeV/amu Fe) were non-random. This deviation from the expected DNA-weighted random pattern can be further characterized by “relative DNA image measurements.” This novel imaging approach shows that RIF were located preferentially at the interface between high and low DNA density regions, and were more frequent than predicted in regions with lower DNA density. The same preferential nuclear location was also measured for RIF induced by 1 Gy of low-LET radiation. This deviation from random behavior was evident only 5 min after irradiation for phosphorylated ATM RIF, while γH2AX and 53BP1 RIF showed pronounced deviations up to 30 min after exposure. These data suggest that DNA damage–induced foci are restricted to certain regions of the nucleus of human epithelial cells. It is possible that DNA lesions are collected in these nuclear sub-domains for more efficient repair. PMID:17676951

Kernel-Correlated Levy Field Driven Forward Rate and Application to Derivative Pricing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bo Lijun; Wang Yongjin; Yang Xuewei, E-mail: xwyangnk@yahoo.com.cn

2013-08-01

We propose a term structure of forward rates driven by a kernel-correlated Levy random field under the HJM framework. The kernel-correlated Levy random field is composed of a kernel-correlated Gaussian random field and a centered Poisson random measure. We shall give a criterion to preclude arbitrage under the risk-neutral pricing measure. As applications, an interest rate derivative with general payoff functional is priced under this pricing measure.

Stochastic uncertainty analysis for solute transport in randomly heterogeneous media using a Karhunen‐Loève‐based moment equation approach

USGS Publications Warehouse

Liu, Gaisheng; Lu, Zhiming; Zhang, Dongxiao

2007-01-01

A new approach has been developed for solving solute transport problems in randomly heterogeneous media using the Karhunen‐Loève‐based moment equation (KLME) technique proposed by Zhang and Lu (2004). The KLME approach combines the Karhunen‐Loève decomposition of the underlying random conductivity field and the perturbative and polynomial expansions of dependent variables including the hydraulic head, flow velocity, dispersion coefficient, and solute concentration. The equations obtained in this approach are sequential, and their structure is formulated in the same form as the original governing equations such that any existing simulator, such as Modular Three‐Dimensional Multispecies Transport Model for Simulation of Advection, Dispersion, and Chemical Reactions of Contaminants in Groundwater Systems (MT3DMS), can be directly applied as the solver. Through a series of two‐dimensional examples, the validity of the KLME approach is evaluated against the classical Monte Carlo simulations. Results indicate that under the flow and transport conditions examined in this work, the KLME approach provides an accurate representation of the mean concentration. For the concentration variance, the accuracy of the KLME approach is good when the conductivity variance is 0.5. As the conductivity variance increases up to 1.0, the mismatch on the concentration variance becomes large, although the mean concentration can still be accurately reproduced by the KLME approach. Our results also indicate that when the conductivity variance is relatively large, neglecting the effects of the cross terms between velocity fluctuations and local dispersivities, as done in some previous studies, can produce noticeable errors, and a rigorous treatment of the dispersion terms becomes more appropriate.

Features of the normal choriocapillaris with OCT-angiography: Density estimation and textural properties.

PubMed

Montesano, Giovanni; Allegrini, Davide; Colombo, Leonardo; Rossetti, Luca M; Pece, Alfredo

2017-01-01

The main objective of our work is to perform an in depth analysis of the structural features of normal choriocapillaris imaged with OCT Angiography. Specifically, we provide an optimal radius for a circular Region of Interest (ROI) to obtain a stable estimate of the subfoveal choriocapillaris density and characterize its textural properties using Markov Random Fields. On each binarized image of the choriocapillaris OCT Angiography we performed simulated measurements of the subfoveal choriocapillaris densities with circular Regions of Interest (ROIs) of different radii and with small random displacements from the center of the Foveal Avascular Zone (FAZ). We then calculated the variability of the density measure with different ROI radii. We then characterized the textural features of choriocapillaris binary images by estimating the parameters of an Ising model. For each image we calculated the Optimal Radius (OR) as the minimum ROI radius required to obtain a standard deviation in the simulation below 0.01. The density measured with the individual OR was 0.52 ± 0.07 (mean ± STD). Similar density values (0.51 ± 0.07) were obtained using a fixed ROI radius of 450 μm. The Ising model yielded two parameter estimates (β = 0.34 ± 0.03; γ = 0.003 ± 0.012; mean ± STD), characterizing pixel clustering and white pixel density respectively. Using the estimated parameters to synthetize new random textures via simulation we obtained a good reproduction of the original choriocapillaris structural features and density. In conclusion, we developed an extensive characterization of the normal subfoveal choriocapillaris that might be used for flow analysis and applied to the investigation pathological alterations.

Supercomputations and big-data analysis in strong-field ultrafast optical physics: filamentation of high-peak-power ultrashort laser pulses

NASA Astrophysics Data System (ADS)

Voronin, A. A.; Panchenko, V. Ya; Zheltikov, A. M.

2016-06-01

High-intensity ultrashort laser pulses propagating in gas media or in condensed matter undergo complex nonlinear spatiotemporal evolution where temporal transformations of optical field waveforms are strongly coupled to an intricate beam dynamics and ultrafast field-induced ionization processes. At the level of laser peak powers orders of magnitude above the critical power of self-focusing, the beam exhibits modulation instabilities, producing random field hot spots and breaking up into multiple noise-seeded filaments. This problem is described by a (3  +  1)-dimensional nonlinear field evolution equation, which needs to be solved jointly with the equation for ultrafast ionization of a medium. Analysis of this problem, which is equivalent to solving a billion-dimensional evolution problem, is only possible by means of supercomputer simulations augmented with coordinated big-data processing of large volumes of information acquired through theory-guiding experiments and supercomputations. Here, we review the main challenges of supercomputations and big-data processing encountered in strong-field ultrafast optical physics and discuss strategies to confront these challenges.

Is the Non-Dipole Magnetic Field Random?

NASA Technical Reports Server (NTRS)

Walker, Andrew D.; Backus, George E.

1996-01-01

Statistical modelling of the Earth's magnetic field B has a long history. In particular, the spherical harmonic coefficients of scalar fields derived from B can be treated as Gaussian random variables. In this paper, we give examples of highly organized fields whose spherical harmonic coefficients pass tests for independent Gaussian random variables. The fact that coefficients at some depth may be usefully summarized as independent samples from a normal distribution need not imply that there really is some physical, random process at that depth. In fact, the field can be extremely structured and still be regarded for some purposes as random. In this paper, we examined the radial magnetic field B(sub r) produced by the core, but the results apply to any scalar field on the core-mantle boundary (CMB) which determines B outside the CMB.

Global enhancement and structure formation of the magnetic field in spiral galaxies

NASA Astrophysics Data System (ADS)

Khoperskov, Sergey A.; Khrapov, Sergey S.

2018-01-01

In this paper we study numerically large-scale magnetic field evolution and its enhancement in gaseous disks of spiral galaxies. We consider a set of models with the various spiral pattern parameters and the initial magnetic field strength with taking into account gas self-gravity and cooling and heating processes. In agreement with previous studies we find out that galactic magnetic field is mostly aligned with gaseous structures, however small-scale gaseous structures (spurs and clumps) are more chaotic than the magnetic field structure. In spiral arms magnetic field often coexists with the gas distribution, in the inter-arm region we see filamentary magnetic field structure. These filaments connect several isolated gaseous clumps. Simulations reveal the presence of the small-scale irregularities of the magnetic field as well as the reversal of magnetic field at the outer edge of the large-scale spurs. We provide evidences that the magnetic field in the spiral arms has a stronger mean-field component, and there is a clear inverse correlation between gas density and plasma-beta parameter, compared to the rest of the disk with a more turbulent component of the field and an absence of correlation between gas density and plasma-beta. We show the mean field growth up to >3-10 μG in the cold gas during several rotation periods (>500-800 Myr), whereas ratio between azimuthal and radial field is equal to >4/1. We find an enhancement of random and ordered components of the magnetic field. Mean field strength increases by a factor of >1.5-2.5 for models with various spiral pattern parameters. Random magnetic field component can reach up to 25% from the total strength. By making an analysis of the time-dependent evolution of the radial Poynting flux, we point out that the magnetic field strength is enhanced more strongly at the galactic outskirts which is due to the radial transfer of magnetic energy by the spiral arms pushing the magnetic field outward. Our results also support the presence of sufficient conditions for the development of magnetorotational instability at distances >11 kpc after >300 Myr of evolution.

Defining Higher-Order Turbulent Moment Closures with an Artificial Neural Network and Random Forest

NASA Astrophysics Data System (ADS)

McGibbon, J.; Bretherton, C. S.

2017-12-01

Unresolved turbulent advection and clouds must be parameterized in atmospheric models. Modern higher-order closure schemes depend on analytic moment closure assumptions that diagnose higher-order moments in terms of lower-order ones. These are then tested against Large-Eddy Simulation (LES) higher-order moment relations. However, these relations may not be neatly analytic in nature. Rather than rely on an analytic higher-order moment closure, can we use machine learning on LES data itself to define a higher-order moment closure?We assess the ability of a deep artificial neural network (NN) and random forest (RF) to perform this task using a set of observationally-based LES runs from the MAGIC field campaign. By training on a subset of 12 simulations and testing on remaining simulations, we avoid over-fitting the training data.Performance of the NN and RF will be assessed and compared to the Analytic Double Gaussian 1 (ADG1) closure assumed by Cloudy Layers Unified By Binormals (CLUBB), a higher-order turbulence closure currently used in the Community Atmosphere Model (CAM). We will show that the RF outperforms the NN and the ADG1 closure for the MAGIC cases within this diagnostic framework. Progress and challenges in using a diagnostic machine learning closure within a prognostic cloud and turbulence parameterization will also be discussed.

Random Fields

NASA Astrophysics Data System (ADS)

Vanmarcke, Erik

1983-03-01

Random variation over space and time is one of the few attributes that might safely be predicted as characterizing almost any given complex system. Random fields or "distributed disorder systems" confront astronomers, physicists, geologists, meteorologists, biologists, and other natural scientists. They appear in the artifacts developed by electrical, mechanical, civil, and other engineers. They even underlie the processes of social and economic change. The purpose of this book is to bring together existing and new methodologies of random field theory and indicate how they can be applied to these diverse areas where a "deterministic treatment is inefficient and conventional statistics insufficient." Many new results and methods are included. After outlining the extent and characteristics of the random field approach, the book reviews the classical theory of multidimensional random processes and introduces basic probability concepts and methods in the random field context. It next gives a concise amount of the second-order analysis of homogeneous random fields, in both the space-time domain and the wave number-frequency domain. This is followed by a chapter on spectral moments and related measures of disorder and on level excursions and extremes of Gaussian and related random fields. After developing a new framework of analysis based on local averages of one-, two-, and n-dimensional processes, the book concludes with a chapter discussing ramifications in the important areas of estimation, prediction, and control. The mathematical prerequisite has been held to basic college-level calculus.

Surface plasmon enhanced cell microscopy with blocked random spatial activation

NASA Astrophysics Data System (ADS)

Son, Taehwang; Oh, Youngjin; Lee, Wonju; Yang, Heejin; Kim, Donghyun

2016-03-01

We present surface plasmon enhanced fluorescence microscopy with random spatial sampling using patterned block of silver nanoislands. Rigorous coupled wave analysis was performed to confirm near-field localization on nanoislands. Random nanoislands were fabricated in silver by temperature annealing. By analyzing random near-field distribution, average size of localized fields was found to be on the order of 135 nm. Randomly localized near-fields were used to spatially sample F-actin of J774 cells (mouse macrophage cell-line). Image deconvolution algorithm based on linear imaging theory was established for stochastic estimation of fluorescent molecular distribution. The alignment between near-field distribution and raw image was performed by the patterned block. The achieved resolution is dependent upon factors including the size of localized fields and estimated to be 100-150 nm.

Space electric field concentrated effect for Zr:SiO2 RRAM devices using porous SiO2 buffer layer

PubMed Central

2013-01-01

To improve the operation current lowing of the Zr:SiO2 RRAM devices, a space electric field concentrated effect established by the porous SiO2 buffer layer was investigated and found in this study. The resistive switching properties of the low-resistance state (LRS) and high-resistance state (HRS) in resistive random access memory (RRAM) devices for the single-layer Zr:SiO2 and bilayer Zr:SiO2/porous SiO2 thin films were analyzed and discussed. In addition, the original space charge limited current (SCLC) conduction mechanism in LRS and HRS of the RRAM devices using bilayer Zr:SiO2/porous SiO2 thin films was found. Finally, a space electric field concentrated effect in the bilayer Zr:SiO2/porous SiO2 RRAM devices was also explained and verified by the COMSOL Multiphysics simulation model. PMID:24330524

Interstellar Pickup Ion Acceleration in the Turbulent Magnetic Field at the Solar Wind Termination Shock Using a Focused Transport Approach

NASA Astrophysics Data System (ADS)

Ye, Junye; le Roux, Jakobus A.; Arthur, Aaron D.

2016-08-01

We study the physics of locally born interstellar pickup proton acceleration at the nearly perpendicular solar wind termination shock (SWTS) in the presence of a random magnetic field spiral angle using a focused transport model. Guided by Voyager 2 observations, the spiral angle is modeled with a q-Gaussian distribution. The spiral angle fluctuations, which are used to generate the perpendicular diffusion of pickup protons across the SWTS, play a key role in enabling efficient injection and rapid diffusive shock acceleration (DSA) when these particles follow field lines. Our simulations suggest that variation of both the shape (q-value) and the standard deviation (σ-value) of the q-Gaussian distribution significantly affect the injection speed, pitch-angle anisotropy, radial distribution, and the efficiency of the DSA of pickup protons at the SWTS. For example, increasing q and especially reducing σ enhances the DSA rate.

Heterodyne efficiency for a coherent laser radar with diffuse or aerosol targets

NASA Technical Reports Server (NTRS)

Frehlich, R. G.

1993-01-01

The performance of a Coherent Laser Radar is determined by the statistics of the coherent Doppler signal. The heterodyne efficiency is an excellent indication of performance because it is an absolute measure of beam alignment and is independent of the transmitter power, the target backscatter coefficient, the atmospheric attenuation, and the detector quantum efficiency and gain. The theoretical calculation of heterodyne efficiency for an optimal monostatic lidar with a circular aperture and Gaussian transmit laser is presented including beam misalignment in the far-field and near-field regimes. The statistical behavior of estimates of the heterodyne efficiency using a calibration hard target are considered. For space based applications, a biased estimate of heterodyne efficiency is proposed that removes the variability due to the random surface return but retains the sensitivity to misalignment. Physical insight is provided by simulation of the fields on the detector surface. The required detector calibration is also discussed.

Effect of patient setup errors on simultaneously integrated boost head and neck IMRT treatment plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siebers, Jeffrey V.; Keall, Paul J.; Wu Qiuwen

2005-10-01

Purpose: The purpose of this study is to determine dose delivery errors that could result from random and systematic setup errors for head-and-neck patients treated using the simultaneous integrated boost (SIB)-intensity-modulated radiation therapy (IMRT) technique. Methods and Materials: Twenty-four patients who participated in an intramural Phase I/II parotid-sparing IMRT dose-escalation protocol using the SIB treatment technique had their dose distributions reevaluated to assess the impact of random and systematic setup errors. The dosimetric effect of random setup error was simulated by convolving the two-dimensional fluence distribution of each beam with the random setup error probability density distribution. Random setup errorsmore » of {sigma} = 1, 3, and 5 mm were simulated. Systematic setup errors were simulated by randomly shifting the patient isocenter along each of the three Cartesian axes, with each shift selected from a normal distribution. Systematic setup error distributions with {sigma} = 1.5 and 3.0 mm along each axis were simulated. Combined systematic and random setup errors were simulated for {sigma} = {sigma} = 1.5 and 3.0 mm along each axis. For each dose calculation, the gross tumor volume (GTV) received by 98% of the volume (D{sub 98}), clinical target volume (CTV) D{sub 90}, nodes D{sub 90}, cord D{sub 2}, and parotid D{sub 50} and parotid mean dose were evaluated with respect to the plan used for treatment for the structure dose and for an effective planning target volume (PTV) with a 3-mm margin. Results: Simultaneous integrated boost-IMRT head-and-neck treatment plans were found to be less sensitive to random setup errors than to systematic setup errors. For random-only errors, errors exceeded 3% only when the random setup error {sigma} exceeded 3 mm. Simulated systematic setup errors with {sigma} = 1.5 mm resulted in approximately 10% of plan having more than a 3% dose error, whereas a {sigma} = 3.0 mm resulted in half of the plans having more than a 3% dose error and 28% with a 5% dose error. Combined random and systematic dose errors with {sigma} = {sigma} = 3.0 mm resulted in more than 50% of plans having at least a 3% dose error and 38% of the plans having at least a 5% dose error. Evaluation with respect to a 3-mm expanded PTV reduced the observed dose deviations greater than 5% for the {sigma} = {sigma} = 3.0 mm simulations to 5.4% of the plans simulated. Conclusions: Head-and-neck SIB-IMRT dosimetric accuracy would benefit from methods to reduce patient systematic setup errors. When GTV, CTV, or nodal volumes are used for dose evaluation, plans simulated including the effects of random and systematic errors deviate substantially from the nominal plan. The use of PTVs for dose evaluation in the nominal plan improves agreement with evaluated GTV, CTV, and nodal dose values under simulated setup errors. PTV concepts should be used for SIB-IMRT head-and-neck squamous cell carcinoma patients, although the size of the margins may be less than those used with three-dimensional conformal radiation therapy.« less

Treatment planning and delivery of involved field radiotherapy in advanced Hodgkin's disease: results from a questionnaire-based audit for the UK Stanford V regimen vs ABVD clinical trial quality assurance programme (ISRCTN 64141244).

PubMed

Diez, P; Hoskin, P J; Aird, E G A

2007-10-01

This questionnaire forms the basis of the quality assurance (QA) programme for the UK randomized Phase III study of the Stanford V regimen versus ABVD for treatment of advanced Hodgkin's disease to assess differences between participating centres in treatment planning and delivery of involved-field radiotherapy for Hodgkin's lymphoma The questionnaire, which was circulated amongst 42 participating centres, consisted of seven sections: target volume definition and dose prescription; critical structures; patient positioning and irradiation techniques; planning; dose calculation; verification; and future developments The results are based on 25 responses. One-third plan using CT alone, one-third use solely the simulator and the rest individualize, depending on disease site. Eleven centres determine a dose distribution for each patient. Technique depends on disease site and whether CT or simulator planning is employed. Most departments apply isocentric techniques and use immobilization and customized shielding. In vivo dosimetry is performed in 7 centres and treatment verification occurs in 24 hospitals. In conclusion, the planning and delivery of treatment for lymphoma patients varies across the country. Conventional planning is still widespread but most centres are moving to CT-based planning and virtual simulation with extended use of immobilization, customized shielding and compensation.

Study of electron transport in a Hall thruster by axial–radial fully kinetic particle simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, Shinatora, E-mail: choh.shinatora@jaxa.jp; Kubota, Kenichi; Funaki, Ikkoh

2015-10-15

Electron transport across a magnetic field in a magnetic-layer-type Hall thruster was numerically investigated for the future predictive modeling of Hall thrusters. The discharge of a 1-kW-class magnetic-layer-type Hall thruster designed for high-specific-impulse operation was modeled using an r-z two-dimensional fully kinetic particle code with and without artificial electron-diffusion models. The thruster performance results showed that both electron transport models captured the experimental result within discrepancies less than 20% in thrust and discharge current for all the simulated operation conditions. The electron cross-field transport mechanism of the so-called anomalous diffusion was self-consistently observed in the simulation without artificial diffusion models;more » the effective electron mobility was two orders of magnitude higher than the value obtained using the classical diffusion theory. To account for the self-consistently observed anomalous transport, the oscillation of plasma properties was speculated. It was suggested that the enhanced random-walk diffusion due to the velocity oscillation of low-frequency electron flow could explain the observed anomalous diffusion within an order of magnitude. The dominant oscillation mode of the electron flow velocity was found to be 20 kHz, which was coupled to electrostatic oscillation excited by global ionization instability.« less

Comparison of Coarse-Grained Approaches in Predicting Polymer Nanocomposite Phase Behavior

DOE PAGES

Koski, Jason P.; Ferrier, Robert C.; Krook, Nadia M.; ...

2017-11-02

Because of the considerable parameter space, efficient theoretical and simulation methods are required to predict the morphology and guide experiments in polymer nanocomposites (PNCs). Unfortunately, theoretical and simulation methods are restricted in their ability to accurately map to experiments based on necessary approximations and numerical limitations. In this study, we provide direct comparisons of two recently developed coarse-grained approaches for modeling polymer nanocomposites (PNCs): polymer nanocomposite field theory (PNC-FT) and dynamic mean-field theory (DMFT). These methods are uniquely suited to efficiently capture mesoscale phase behavior of PNCs in comparison to other theoretical and simulation frameworks. We demonstrate the ability ofmore » both methods to capture macrophase separation and describe the thermodynamics of PNCs. We systematically test how the nanoparticle morphology in PNCs is affected by a uniform probability distribution of grafting sites, common in field-based methods, versus random discrete grafting sites on the nanoparticle surface. We also analyze the accuracy of the mean-field approximation in capturing the phase behavior of PNCs. Moreover, the DMFT method introduces the ability to describe nonequilibrium phase behavior while the PNC-FT method is strictly an equilibrium method. With the DMFT method we are able to show the evolution of nonequilibrium states toward their equilibrium state and a qualitative assessment of the dynamics in these systems. These simulations are compared to experiments consisting of polystyrene grafted gold nanorods in a poly(methyl methacrylate) matrix to ensure the model gives results that qualitatively agree with the experiments. This study reveals that nanoparticles in a relatively high matrix molecular weight are trapped in a nonequilibrium state and demonstrates the utility of the DMFT framework in capturing nonequilibrium phase behavior of PNCs. In conclusion, both the PNC-FT and DMFT framework are promising methods to describe the thermodynamic and nonequilibrium phase behavior of PNCs.« less

Stochastic porous media modeling and high-resolution schemes for numerical simulation of subsurface immiscible fluid flow transport

NASA Astrophysics Data System (ADS)

Brantson, Eric Thompson; Ju, Binshan; Wu, Dan; Gyan, Patricia Semwaah

2018-04-01

This paper proposes stochastic petroleum porous media modeling for immiscible fluid flow simulation using Dykstra-Parson coefficient (V DP) and autocorrelation lengths to generate 2D stochastic permeability values which were also used to generate porosity fields through a linear interpolation technique based on Carman-Kozeny equation. The proposed method of permeability field generation in this study was compared to turning bands method (TBM) and uniform sampling randomization method (USRM). On the other hand, many studies have also reported that, upstream mobility weighting schemes, commonly used in conventional numerical reservoir simulators do not accurately capture immiscible displacement shocks and discontinuities through stochastically generated porous media. This can be attributed to high level of numerical smearing in first-order schemes, oftentimes misinterpreted as subsurface geological features. Therefore, this work employs high-resolution schemes of SUPERBEE flux limiter, weighted essentially non-oscillatory scheme (WENO), and monotone upstream-centered schemes for conservation laws (MUSCL) to accurately capture immiscible fluid flow transport in stochastic porous media. The high-order schemes results match well with Buckley Leverett (BL) analytical solution without any non-oscillatory solutions. The governing fluid flow equations were solved numerically using simultaneous solution (SS) technique, sequential solution (SEQ) technique and iterative implicit pressure and explicit saturation (IMPES) technique which produce acceptable numerical stability and convergence rate. A comparative and numerical examples study of flow transport through the proposed method, TBM and USRM permeability fields revealed detailed subsurface instabilities with their corresponding ultimate recovery factors. Also, the impact of autocorrelation lengths on immiscible fluid flow transport were analyzed and quantified. A finite number of lines used in the TBM resulted into visual artifact banding phenomenon unlike the proposed method and USRM. In all, the proposed permeability and porosity fields generation coupled with the numerical simulator developed will aid in developing efficient mobility control schemes to improve on poor volumetric sweep efficiency in porous media.

Comparison of Coarse-Grained Approaches in Predicting Polymer Nanocomposite Phase Behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koski, Jason P.; Ferrier, Robert C.; Krook, Nadia M.

Because of the considerable parameter space, efficient theoretical and simulation methods are required to predict the morphology and guide experiments in polymer nanocomposites (PNCs). Unfortunately, theoretical and simulation methods are restricted in their ability to accurately map to experiments based on necessary approximations and numerical limitations. In this study, we provide direct comparisons of two recently developed coarse-grained approaches for modeling polymer nanocomposites (PNCs): polymer nanocomposite field theory (PNC-FT) and dynamic mean-field theory (DMFT). These methods are uniquely suited to efficiently capture mesoscale phase behavior of PNCs in comparison to other theoretical and simulation frameworks. We demonstrate the ability ofmore » both methods to capture macrophase separation and describe the thermodynamics of PNCs. We systematically test how the nanoparticle morphology in PNCs is affected by a uniform probability distribution of grafting sites, common in field-based methods, versus random discrete grafting sites on the nanoparticle surface. We also analyze the accuracy of the mean-field approximation in capturing the phase behavior of PNCs. Moreover, the DMFT method introduces the ability to describe nonequilibrium phase behavior while the PNC-FT method is strictly an equilibrium method. With the DMFT method we are able to show the evolution of nonequilibrium states toward their equilibrium state and a qualitative assessment of the dynamics in these systems. These simulations are compared to experiments consisting of polystyrene grafted gold nanorods in a poly(methyl methacrylate) matrix to ensure the model gives results that qualitatively agree with the experiments. This study reveals that nanoparticles in a relatively high matrix molecular weight are trapped in a nonequilibrium state and demonstrates the utility of the DMFT framework in capturing nonequilibrium phase behavior of PNCs. In conclusion, both the PNC-FT and DMFT framework are promising methods to describe the thermodynamic and nonequilibrium phase behavior of PNCs.« less

RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference

PubMed Central

Maples, Brian K.; Gravel, Simon; Kenny, Eimear E.; Bustamante, Carlos D.

2013-01-01

Local-ancestry inference is an important step in the genetic analysis of fully sequenced human genomes. Current methods can only detect continental-level ancestry (i.e., European versus African versus Asian) accurately even when using millions of markers. Here, we present RFMix, a powerful discriminative modeling approach that is faster (∼30×) and more accurate than existing methods. We accomplish this by using a conditional random field parameterized by random forests trained on reference panels. RFMix is capable of learning from the admixed samples themselves to boost performance and autocorrect phasing errors. RFMix shows high sensitivity and specificity in simulated Hispanics/Latinos and African Americans and admixed Europeans, Africans, and Asians. Finally, we demonstrate that African Americans in HapMap contain modest (but nonzero) levels of Native American ancestry (∼0.4%). PMID:23910464

Force-field functor theory: classical force-fields which reproduce equilibrium quantum distributions

PubMed Central

Babbush, Ryan; Parkhill, John; Aspuru-Guzik, Alán

2013-01-01

Feynman and Hibbs were the first to variationally determine an effective potential whose associated classical canonical ensemble approximates the exact quantum partition function. We examine the existence of a map between the local potential and an effective classical potential which matches the exact quantum equilibrium density and partition function. The usefulness of such a mapping rests in its ability to readily improve Born-Oppenheimer potentials for use with classical sampling. We show that such a map is unique and must exist. To explore the feasibility of using this result to improve classical molecular mechanics, we numerically produce a map from a library of randomly generated one-dimensional potential/effective potential pairs then evaluate its performance on independent test problems. We also apply the map to simulate liquid para-hydrogen, finding that the resulting radial pair distribution functions agree well with path integral Monte Carlo simulations. The surprising accessibility and transferability of the technique suggest a quantitative route to adapting Born-Oppenheimer potentials, with a motivation similar in spirit to the powerful ideas and approximations of density functional theory. PMID:24790954

Comparison of forcing functions in magnetohydrodynamics

NASA Astrophysics Data System (ADS)

McKay, Mairi E.; Linkmann, Moritz; Clark, Daniel; Chalupa, Adam A.; Berera, Arjun

2017-11-01

Results are presented of direct numerical simulations of incompressible, homogeneous magnetohydrodynamic turbulence without a mean magnetic field, subject to different mechanical forcing functions commonly used in the literature. Specifically, the forces are negative damping (which uses the large-scale velocity field as a forcing function), a nonhelical random force, and a nonhelical static sinusoidal force (analogous to helical ABC forcing). The time evolution of the three ideal invariants (energy, magnetic helicity, and cross helicity), the time-averaged energy spectra, the energy ratios, and the dissipation ratios are examined. All three forcing functions produce qualitatively similar steady states with regard to the time evolution of the energy and magnetic helicity. However, differences in the cross-helicity evolution are observed, particularly in the case of the static sinusoidal method of energy injection. Indeed, an ensemble of sinusoidally forced simulations with identical parameters shows significant variations in the cross helicity over long time periods, casting some doubt on the validity of the principle of ergodicity in systems in which the injection of helicity cannot be controlled. Cross helicity can unexpectedly enter the system through the forcing function and must be carefully monitored.

Ab Initio Molecular Dynamics and Lattice Dynamics-Based Force Field for Modeling Hexagonal Boron Nitride in Mechanical and Interfacial Applications.

PubMed

Govind Rajan, Ananth; Strano, Michael S; Blankschtein, Daniel

2018-04-05

Hexagonal boron nitride (hBN) is an up-and-coming two-dimensional material, with applications in electronic devices, tribology, and separation membranes. Herein, we utilize density-functional-theory-based ab initio molecular dynamics (MD) simulations and lattice dynamics calculations to develop a classical force field (FF) for modeling hBN. The FF predicts the crystal structure, elastic constants, and phonon dispersion relation of hBN with good accuracy and exhibits remarkable agreement with the interlayer binding energy predicted by random phase approximation calculations. We demonstrate the importance of including Coulombic interactions but excluding 1-4 intrasheet interactions to obtain the correct phonon dispersion relation. We find that improper dihedrals do not modify the bulk mechanical properties and the extent of thermal vibrations in hBN, although they impact its flexural rigidity. Combining the FF with the accurate TIP4P/Ice water model yields excellent agreement with interaction energies predicted by quantum Monte Carlo calculations. Our FF should enable an accurate description of hBN interfaces in classical MD simulations.

Investigations of turbulent scalar fields using probability density function approach

NASA Technical Reports Server (NTRS)

Gao, Feng

1991-01-01

Scalar fields undergoing random advection have attracted much attention from researchers in both the theoretical and practical sectors. Research interest spans from the study of the small scale structures of turbulent scalar fields to the modeling and simulations of turbulent reacting flows. The probability density function (PDF) method is an effective tool in the study of turbulent scalar fields, especially for those which involve chemical reactions. It has been argued that a one-point, joint PDF approach is the one to choose from among many simulation and closure methods for turbulent combustion and chemically reacting flows based on its practical feasibility in the foreseeable future for multiple reactants. Instead of the multi-point PDF, the joint PDF of a scalar and its gradient which represents the roles of both scalar and scalar diffusion is introduced. A proper closure model for the molecular diffusion term in the PDF equation is investigated. Another direction in this research is to study the mapping closure method that has been recently proposed to deal with the PDF's in turbulent fields. This method seems to have captured the physics correctly when applied to diffusion problems. However, if the turbulent stretching is included, the amplitude mapping has to be supplemented by either adjusting the parameters representing turbulent stretching at each time step or by introducing the coordinate mapping. This technique is still under development and seems to be quite promising. The final objective of this project is to understand some fundamental properties of the turbulent scalar fields and to develop practical numerical schemes that are capable of handling turbulent reacting flows.

Compact, self-contained enhanced-vision system (EVS) sensor simulator

NASA Astrophysics Data System (ADS)

Tiana, Carlo

2007-04-01

We describe the model SIM-100 PC-based simulator, for imaging sensors used, or planned for use, in Enhanced Vision System (EVS) applications. Typically housed in a small-form-factor PC, it can be easily integrated into existing out-the-window visual simulators for fixed-wing or rotorcraft, to add realistic sensor imagery to the simulator cockpit. Multiple bands of infrared (short-wave, midwave, extended-midwave and longwave) as well as active millimeter-wave RADAR systems can all be simulated in real time. Various aspects of physical and electronic image formation and processing in the sensor are accurately (and optionally) simulated, including sensor random and fixed pattern noise, dead pixels, blooming, B-C scope transformation (MMWR). The effects of various obscurants (fog, rain, etc.) on the sensor imagery are faithfully represented and can be selected by an operator remotely and in real-time. The images generated by the system are ideally suited for many applications, ranging from sensor development engineering tradeoffs (Field Of View, resolution, etc.), to pilot familiarization and operational training, and certification support. The realistic appearance of the simulated images goes well beyond that of currently deployed systems, and beyond that required by certification authorities; this level of realism will become necessary as operational experience with EVS systems grows.

Notes From the Field: Secondary Task Precision for Cognitive Load Estimation During Virtual Reality Surgical Simulation Training.

PubMed

Rasmussen, Sebastian R; Konge, Lars; Mikkelsen, Peter T; Sørensen, Mads S; Andersen, Steven A W

2016-03-01

Cognitive load (CL) theory suggests that working memory can be overloaded in complex learning tasks such as surgical technical skills training, which can impair learning. Valid and feasible methods for estimating the CL in specific learning contexts are necessary before the efficacy of CL-lowering instructional interventions can be established. This study aims to explore secondary task precision for the estimation of CL in virtual reality (VR) surgical simulation and also investigate the effects of CL-modifying factors such as simulator-integrated tutoring and repeated practice. Twenty-four participants were randomized for visual assistance by a simulator-integrated tutor function during the first 5 of 12 repeated mastoidectomy procedures on a VR temporal bone simulator. Secondary task precision was found to be significantly lower during simulation compared with nonsimulation baseline, p < .001. Contrary to expectations, simulator-integrated tutoring and repeated practice did not have an impact on secondary task precision. This finding suggests that even though considerable changes in CL are reflected in secondary task precision, it lacks sensitivity. In contrast, secondary task reaction time could be more sensitive, but requires substantial postprocessing of data. Therefore, future studies on the effect of CL modifying interventions should weigh the pros and cons of the various secondary task measurements. © The Author(s) 2015.

The conditional power of randomization tests for single-case effect sizes in designs with randomized treatment order: A Monte Carlo simulation study.

PubMed

Michiels, Bart; Heyvaert, Mieke; Onghena, Patrick

2018-04-01

The conditional power (CP) of the randomization test (RT) was investigated in a simulation study in which three different single-case effect size (ES) measures were used as the test statistics: the mean difference (MD), the percentage of nonoverlapping data (PND), and the nonoverlap of all pairs (NAP). Furthermore, we studied the effect of the experimental design on the RT's CP for three different single-case designs with rapid treatment alternation: the completely randomized design (CRD), the randomized block design (RBD), and the restricted randomized alternation design (RRAD). As a third goal, we evaluated the CP of the RT for three types of simulated data: data generated from a standard normal distribution, data generated from a uniform distribution, and data generated from a first-order autoregressive Gaussian process. The results showed that the MD and NAP perform very similarly in terms of CP, whereas the PND performs substantially worse. Furthermore, the RRAD yielded marginally higher power in the RT, followed by the CRD and then the RBD. Finally, the power of the RT was almost unaffected by the type of the simulated data. On the basis of the results of the simulation study, we recommend at least 20 measurement occasions for single-case designs with a randomized treatment order that are to be evaluated with an RT using a 5% significance level. Furthermore, we do not recommend use of the PND, because of its low power in the RT.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Juan; Beltran, Chris J., E-mail: beltran.chris@mayo.edu; Herman, Michael G.

Purpose: To quantitatively and systematically assess dosimetric effects induced by spot positioning error as a function of spot spacing (SS) on intensity-modulated proton therapy (IMPT) plan quality and to facilitate evaluation of safety tolerance limits on spot position. Methods: Spot position errors (PE) ranging from 1 to 2 mm were simulated. Simple plans were created on a water phantom, and IMPT plans were calculated on two pediatric patients with a brain tumor of 28 and 3 cc, respectively, using a commercial planning system. For the phantom, a uniform dose was delivered to targets located at different depths from 10 tomore » 20 cm with various field sizes from 2{sup 2} to 15{sup 2} cm{sup 2}. Two nominal spot sizes, 4.0 and 6.6 mm of 1 σ in water at isocenter, were used for treatment planning. The SS ranged from 0.5 σ to 1.5 σ, which is 2–6 mm for the small spot size and 3.3–9.9 mm for the large spot size. Various perturbation scenarios of a single spot error and systematic and random multiple spot errors were studied. To quantify the dosimetric effects, percent dose error (PDE) depth profiles and the value of percent dose error at the maximum dose difference (PDE [ΔDmax]) were used for evaluation. Results: A pair of hot and cold spots was created per spot shift. PDE[ΔDmax] is found to be a complex function of PE, SS, spot size, depth, and global spot distribution that can be well defined in simple models. For volumetric targets, the PDE [ΔDmax] is not noticeably affected by the change of field size or target volume within the studied ranges. In general, reducing SS decreased the dose error. For the facility studied, given a single spot error with a PE of 1.2 mm and for both spot sizes, a SS of 1σ resulted in a 2% maximum dose error; a SS larger than 1.25 σ substantially increased the dose error and its sensitivity to PE. A similar trend was observed in multiple spot errors (both systematic and random errors). Systematic PE can lead to noticeable hot spots along the field edges, which may be near critical structures. However, random PE showed minimal dose error. Conclusions: Dose error dependence for PE was quantitatively and systematically characterized and an analytic tool was built to simulate systematic and random errors for patient-specific IMPT. This information facilitates the determination of facility specific spot position error thresholds.« less

Stochastic simulation for the propagation of high-frequency acoustic waves through a random velocity field

NASA Astrophysics Data System (ADS)

Lu, B.; Darmon, M.; Leymarie, N.; Chatillon, S.; Potel, C.

2012-05-01

In-service inspection of Sodium-Cooled Fast Reactors (SFR) requires the development of non-destructive techniques adapted to the harsh environment conditions and the examination complexity. From past experiences, ultrasonic techniques are considered as suitable candidates. The ultrasonic telemetry is a technique used to constantly insure the safe functioning of reactor inner components by determining their exact position: it consists in measuring the time of flight of the ultrasonic response obtained after propagation of a pulse emitted by a transducer and its interaction with the targets. While in-service the sodium flow creates turbulences that lead to temperature inhomogeneities, which translates into ultrasonic velocity inhomogeneities. These velocity variations could directly impact the accuracy of the target locating by introducing time of flight variations. A stochastic simulation model has been developed to calculate the propagation of ultrasonic waves in such an inhomogeneous medium. Using this approach, the travel time is randomly generated by a stochastic process whose inputs are the statistical moments of travel times known analytically. The stochastic model predicts beam deviations due to velocity inhomogeneities, which are similar to those provided by a determinist method, such as the ray method.

SIMULATIONS OF LATERAL TRANSPORT AND DROPOUT STRUCTURE OF ENERGETIC PARTICLES FROM IMPULSIVE SOLAR FLARES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tooprakai, P.; Seripienlert, A.; Ruffolo, D.

2016-11-10

We simulate trajectories of energetic particles from impulsive solar flares for 2D+slab models of magnetic turbulence in spherical geometry to study dropout features, i.e., sharp, repeated changes in the particle density. Among random-phase realizations of two-dimensional (2D) turbulence, a spherical harmonic expansion can generate homogeneous turbulence over a sphere, but a 2D fast Fourier transform (FFT) locally mapped onto the lateral coordinates in the region of interest is much faster computationally, and we show that the results are qualitatively similar. We then use the 2D FFT field as input to a 2D MHD simulation, which dynamically generates realistic features ofmore » turbulence such as coherent structures. The magnetic field lines and particles spread non-diffusively (ballistically) to a patchy distribution reaching up to 25° from the injection longitude and latitude at r ∼ 1 au. This dropout pattern in field line trajectories has sharper features in the case of the more realistic 2D MHD model, in better qualitative agreement with observations. The initial dropout pattern in particle trajectories is relatively insensitive to particle energy, though the energy affects the pattern’s evolution with time. We make predictions for future observations of solar particles near the Sun (e.g., at 0.25 au), for which we expect a sharp pulse of outgoing particles along the dropout pattern, followed by backscattering that first remains close to the dropout pattern and later exhibits cross-field transport to a distribution that is more diffusive, yet mostly contained within the dropout pattern found at greater distances.« less

Statistical theory of dynamo

NASA Astrophysics Data System (ADS)

Kim, E.; Newton, A. P.

2012-04-01

One major problem in dynamo theory is the multi-scale nature of the MHD turbulence, which requires statistical theory in terms of probability distribution functions. In this contribution, we present the statistical theory of magnetic fields in a simplified mean field α-Ω dynamo model by varying the statistical property of alpha, including marginal stability and intermittency, and then utilize observational data of solar activity to fine-tune the mean field dynamo model. Specifically, we first present a comprehensive investigation into the effect of the stochastic parameters in a simplified α-Ω dynamo model. Through considering the manifold of marginal stability (the region of parameter space where the mean growth rate is zero), we show that stochastic fluctuations are conductive to dynamo. Furthermore, by considering the cases of fluctuating alpha that are periodic and Gaussian coloured random noise with identical characteristic time-scales and fluctuating amplitudes, we show that the transition to dynamo is significantly facilitated for stochastic alpha with random noise. Furthermore, we show that probability density functions (PDFs) of the growth-rate, magnetic field and magnetic energy can provide a wealth of useful information regarding the dynamo behaviour/intermittency. Finally, the precise statistical property of the dynamo such as temporal correlation and fluctuating amplitude is found to be dependent on the distribution the fluctuations of stochastic parameters. We then use observations of solar activity to constrain parameters relating to the effect in stochastic α-Ω nonlinear dynamo models. This is achieved through performing a comprehensive statistical comparison by computing PDFs of solar activity from observations and from our simulation of mean field dynamo model. The observational data that are used are the time history of solar activity inferred for C14 data in the past 11000 years on a long time scale and direct observations of the sun spot numbers obtained in recent years 1795-1995 on a short time scale. Monte Carlo simulations are performed on these data to obtain PDFs of the solar activity on both long and short time scales. These PDFs are then compared with predicted PDFs from numerical simulation of our α-Ω dynamo model, where α is assumed to have both mean α0 and fluctuating α' parts. By varying the correlation time of fluctuating α', the ratio of the amplitude of the fluctuating to mean alpha <α'2>/α02 (where angular brackets <> denote ensemble average), and the ratio of poloidal to toroidal magnetic fields, we show that the results from our stochastic dynamo model can match the PDFs of solar activity on both long and short time scales. In particular, a good agreement is obtained when the fluctuation in alpha is roughly equal to the mean part with a correlation time shorter than the solar period.

Surface roughness scattering of electrons in bulk mosfets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zuverink, Amanda Renee

2015-11-01

Surface-roughness scattering of electrons at the Si-SiO 2 interface is a very important consideration when analyzing Si metal-oxide-semiconductor field-effect transistors (MOSFETs). Scattering reduces the mobility of the electrons and degrades the device performance. 250-nm and 50-nm bulk MOSFETs were simulated with varying device parameters and mesh sizes in order to compare the effects of surface-roughness scattering in multiple devices. The simulation framework includes the ensemble Monte Carlo method used to solve the Boltzmann transport equation coupled with a successive over-relaxation method used to solve the two-dimensional Poisson's equation. Four methods for simulating the surface-roughness scattering of electrons were implemented onmore » both devices and compared: the constant specularity parameter, the momentum-dependent specularity parameter, and the real-space-roughness method with both uniform and varying electric fields. The specularity parameter is the probability of an electron scattering speculariy from a rough surface. It can be chosen as a constant, characterizing partially diffuse scattering of all electrons from the surface the same way, or it can be momentum dependent, where the size of rms roughness and the normal component of the electron wave number determine the probability of electron-momentum randomization. The real-space rough surface method uses the rms roughness height and correlation length of an actual MOSFET to simulate a rough interface. Due to their charge, electrons scatter from the electric field and not directly from the surface. If the electric field is kept uniform, the electrons do not perceive the roughness and scatter as if from a at surface. However, if the field is allowed to vary, the electrons scatter from the varying electric field as they would in a MOSFET. These methods were implemented for both the 50-nm and 250-nm MOSFETs, and using the rms roughness heights and correlation lengths for real devices. The current-voltage and mobility-electric field curves were plotted for each method on the two devices and compared. The conclusion is that the specularity-parameter methods are valuable as simple models for relatively smooth interfaces. However, they have limitations, as they cannot accurately describe the drastic reduction in the current and the electron mobility that occur in MOSFETs with very rough Si-SiO 2 interfaces.« less

Computed narrow-band azimuthal time-reversing array retrofocusing in shallow water.

PubMed

Dungan, M R; Dowling, D R

2001-10-01

The process of acoustic time reversal sends sound waves back to their point of origin in reciprocal acoustic environments even when the acoustic environment is unknown. The properties of the time-reversed field commonly depend on the frequency of the original signal, the characteristics of the acoustic environment, and the configuration of the time-reversing transducer array (TRA). In particular, vertical TRAs are predicted to produce horizontally confined foci in environments containing random volume refraction. This article validates and extends this prediction to shallow water environments via monochromatic Monte Carlo propagation simulations (based on parabolic equation computations using RAM). The computational results determine the azimuthal extent of a TRA's retrofocus in shallow-water sound channels either having random bottom roughness or containing random internal-wave-induced sound speed fluctuations. In both cases, randomness in the environment may reduce the predicted azimuthal angular width of the vertical TRA retrofocus to as little as several degrees (compared to 360 degrees for uniform environments) for source-array ranges from 5 to 20 km at frequencies from 500 Hz to 2 kHz. For both types of randomness, power law scalings are found to collapse the calculated azimuthal retrofocus widths for shallow sources over a variety of acoustic frequencies, source-array ranges, water column depths, and random fluctuation amplitudes and correlation scales. Comparisons are made between retrofocusing on shallow and deep sources, and in strongly and mildly absorbing environments.

Generating log-normal mock catalog of galaxies in redshift space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agrawal, Aniket; Makiya, Ryu; Saito, Shun

We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear biasmore » relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.« less

Safety assessment of a shallow foundation using the random finite element method

NASA Astrophysics Data System (ADS)

Zaskórski, Łukasz; Puła, Wojciech

2015-04-01

A complex structure of soil and its random character are reasons why soil modeling is a cumbersome task. Heterogeneity of soil has to be considered even within a homogenous layer of soil. Therefore an estimation of shear strength parameters of soil for the purposes of a geotechnical analysis causes many problems. In applicable standards (Eurocode 7) there is not presented any explicit method of an evaluation of characteristic values of soil parameters. Only general guidelines can be found how these values should be estimated. Hence many approaches of an assessment of characteristic values of soil parameters are presented in literature and can be applied in practice. In this paper, the reliability assessment of a shallow strip footing was conducted using a reliability index β. Therefore some approaches of an estimation of characteristic values of soil properties were compared by evaluating values of reliability index β which can be achieved by applying each of them. Method of Orr and Breysse, Duncan's method, Schneider's method, Schneider's method concerning influence of fluctuation scales and method included in Eurocode 7 were examined. Design values of the bearing capacity based on these approaches were referred to the stochastic bearing capacity estimated by the random finite element method (RFEM). Design values of the bearing capacity were conducted for various widths and depths of a foundation in conjunction with design approaches DA defined in Eurocode. RFEM was presented by Griffiths and Fenton (1993). It combines deterministic finite element method, random field theory and Monte Carlo simulations. Random field theory allows to consider a random character of soil parameters within a homogenous layer of soil. For this purpose a soil property is considered as a separate random variable in every element of a mesh in the finite element method with proper correlation structure between points of given area. RFEM was applied to estimate which theoretical probability distribution fits the empirical probability distribution of bearing capacity basing on 3000 realizations. Assessed probability distribution was applied to compute design values of the bearing capacity and related reliability indices β. Conducted analysis were carried out for a cohesion soil. Hence a friction angle and a cohesion were defined as a random parameters and characterized by two dimensional random fields. A friction angle was described by a bounded distribution as it differs within limited range. While a lognormal distribution was applied in case of a cohesion. Other properties - Young's modulus, Poisson's ratio and unit weight were assumed as deterministic values because they have negligible influence on the stochastic bearing capacity. Griffiths D. V., & Fenton G. A. (1993). Seepage beneath water retaining structures founded on spatially random soil. Géotechnique, 43(6), 577-587.

Seismic waveform tomography with shot-encoding using a restarted L-BFGS algorithm.

PubMed

Rao, Ying; Wang, Yanghua

2017-08-17

In seismic waveform tomography, or full-waveform inversion (FWI), one effective strategy used to reduce the computational cost is shot-encoding, which encodes all shots randomly and sums them into one super shot to significantly reduce the number of wavefield simulations in the inversion. However, this process will induce instability in the iterative inversion regardless of whether it uses a robust limited-memory BFGS (L-BFGS) algorithm. The restarted L-BFGS algorithm proposed here is both stable and efficient. This breakthrough ensures, for the first time, the applicability of advanced FWI methods to three-dimensional seismic field data. In a standard L-BFGS algorithm, if the shot-encoding remains unchanged, it will generate a crosstalk effect between different shots. This crosstalk effect can only be suppressed by employing sufficient randomness in the shot-encoding. Therefore, the implementation of the L-BFGS algorithm is restarted at every segment. Each segment consists of a number of iterations; the first few iterations use an invariant encoding, while the remainder use random re-coding. This restarted L-BFGS algorithm balances the computational efficiency of shot-encoding, the convergence stability of the L-BFGS algorithm, and the inversion quality characteristic of random encoding in FWI.

Continuous-Time Random Walk Models of DNA Electrophoresis in a Post Array: II. Mobility and Sources of Band Broadening

PubMed Central

Olson, Daniel W.; Dutta, Sarit; Laachi, Nabil; Tian, Mingwei; Dorfman, Kevin D.

2011-01-01

Using the two-state, continuous-time random walk model, we develop expressions for the mobility and the plate height during DNA electrophoresis in an ordered post array that delineate the contributions due to (i) the random distance between collisions and (ii) the random duration of a collision. These contributions are expressed in terms of the means and variances of the underlying stochastic processes, which we evaluate from a large ensemble of Brownian dynamics simulations performed using different electric fields and molecular weights in a hexagonal array of 1 μm posts with a 3 μm center-to-center distance. If we fix the molecular weight, we find that the collision frequency governs the mobility. In contrast, the average collision duration is the most important factor for predicting the mobility as a function of DNA size at constant Péclet number. The plate height is reasonably well-described by a single post rope-over-pulley model, provided that the extension of the molecule is small. Our results only account for dispersion inside the post array and thus represent a theoretical lower bound on the plate height in an actual device. PMID:21290387

A laboratory experiment assessing the effect of sea ice on wave dumping

NASA Astrophysics Data System (ADS)

Cavaliere, Claudio; Alberello, Alberto; Bennetts, Luke; Meylan, Mike; Babanin, Alexander; Malavasi, Stefano; Toffoli, Alessandro

2014-05-01

Wave-ice interaction is a critical factor in the dynamics of the marginal ice zone (MIZ), the region between open ocean and an expanse of ice floes of varying size and shape. This interaction works both ways: while waves cause the fractures of ice floes, the presence of ice floes affects waves through scattering and various dissipative processes. In order to assess the latter, a laboratory experiment has been carried out in the coastal directional basin at Plymouth University. Sea ice has been simulated with two deformable plates: 1mX1m plastic sheet with variable thickness of polypropylene, which holds the same density (~0.9 g/cm3) of ice, and PVC Forex, which hold the same mechanical property of ice. Experiments have been conducted using monochromatic as well as random wave fields with different steepness and wavelengths (both shorter and larger than the floe). The wave field has been monitored before and after the simulated ice floe with a number of wave probes deployed along the basin, including a 6-probe array to track directional properties. On the whole, results show a substantial scattering and dissipation of the wave field, which appears to be dependent on the amount of overwash on the ice floe.

A synthesis approach for reproducing the response of aircraft panels to a turbulent boundary layer excitation.

PubMed

Bravo, Teresa; Maury, Cédric

2011-01-01

Random wall-pressure fluctuations due to the turbulent boundary layer (TBL) are a feature of the air flow over an aircraft fuselage under cruise conditions, creating undesirable effects such as cabin noise annoyance. In order to test potential solutions to reduce the TBL-induced noise, a cost-efficient alternative to in-flight or wind-tunnel measurements involves the laboratory simulation of the response of aircraft sidewalls to high-speed subsonic TBL excitation. Previously published work has shown that TBL simulation using a near-field array of loudspeakers is only feasible in the low frequency range due to the rapid decay of the spanwise correlation length with frequency. This paper demonstrates through theoretical criteria how the wavenumber filtering capabilities of the radiating panel reduces the number of sources required, thus dramatically enlarging the frequency range over which the response of the TBL-excited panel is accurately reproduced. Experimental synthesis of the panel response to high-speed TBL excitation is found to be feasible over the hydrodynamic coincidence frequency range using a reduced set of near-field loudspeakers driven by optimal signals. Effective methodologies are proposed for an accurate reproduction of the TBL-induced sound power radiated by the panel into a free-field and when coupled to a cavity.

A Monte Carlo analysis of breast screening randomized trials.

PubMed

Zamora, Luis I; Forastero, Cristina; Guirado, Damián; Lallena, Antonio M

2016-12-01

To analyze breast screening randomized trials with a Monte Carlo simulation tool. A simulation tool previously developed to simulate breast screening programmes was adapted for that purpose. The history of women participating in the trials was simulated, including a model for survival after local treatment of invasive cancers. Distributions of time gained due to screening detection against symptomatic detection and the overall screening sensitivity were used as inputs. Several randomized controlled trials were simulated. Except for the age range of women involved, all simulations used the same population characteristics and this permitted to analyze their external validity. The relative risks obtained were compared to those quoted for the trials, whose internal validity was addressed by further investigating the reasons of the disagreements observed. The Monte Carlo simulations produce results that are in good agreement with most of the randomized trials analyzed, thus indicating their methodological quality and external validity. A reduction of the breast cancer mortality around 20% appears to be a reasonable value according to the results of the trials that are methodologically correct. Discrepancies observed with Canada I and II trials may be attributed to a low mammography quality and some methodological problems. Kopparberg trial appears to show a low methodological quality. Monte Carlo simulations are a powerful tool to investigate breast screening controlled randomized trials, helping to establish those whose results are reliable enough to be extrapolated to other populations and to design the trial strategies and, eventually, adapting them during their development. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Monte Carlo Simulation Using HyperCard and Lotus 1-2-3.

ERIC Educational Resources Information Center

Oulman, Charles S.; Lee, Motoko Y.

Monte Carlo simulation is a computer modeling procedure for mimicking observations on a random variable. A random number generator is used in generating the outcome for the events that are being modeled. The simulation can be used to obtain results that otherwise require extensive testing or complicated computations. This paper describes how Monte…

Examination of ductile spall failure through direct numerical simulation

NASA Astrophysics Data System (ADS)

Becker, Richard

2017-06-01

Direct numerical simulation is used to examine the growth and coalescence of a random population of voids leading to spall failure. Void nucleating particles are explicitly represented in the initial geometry, and the arbitrary Lagrange-Eulerian finite element code tracks the void evolution to create the spall surface. The flow fields capture strain localization associated with void interaction at low porosities and ligament necking at final coalescence. Simulations are run to assess the influence of material strain hardening and strain rate sensitivity on void growth and coalescence. These analyses also provide the evolution of longitudinal stress and the energy dissipated, and they reveal a length scale associated with the spall. Additional calculations are performed to examine the influence of loading pulse shape on spall behavior for triangular shaped pressure loading. A dependence of spall scab thickness on pulse shape is determined. These results show localization delayed until porosities reach a few percent and they demonstrate a consistent stress versus porosity relation. The simulations also provide a direct correlation between the spall stress history and the free surface velocity, which can aid in understanding stress corrections applied to experimental data.

Using sequential self-calibration method to identify conductivity distribution: Conditioning on tracer test data

USGS Publications Warehouse

Hu, B.X.; He, C.

2008-01-01

An iterative inverse method, the sequential self-calibration method, is developed for mapping spatial distribution of a hydraulic conductivity field by conditioning on nonreactive tracer breakthrough curves. A streamline-based, semi-analytical simulator is adopted to simulate solute transport in a heterogeneous aquifer. The simulation is used as the forward modeling step. In this study, the hydraulic conductivity is assumed to be a deterministic or random variable. Within the framework of the streamline-based simulator, the efficient semi-analytical method is used to calculate sensitivity coefficients of the solute concentration with respect to the hydraulic conductivity variation. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by two synthetic tracer tests conducted in an aquifer with a distinct spatial pattern of heterogeneity. The study results indicate that the developed iterative inverse method is able to identify and reproduce the large-scale heterogeneity pattern of the aquifer given appropriate observation wells in these synthetic cases. ?? International Association for Mathematical Geology 2008.

Modeling 2D and 3D diffusion.

PubMed

Saxton, Michael J

2007-01-01

Modeling obstructed diffusion is essential to the understanding of diffusion-mediated processes in the crowded cellular environment. Simple Monte Carlo techniques for modeling obstructed random walks are explained and related to Brownian dynamics and more complicated Monte Carlo methods. Random number generation is reviewed in the context of random walk simulations. Programming techniques and event-driven algorithms are discussed as ways to speed simulations.

On Pfaffian Random Point Fields

NASA Astrophysics Data System (ADS)

Kargin, V.

2014-02-01

We study Pfaffian random point fields by using the Moore-Dyson quaternion determinants. First, we give sufficient conditions that ensure that a self-dual quaternion kernel defines a valid random point field, and then we prove a CLT for Pfaffian point fields. The proofs are based on a new quaternion extension of the Cauchy-Binet determinantal identity. In addition, we derive the Fredholm determinantal formulas for the Pfaffian point fields which use the quaternion determinant.

Optimization of planar PIV-based pressure estimates in laminar and turbulent wakes

NASA Astrophysics Data System (ADS)

McClure, Jeffrey; Yarusevych, Serhiy

2017-05-01

The performance of four pressure estimation techniques using Eulerian material acceleration estimates from planar, two-component Particle Image Velocimetry (PIV) data were evaluated in a bluff body wake. To allow for the ground truth comparison of the pressure estimates, direct numerical simulations of flow over a circular cylinder were used to obtain synthetic velocity fields. Direct numerical simulations were performed for Re_D = 100, 300, and 1575, spanning laminar, transitional, and turbulent wake regimes, respectively. A parametric study encompassing a range of temporal and spatial resolutions was performed for each Re_D. The effect of random noise typical of experimental velocity measurements was also evaluated. The results identified optimal temporal and spatial resolutions that minimize the propagation of random and truncation errors to the pressure field estimates. A model derived from linear error propagation through the material acceleration central difference estimators was developed to predict these optima, and showed good agreement with the results from common pressure estimation techniques. The results of the model are also shown to provide acceptable first-order approximations for sampling parameters that reduce error propagation when Lagrangian estimations of material acceleration are employed. For pressure integration based on planar PIV, the effect of flow three-dimensionality was also quantified, and shown to be most pronounced at higher Reynolds numbers downstream of the vortex formation region, where dominant vortices undergo substantial three-dimensional deformations. The results of the present study provide a priori recommendations for the use of pressure estimation techniques from experimental PIV measurements in vortex dominated laminar and turbulent wake flows.

Tailpulse signal generator

DOEpatents

Baker, John [Walnut Creek, CA; Archer, Daniel E [Knoxville, TN; Luke, Stanley John [Pleasanton, CA; Decman, Daniel J [Livermore, CA; White, Gregory K [Livermore, CA

2009-06-23

A tailpulse signal generating/simulating apparatus, system, and method designed to produce electronic pulses which simulate tailpulses produced by a gamma radiation detector, including the pileup effect caused by the characteristic exponential decay of the detector pulses, and the random Poisson distribution pulse timing for radioactive materials. A digital signal process (DSP) is programmed and configured to produce digital values corresponding to pseudo-randomly selected pulse amplitudes and pseudo-randomly selected Poisson timing intervals of the tailpulses. Pulse amplitude values are exponentially decayed while outputting the digital value to a digital to analog converter (DAC). And pulse amplitudes of new pulses are added to decaying pulses to simulate the pileup effect for enhanced realism in the simulation.

Impact of Increased Football Field Width on Player High-Speed Collision Rate.

PubMed

Joseph, Jacob R; Khalsa, Siri S; Smith, Brandon W; Park, Paul

2017-07-01

High-acceleration head impact is a known risk for mild traumatic brain injury (mTBI) based on studies using helmet accelerometry. In football, offensive and defensive players are at higher risk of mTBI due to increased speed of play. Other collision sport studies suggest that increased playing surface size may contribute to reductions in high-speed collisions. We hypothesized that wider football fields lead to a decreased rate of high-speed collisions. Computer football game simulation was developed using MATLAB. Four wide receivers were matched against 7 defensive players. Each offensive player was randomized to one of 5 typical routes on each play. The ball was thrown 3 seconds into play; ball flight time was 2 seconds. Defensive players were delayed 0.5 second before reacting to ball release. A high-speed collision was defined as the receiver converging with a defensive player within 0.5 second of catching the ball. The simulation counted high-speed collisions for 1 team/season (65 plays/game for 16 games/season = 1040 plays/season) averaged during 10 seasons, and was validated against existing data using standard field width (53.3 yards). Field width was increased in 1-yard intervals up to 58.3 yards. Using standard field width, 188 ± 4 high-speed collisions were seen per team per season (18% of plays). When field width increased by 3 yards, high-speed collision rate decreased to 135 ± 3 per team per season (28% decrease; P < 0.0001). Even small increases in football field width can lead to substantial decline in high-speed collisions, with potential for reducing instances of mTBI in football players. Copyright © 2017 Elsevier Inc. All rights reserved.

Adaptive near-field beamforming techniques for sound source imaging.

PubMed

Cho, Yong Thung; Roan, Michael J

2009-02-01

Phased array signal processing techniques such as beamforming have a long history in applications such as sonar for detection and localization of far-field sound sources. Two sometimes competing challenges arise in any type of spatial processing; these are to minimize contributions from directions other than the look direction and minimize the width of the main lobe. To tackle this problem a large body of work has been devoted to the development of adaptive procedures that attempt to minimize side lobe contributions to the spatial processor output. In this paper, two adaptive beamforming procedures-minimum variance distorsionless response and weight optimization to minimize maximum side lobes--are modified for use in source visualization applications to estimate beamforming pressure and intensity using near-field pressure measurements. These adaptive techniques are compared to a fixed near-field focusing technique (both techniques use near-field beamforming weightings focusing at source locations estimated based on spherical wave array manifold vectors with spatial windows). Sound source resolution accuracies of near-field imaging procedures with different weighting strategies are compared using numerical simulations both in anechoic and reverberant environments with random measurement noise. Also, experimental results are given for near-field sound pressure measurements of an enclosed loudspeaker.

Structure of receptive fields in a computational model of area 3b of primary sensory cortex.

PubMed

Detorakis, Georgios Is; Rougier, Nicolas P

2014-01-01

In a previous work, we introduced a computational model of area 3b which is built upon the neural field theory and receives input from a simplified model of the index distal finger pad populated by a random set of touch receptors (Merkell cells). This model has been shown to be able to self-organize following the random stimulation of the finger pad model and to cope, to some extent, with cortical or skin lesions. The main hypothesis of the model is that learning of skin representations occurs at the thalamo-cortical level while cortico-cortical connections serve a stereotyped competition mechanism that shapes the receptive fields. To further assess this hypothesis and the validity of the model, we reproduced in this article the exact experimental protocol of DiCarlo et al. that has been used to examine the structure of receptive fields in area 3b of the primary somatosensory cortex. Using the same analysis toolset, the model yields consistent results, having most of the receptive fields to contain a single region of excitation and one to several regions of inhibition. We further proceeded our study using a dynamic competition that deeply influences the formation of the receptive fields. We hypothesized this dynamic competition to correspond to some form of somatosensory attention that may help to precisely shape the receptive fields. To test this hypothesis, we designed a protocol where an arbitrary region of interest is delineated on the index distal finger pad and we either (1) instructed explicitly the model to attend to this region (simulating an attentional signal) (2) preferentially trained the model on this region or (3) combined the two aforementioned protocols simultaneously. Results tend to confirm that dynamic competition leads to shrunken receptive fields and its joint interaction with intensive training promotes a massive receptive fields migration and shrinkage.

A brief introduction to computer-intensive methods, with a view towards applications in spatial statistics and stereology.

PubMed

Mattfeldt, Torsten

2011-04-01

Computer-intensive methods may be defined as data analytical procedures involving a huge number of highly repetitive computations. We mention resampling methods with replacement (bootstrap methods), resampling methods without replacement (randomization tests) and simulation methods. The resampling methods are based on simple and robust principles and are largely free from distributional assumptions. Bootstrap methods may be used to compute confidence intervals for a scalar model parameter and for summary statistics from replicated planar point patterns, and for significance tests. For some simple models of planar point processes, point patterns can be simulated by elementary Monte Carlo methods. The simulation of models with more complex interaction properties usually requires more advanced computing methods. In this context, we mention simulation of Gibbs processes with Markov chain Monte Carlo methods using the Metropolis-Hastings algorithm. An alternative to simulations on the basis of a parametric model consists of stochastic reconstruction methods. The basic ideas behind the methods are briefly reviewed and illustrated by simple worked examples in order to encourage novices in the field to use computer-intensive methods. © 2010 The Authors Journal of Microscopy © 2010 Royal Microscopical Society.

Simulation of angular-resolved RABBITT measurements in noble-gas atoms

NASA Astrophysics Data System (ADS)

Bray, Alexander W.; Naseem, Faiza; Kheifets, Anatoli S.

2018-06-01

We simulate angular-resolved RABBITT (reconstruction of attosecond beating by interference of two-photon transitions) measurements on valence shells of noble-gas atoms (Ne, Ar, Kr, and Xe). Our nonperturbative numerical simulation is based on solution of the time-dependent Schrödinger equation (TDSE) for a target atom driven by an ionizing XUV and dressing IR fields. From these simulations we extract the angular-dependent magnitude and phase of the RABBITT oscillations and deduce the corresponding angular anisotropy β parameter and Wigner time delay τW for the single XUV photon absorption that initiates the RABBITT process. Said β and τW parameters are compared with calculations in the random-phase approximation with exchange (RPAE), which includes intershell correlation. This comparison is used to test various effective potentials employed in the one-electron TDSE. In lighter atoms (Ne and Ar), several effective potentials are found to provide accurate simulations of RABBITT measurements for a wide range of photon energies up to 100 eV above the valence-shell threshold. In heavier atoms (Kr and Xe), the onset of strong correlation with the d shell restricts the validity of the single active electron approximation to several tens of eV above the valence-shell threshold.

Persistence in a Random Bond Ising Model of Socio-Econo Dynamics

NASA Astrophysics Data System (ADS)

Jain, S.; Yamano, T.

We study the persistence phenomenon in a socio-econo dynamics model using computer simulations at a finite temperature on hypercubic lattices in dimensions up to five. The model includes a "social" local field which contains the magnetization at time t. The nearest neighbour quenched interactions are drawn from a binary distribution which is a function of the bond concentration, p. The decay of the persistence probability in the model depends on both the spatial dimension and p. We find no evidence of "blocking" in this model. We also discuss the implications of our results for possible applications in the social and economic fields. It is suggested that the absence, or otherwise, of blocking could be used as a criterion to decide on the validity of a given model in different scenarios.

Magnetocapacitance without magnetism

PubMed Central

Parish, Meera M.

2014-01-01

A substantial magnetodielectric effect is often an indication of coupled magnetic and elastic order, such as is found in the multi-ferroics. However, it has recently been shown that magnetism is not necessary to produce either a magnetoresistance or a magnetocapacitance when the material is inhomogeneous. Here, we will investigate the characteristic magnetic-field-dependent dielectric response of such an inhomogeneous system using exact calculations and numerical simulations of conductor–dielectric composites. In particular, we will show that even simple conductor–dielectric layers exhibit a magneto-capacitance, and thus random bulk inhomogeneities are not a requirement for this effect. Indeed, this work essentially provides a natural generalization of the Maxwell–Wagner effect to finite magnetic field. We will also discuss how this phenomenon has already been observed experimentally in some materials. PMID:24421378

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gottwald, M.; Kan, J. J.; Lee, K.

Thermal budget, stack thickness, and dipolar offset field control are crucial for seamless integration of perpendicular magnetic junctions (pMTJ) into semiconductor integrated circuits to build scalable spin-transfer-torque magnetoresistive random access memory. This paper is concerned with materials and process tuning to deliver thermally robust (400 °C, 30 min) and thin (i.e., fewer layers and integration-friendly) pMTJ utilizing Co/Pt-based bottom pinned layers. Interlayer roughness control is identified as a key enabler to achieve high thermal budgets. The dipolar offset fields of the developed film stacks at scaled dimensions are evaluated by micromagnetic simulations. This paper shows a path towards achieving sub-15 nm-thick pMTJ withmore » tunneling magnetoresistance ratio higher than 150% after 30 min of thermal excursion at 400 °C.« less

Structure and Dynamics of the Solar Corona

NASA Technical Reports Server (NTRS)

Schnack, D. D.

1994-01-01

Advanced computational techniques were used to study solar coronal heating and coronal mass ejections. A three dimensional, time dependent resistive magnetohydrodynamic code was used to study the dynamic response of a model corona to continuous, slow, random magnetic footpoint displacements in the photosphere. Three dimensional numerical simulations of the response of the corona to simple smooth braiding flows in the photosphere were calculated to illustrate and understand the spontaneous formation of current filaments. Two dimensional steady state helmet streamer configurations were obtained by determining the time asymptotic state of the interaction of an initially one dimensinal transponic solar wind with a spherical potential dipole field. The disruption of the steady state helmet streamer configuration was studied as a response to shearing of the magnetic footpoints of the closed field lines under the helmet.

Hexagonal boron nitride and water interaction parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Yanbin; Aluru, Narayana R., E-mail: aluru@illinois.edu; Wagner, Lucas K.

2016-04-28

The study of hexagonal boron nitride (hBN) in microfluidic and nanofluidic applications at the atomic level requires accurate force field parameters to describe the water-hBN interaction. In this work, we begin with benchmark quality first principles quantum Monte Carlo calculations on the interaction energy between water and hBN, which are used to validate random phase approximation (RPA) calculations. We then proceed with RPA to derive force field parameters, which are used to simulate water contact angle on bulk hBN, attaining a value within the experimental uncertainties. This paper demonstrates that end-to-end multiscale modeling, starting at detailed many-body quantum mechanics andmore » ending with macroscopic properties, with the approximations controlled along the way, is feasible for these systems.« less

Robust criticality of an Ising model on rewired directed networks

NASA Astrophysics Data System (ADS)

Lipowski, Adam; Gontarek, Krzysztof; Lipowska, Dorota

2015-06-01

We show that preferential rewiring, which is supposed to mimic the behavior of financial agents, changes a directed-network Ising ferromagnet with a single critical point into a model with robust critical behavior. For the nonrewired random graph version, due to a constant number of out-links for each site, we write a simple mean-field-like equation describing the behavior of magnetization; we argue that it is exact and support the claim with extensive Monte Carlo simulations. For the rewired version, this equation is obeyed only at low temperatures. At higher temperatures, rewiring leads to strong heterogeneities, which apparently invalidates mean-field arguments and induces large fluctuations and divergent susceptibility. Such behavior is traced back to the formation of a relatively small core of agents that influence the entire system.

Variability and reliability analysis in self-assembled multichannel carbon nanotube field-effect transistors

NASA Astrophysics Data System (ADS)

Hu, Zhaoying; Tulevski, George S.; Hannon, James B.; Afzali, Ali; Liehr, Michael; Park, Hongsik

2015-06-01

Carbon nanotubes (CNTs) have been widely studied as a channel material of scaled transistors for high-speed and low-power logic applications. In order to have sufficient drive current, it is widely assumed that CNT-based logic devices will have multiple CNTs in each channel. Understanding the effects of the number of CNTs on device performance can aid in the design of CNT field-effect transistors (CNTFETs). We have fabricated multi-CNT-channel CNTFETs with an 80-nm channel length using precise self-assembly methods. We describe compact statistical models and Monte Carlo simulations to analyze failure probability and the variability of the on-state current and threshold voltage. The results show that multichannel CNTFETs are more resilient to process variation and random environmental fluctuations than single-CNT devices.

Anomalous diffusion in the evolution of soccer championship scores: Real data, mean-field analysis, and an agent-based model

NASA Astrophysics Data System (ADS)

da Silva, Roberto; Vainstein, Mendeli H.; Gonçalves, Sebastián; Paula, Felipe S. F.

2013-08-01

Statistics of soccer tournament scores based on the double round robin system of several countries are studied. Exploring the dynamics of team scoring during tournament seasons from recent years we find evidences of superdiffusion. A mean-field analysis results in a drift velocity equal to that of real data but in a different diffusion coefficient. Along with the analysis of real data we present the results of simulations of soccer tournaments obtained by an agent-based model which successfully describes the final scoring distribution [da Silva , Comput. Phys. Commun.CPHCBZ0010-465510.1016/j.cpc.2012.10.030 184, 661 (2013)]. Such model yields random walks of scores over time with the same anomalous diffusion as observed in real data.

Probing the gravitational Faraday rotation using quasar X-ray microlensing.

PubMed

Chen, Bin

2015-11-17

The effect of gravitational Faraday rotation was predicted in the 1950s, but there is currently no practical method for measuring this effect. Measuring this effect is important because it will provide new evidence for correctness of general relativity, in particular, in the strong field limit. We predict that the observed degree and angle of the X-ray polarization of a cosmologically distant quasar microlensed by the random star field in a foreground galaxy or cluster lens vary rapidly and concurrently with flux during caustic-crossing events using the first simulation of quasar X-ray microlensing polarization light curves. Therefore, it is possible to detect gravitational Faraday rotation by monitoring the X-ray polarization of gravitationally microlensed quasars. Detecting this effect will also confirm the strong gravity nature of quasar X-ray emission.

Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heasler, Patrick G.

This report develops a random field model that describes gas plumes in LWIR remote sensing images. The random field model serves as a prior distribution that can be combined with LWIR data to produce a posterior that determines the probability that a gas plume exists in the scene and also maps the most probable location of any plume. The random field model is intended to work with a single pixel regression estimator--a regression model that estimates gas concentration on an individual pixel basis.

Tensor Minkowski Functionals for random fields on the sphere

NASA Astrophysics Data System (ADS)

Chingangbam, Pravabati; Yogendran, K. P.; Joby, P. K.; Ganesan, Vidhya; Appleby, Stephen; Park, Changbom

2017-12-01

We generalize the translation invariant tensor-valued Minkowski Functionals which are defined on two-dimensional flat space to the unit sphere. We apply them to level sets of random fields. The contours enclosing boundaries of level sets of random fields give a spatial distribution of random smooth closed curves. We outline a method to compute the tensor-valued Minkowski Functionals numerically for any random field on the sphere. Then we obtain analytic expressions for the ensemble expectation values of the matrix elements for isotropic Gaussian and Rayleigh fields. The results hold on flat as well as any curved space with affine connection. We elucidate the way in which the matrix elements encode information about the Gaussian nature and statistical isotropy (or departure from isotropy) of the field. Finally, we apply the method to maps of the Galactic foreground emissions from the 2015 PLANCK data and demonstrate their high level of statistical anisotropy and departure from Gaussianity.

A study of MRI gradient echo signals from discrete magnetic particles with considerations of several parameters in simulations.

PubMed

Kokeny, Paul; Cheng, Yu-Chung N; Xie, He

2018-05-01

Modeling MRI signal behaviors in the presence of discrete magnetic particles is important, as magnetic particles appear in nanoparticle labeled cells, contrast agents, and other biological forms of iron. Currently, many models that take into account the discrete particle nature in a system have been used to predict magnitude signal decays in the form of R2* or R2' from one single voxel. Little work has been done for predicting phase signals. In addition, most calculations of phase signals rely on the assumption that a system containing discrete particles behaves as a continuous medium. In this work, numerical simulations are used to investigate MRI magnitude and phase signals from discrete particles, without diffusion effects. Factors such as particle size, number density, susceptibility, volume fraction, particle arrangements for their randomness, and field of view have been considered in simulations. The results are compared to either a ground truth model, theoretical work based on continuous mediums, or previous literature. Suitable parameters used to model particles in several voxels that lead to acceptable magnetic field distributions around particle surfaces and accurate MR signals are identified. The phase values as a function of echo time from a central voxel filled by particles can be significantly different from those of a continuous cubic medium. However, a completely random distribution of particles can lead to an R2' value which agrees with the prediction from the static dephasing theory. A sphere with a radius of at least 4 grid points used in simulations is found to be acceptable to generate MR signals equivalent from a larger sphere. Increasing number of particles with a fixed volume fraction in simulations reduces the resulting variance in the phase behavior, and converges to almost the same phase value for different particle numbers at each echo time. The variance of phase values is also reduced when increasing the number of particles in a fixed voxel. These results indicate that MRI signals from voxels containing discrete particles, even with a sufficient number of particles per voxel, cannot be properly modeled by a continuous medium with an equivalent susceptibility value in the voxel. Copyright © 2017 Elsevier Inc. All rights reserved.

Simulating Realistic Test Data for the European Lightning Imager on MTG using Data from Seviri, TRMM-LIS and ISS-LIS

NASA Astrophysics Data System (ADS)

Finke, U.; Blakeslee, R. J.; Mach, D. M.

2017-12-01

The next generation of European geostationary weather observing satellites (MTG) will operate an optical lightning location instrument (LI) which will be very similar to the Global Lightning Mapper (GLM) on board of GOES-R. For the development and verification of the product processing algorithms realistic test data are necessary. This paper presents a method of test data generation on the basis of optical lightning data from the LIS instrument and cloud image data from the Seviri radiometer.The basis is the lightning data gathered during the 15 year LIS operation time, particularly the empirical distribution functions of the optical pulse size, duration and radiance as well as the inter-correlation of lightning in space and time. These allow for a realistically structured simulation of lightning test data. Due to its low orbit the instantaneous field of view of the LIS is limited and moving with time. For the generation of test data which cover the geostationary visible disk, the LIS data have to be extended. This is realized by 1. simulating random lightning pulses according to the established distribution functions of the lightning parameters and 2. using the cloud radiometer data of the Seviri instrument on board of the geostationary Meteosat second generation (MSG). Particularly, the cloud top height product (CTH) identifies convective storm clouds wherein the simulation places random lightning pulses. The LIS instrument was recently deployed on the International Space Station (ISS). The ISS orbit reaches higher latitudes, particularly Europe. The ISS-LIS data is analyzed for single observation days. Additionally, the statistical distribution of parameters such as radiance, footprint size, and space time correlation of the groups are compared against the long time statistics from TRMM-LIS.Optical lightning detection efficiency from space is affected by the solar radiation reflected from the clouds. This effect is changing with day and night areas across the field of view. For a realistic simulation of this cloud background radiance the Seviri visual channel VIS08 data is used.Additionally to the test data study, this paper gives a comparison of the MTG-LI to the GLM and discusses differences in instrument design, product definition and generation and the merging of data from both geostationary instruments.

Spectral Indices in Simulations of Imbalanced Magnetohydrodynamic Turbulence

NASA Astrophysics Data System (ADS)

Ng, C. S.; Dennis, T. J.

2017-12-01

Three-dimensional (3D) simulations of imbalanced magnetohydrodynamic (MHD) turbulence based on reduced MHD equations have been performed. Alfven waves are launched from both ends of a long tube along the background uniform magnetic field so that turbulence develops due to collision between counter propagating Alfven waves in the interior region. Waves are launched randomly with specified correlation time Tc such that the length of the tube, L, is greater than (but of the same order of) VA Tc such that turbulence can fill most of the tube. While waves at both ends are launched with equal power, turbulence generated is imbalanced in general, with normalized cross-helicity gets close to -1 at one end and 1 at the other end. One fundamental unresolved problem in the theory of imbalanced turbulence is how turbulence spectral indices depend on the normalized cross-helicity. We will present turbulence spectral indices found in our latest simulations and discuss theoretical implications. This work is supported by a NASA grant NNX15AU61G.

New three-dimensional modeling technique for studying porous media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quiblier, J.A.

A great deal of research has been done on the relationships between the structure of porous media on the microscopic level and their overall properties. A short bibliographic survey is attempted, with special attention being paid to the use of models. The limitations of such research are outlined. A three-dimensional simulation process is proposed. On the basis of measurements of characteristics using thin sections of porous media, the aim is to simulate, through a random process, a porous medium which is at the same time geometrically realistic and fully determined (i.e., the coordinates of a point in the medium fullymore » determine whether this point belongs to the matrix or to the pores). Simulation opens the way to further studies of the porous medium, some of which are outlined. It is clear that a good deal of research remains to be done in this field, and some ideas are suggested for this research. 78 references.« less

A random distribution reacting mixing layer model

NASA Technical Reports Server (NTRS)

Jones, Richard A.; Marek, C. John; Myrabo, Leik N.; Nagamatsu, Henry T.

1994-01-01

A methodology for simulation of molecular mixing, and the resulting velocity and temperature fields has been developed. The ideas are applied to the flow conditions present in the NASA Lewis Research Center Planar Reacting Shear Layer (PRSL) facility, and results compared to experimental data. A gaussian transverse turbulent velocity distribution is used in conjunction with a linearly increasing time scale to describe the mixing of different regions of the flow. Equilibrium reaction calculations are then performed on the mix to arrive at a new species composition and temperature. Velocities are determined through summation of momentum contributions. The analysis indicates a combustion efficiency of the order of 80 percent for the reacting mixing layer, and a turbulent Schmidt number of 2/3. The success of the model is attributed to the simulation of large-scale transport of fluid. The favorable comparison shows that a relatively quick and simple PC calculation is capable of simulating the basic flow structure in the reacting and nonreacting shear layer present in the facility given basic assumptions about turbulence properties.

Correlations induced by depressing synapses in critically self-organized networks with quenched dynamics

NASA Astrophysics Data System (ADS)

Campos, João Guilherme Ferreira; Costa, Ariadne de Andrade; Copelli, Mauro; Kinouchi, Osame

2017-04-01

In a recent work, mean-field analysis and computer simulations were employed to analyze critical self-organization in networks of excitable cellular automata where randomly chosen synapses in the network were depressed after each spike (the so-called annealed dynamics). Calculations agree with simulations of the annealed version, showing that the nominal branching ratio σ converges to unity in the thermodynamic limit, as expected of a self-organized critical system. However, the question remains whether the same results apply to the biological case where only the synapses of firing neurons are depressed (the so-called quenched dynamics). We show that simulations of the quenched model yield significant deviations from σ =1 due to spatial correlations. However, the model is shown to be critical, as the largest eigenvalue of the synaptic matrix approaches unity in the thermodynamic limit, that is, λc=1 . We also study the finite size effects near the critical state as a function of the parameters of the synaptic dynamics.

Coarse-Grained Simulations of Membrane Insertion and Folding of Small Helical Proteins Using the CABS Model.

PubMed

Pulawski, Wojciech; Jamroz, Michal; Kolinski, Michal; Kolinski, Andrzej; Kmiecik, Sebastian

2016-11-28

The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics, and interactions). Here we introduce an extension of the CABS representation and force field (CABS-membrane) to the modeling of the effect of the biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to the all-atom representation and all-atom scoring. The CABS-membrane model is a promising approach for further development toward modeling of large protein-membrane systems.

Simulations of the Richtmyer-Meshkov Instability with experimentally measured volumetric initial conditions

NASA Astrophysics Data System (ADS)

Ferguson, Kevin; Sewell, Everest; Krivets, Vitaliy; Greenough, Jeffrey; Jacobs, Jeffrey

2016-11-01

Initial conditions for the Richtmyer-Meshkov instability (RMI) are measured in three dimensions in the University of Arizona Vertical Shock Tube using a moving magnet galvanometer system. The resulting volumetric data is used as initial conditions for the simulation of the RMI using ARES at Lawrence-Livermore National Laboratory (LLNL). The heavy gas is sulfur hexafluoride (SF6), and the light gas is air. The perturbations are generated by harmonically oscillating the gasses vertically using two loudspeakers mounted to the shock tube which cause Faraday resonance, producing a random short wavelength perturbation on the interface. Planar Mie scattering is used to illuminate the flow field through the addition of propylene glycol particles seeded in the heavy gas. An M=1.2 shock impulsively accelerates the interface, initiating instability growth. Images of the initial condition and instability growth are captured at a rate of 6 kHz using high speed cameras. Comparisons between experimental and simulation results, mixing diagnostics, and mixing zone growth are presented.

Fast Quantum Algorithm for Predicting Descriptive Statistics of Stochastic Processes

NASA Technical Reports Server (NTRS)

Williams Colin P.

1999-01-01

Stochastic processes are used as a modeling tool in several sub-fields of physics, biology, and finance. Analytic understanding of the long term behavior of such processes is only tractable for very simple types of stochastic processes such as Markovian processes. However, in real world applications more complex stochastic processes often arise. In physics, the complicating factor might be nonlinearities; in biology it might be memory effects; and in finance is might be the non-random intentional behavior of participants in a market. In the absence of analytic insight, one is forced to understand these more complex stochastic processes via numerical simulation techniques. In this paper we present a quantum algorithm for performing such simulations. In particular, we show how a quantum algorithm can predict arbitrary descriptive statistics (moments) of N-step stochastic processes in just O(square root of N) time. That is, the quantum complexity is the square root of the classical complexity for performing such simulations. This is a significant speedup in comparison to the current state of the art.

Computer simulation of random variables and vectors with arbitrary probability distribution laws

NASA Technical Reports Server (NTRS)

Bogdan, V. M.

1981-01-01

Assume that there is given an arbitrary n-dimensional probability distribution F. A recursive construction is found for a sequence of functions x sub 1 = f sub 1 (U sub 1, ..., U sub n), ..., x sub n = f sub n (U sub 1, ..., U sub n) such that if U sub 1, ..., U sub n are independent random variables having uniform distribution over the open interval (0,1), then the joint distribution of the variables x sub 1, ..., x sub n coincides with the distribution F. Since uniform independent random variables can be well simulated by means of a computer, this result allows one to simulate arbitrary n-random variables if their joint probability distribution is known.

Generation of dense granular deposits for porosity analysis: assessment and application of large-scale non-smooth granular dynamics

NASA Astrophysics Data System (ADS)

Schruff, T.; Liang, R.; Rüde, U.; Schüttrumpf, H.; Frings, R. M.

2018-01-01

The knowledge of structural properties of granular materials such as porosity is highly important in many application-oriented and scientific fields. In this paper we present new results of computer-based packing simulations where we use the non-smooth granular dynamics (NSGD) method to simulate gravitational random dense packing of spherical particles with various particle size distributions and two types of depositional conditions. A bin packing scenario was used to compare simulation results to laboratory porosity measurements and to quantify the sensitivity of the NSGD regarding critical simulation parameters such as time step size. The results of the bin packing simulations agree well with laboratory measurements across all particle size distributions with all absolute errors below 1%. A large-scale packing scenario with periodic side walls was used to simulate the packing of up to 855,600 spherical particles with various particle size distributions (PSD). Simulation outcomes are used to quantify the effect of particle-domain-size ratio on the packing compaction. A simple correction model, based on the coordination number, is employed to compensate for this effect on the porosity and to determine the relationship between PSD and porosity. Promising accuracy and stability results paired with excellent computational performance recommend the application of NSGD for large-scale packing simulations, e.g. to further enhance the generation of representative granular deposits.

Similarities between principal components of protein dynamics and random diffusion

NASA Astrophysics Data System (ADS)

Hess, Berk

2000-12-01

Principal component analysis, also called essential dynamics, is a powerful tool for finding global, correlated motions in atomic simulations of macromolecules. It has become an established technique for analyzing molecular dynamics simulations of proteins. The first few principal components of simulations of large proteins often resemble cosines. We derive the principal components for high-dimensional random diffusion, which are almost perfect cosines. This resemblance between protein simulations and noise implies that for many proteins the time scales of current simulations are too short to obtain convergence of collective motions.

Effect of increasing disorder on domains of the 2d Coulomb glass.

PubMed

Bhandari, Preeti; Malik, Vikas

2017-12-06

We have studied a two dimensional lattice model of Coulomb glass for a wide range of disorders at [Formula: see text]. The system was first annealed using Monte Carlo simulation. Further minimization of the total energy of the system was done using an algorithm developed by Baranovskii et al, followed by cluster flipping to obtain the pseudo-ground states. We have shown that the energy required to create a domain of linear size L in d dimensions is proportional to [Formula: see text]. Using Imry-Ma arguments given for random field Ising model, one gets critical dimension [Formula: see text] for Coulomb glass. The investigation of domains in the transition region shows a discontinuity in staggered magnetization which is an indication of a first-order type transition from charge-ordered phase to disordered phase. The structure and nature of random field fluctuations of the second largest domain in Coulomb glass are inconsistent with the assumptions of Imry and Ma, as was also reported for random field Ising model. The study of domains showed that in the transition region there were mostly two large domains, and that as disorder was increased the two large domains remained, but a large number of small domains also opened up. We have also studied the properties of the second largest domain as a function of disorder. We furthermore analysed the effect of disorder on the density of states, and showed a transition from hard gap at low disorders to a soft gap at higher disorders. At [Formula: see text], we have analysed the soft gap in detail, and found that the density of states deviates slightly ([Formula: see text]) from the linear behaviour in two dimensions. Analysis of local minima show that the pseudo-ground states have similar structure.

Building a virtual simulation platform for quasistatic breast ultrasound elastography using open source software: A preliminary investigation

PubMed Central

Wang, Yu; Helminen, Emily; Jiang, Jingfeng

2015-01-01

Purpose: Quasistatic ultrasound elastography (QUE) is being used to augment in vivo characterization of breast lesions. Results from early clinical trials indicated that there was a lack of confidence in image interpretation. Such confidence can only be gained through rigorous imaging tests using complex, heterogeneous but known media. The objective of this study is to build a virtual breast QUE simulation platform in the public domain that can be used not only for innovative QUE research but also for rigorous imaging tests. Methods: The main thrust of this work is to streamline biomedical ultrasound simulations by leveraging existing open source software packages including Field II (ultrasound simulator), VTK (geometrical visualization and processing), FEBio [finite element (FE) analysis], and Tetgen (mesh generator). However, integration of these open source packages is nontrivial and requires interdisciplinary knowledge. In the first step, a virtual breast model containing complex anatomical geometries was created through a novel combination of image-based landmark structures and randomly distributed (small) structures. Image-based landmark structures were based on data from the NIH Visible Human Project. Subsequently, an unstructured FE-mesh was created by Tetgen. In the second step, randomly positioned point scatterers were placed within the meshed breast model through an octree-based algorithm to make a virtual breast ultrasound phantom. In the third step, an ultrasound simulator (Field II) was used to interrogate the virtual breast phantom to obtain simulated ultrasound echo data. Of note, tissue deformation generated using a FE-simulator (FEBio) was the basis of deforming the original virtual breast phantom in order to obtain the postdeformation breast phantom for subsequent ultrasound simulations. Using the procedures described above, a full cycle of QUE simulations involving complex and highly heterogeneous virtual breast phantoms can be accomplished for the first time. Results: Representative examples were used to demonstrate capabilities of this virtual simulation platform. In the first set of three ultrasound simulation examples, three heterogeneous volumes of interest were selected from a virtual breast ultrasound phantom to perform sophisticated ultrasound simulations. These resultant B-mode images realistically represented the underlying complex but known media. In the second set of three QUE examples, advanced applications in QUE were simulated. The first QUE example was to show breast tumors with complex shapes and/or compositions. The resultant strain images showed complex patterns that were normally seen in freehand clinical ultrasound data. The second and third QUE examples demonstrated (deformation-dependent) nonlinear strain imaging and time-dependent strain imaging, respectively. Conclusions: The proposed virtual QUE platform was implemented and successfully tested in this study. Through show-case examples, the proposed work has demonstrated its capabilities of creating sophisticated QUE data in a way that cannot be done through the manufacture of physical tissue-mimicking phantoms and other software. This open software architecture will soon be made available in the public domain and can be readily adapted to meet specific needs of different research groups to drive innovations in QUE. PMID:26328994

Global mean-field phase diagram of the spin-1 Ising ferromagnet in a random crystal field

NASA Astrophysics Data System (ADS)

Borelli, M. E. S.; Carneiro, C. E. I.

1996-02-01

We study the phase diagram of the mean-field spin-1 Ising ferromagnet in a uniform magnetic field H and a random crystal field Δi, with probability distribution P( Δi) = pδ( Δi - Δ) + (1 - p) δ( Δi). We analyse the effects of randomness on the first-order surfaces of the Δ- T- H phase diagram for different values of the concentration p and show how these surfaces are affected by the dilution of the crystal field.

Cutting Force Predication Based on Integration of Symmetric Fuzzy Number and Finite Element Method

PubMed Central

Wang, Zhanli; Hu, Yanjuan; Wang, Yao; Dong, Chao; Pang, Zaixiang

2014-01-01

In the process of turning, pointing at the uncertain phenomenon of cutting which is caused by the disturbance of random factors, for determining the uncertain scope of cutting force, the integrated symmetric fuzzy number and the finite element method (FEM) are used in the prediction of cutting force. The method used symmetric fuzzy number to establish fuzzy function between cutting force and three factors and obtained the uncertain interval of cutting force by linear programming. At the same time, the change curve of cutting force with time was directly simulated by using thermal-mechanical coupling FEM; also the nonuniform stress field and temperature distribution of workpiece, tool, and chip under the action of thermal-mechanical coupling were simulated. The experimental result shows that the method is effective for the uncertain prediction of cutting force. PMID:24790556

Unsupervised change detection of multispectral images based on spatial constraint chi-squared transform and Markov random field model

NASA Astrophysics Data System (ADS)

Shi, Aiye; Wang, Chao; Shen, Shaohong; Huang, Fengchen; Ma, Zhenli

2016-10-01

Chi-squared transform (CST), as a statistical method, can describe the difference degree between vectors. The CST-based methods operate directly on information stored in the difference image and are simple and effective methods for detecting changes in remotely sensed images that have been registered and aligned. However, the technique does not take spatial information into consideration, which leads to much noise in the result of change detection. An improved unsupervised change detection method is proposed based on spatial constraint CST (SCCST) in combination with a Markov random field (MRF) model. First, the mean and variance matrix of the difference image of bitemporal images are estimated by an iterative trimming method. In each iteration, spatial information is injected to reduce scattered changed points (also known as "salt and pepper" noise). To determine the key parameter confidence level in the SCCST method, a pseudotraining dataset is constructed to estimate the optimal value. Then, the result of SCCST, as an initial solution of change detection, is further improved by the MRF model. The experiments on simulated and real multitemporal and multispectral images indicate that the proposed method performs well in comprehensive indices compared with other methods.