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At least 1,747 records · Page 97

Validation and uncertainty of DRF's for a 1"×2" NaI collimated detector for radioisotope holdup measurements

Detector response functions (DRFs) have become the subject of increasing scientific interest for the last thirty years in several industrial applications of radiation detection. These applications include gamma-ray, prompt gamma-ray, and X-ray spectrometry for elemental analysis and location as applied to mining, radio-tracing in medicine, and holdup source characterization. However, it is difficult to create a rigorous mathematical formulation of the DRF. Therefore, semi-empirical and stochastic approaches have been developed instead to construct detector and application specific DRFs. A DRF can be considered to be a function that converts the energy-dependent incidence of incoming source particles onto a detector into a detector response spectrum that simulates the experimental response. The DRF can also be used in the reverse sense in an inverse problem setting, as a step in the process of predicting the physical characteristics of an unknown source (e.g. the holdup problem and library spectra). Much of the recent work on DRFs has been performed by Gardner. He has developed accurate DRF models through semi-empirical curve fitting and Monte Carlo simulation. His DRFs for 3" X 3" NaI detectors have been developed with the experimental measurements taken by Heath and for 6"x6" bare (unshielded) NaI(Tl) detector data with single-energy sources centered on the detector face at a distance of 10 cm. There was agreement with the Heath benchmark detector measurements within two Poisson standard deviations of the measured data. DRFs have also been developed for other detectors such as high purity Germanium detectors and Si(Li) for the same geometries as NaI. Other than a few artifacts such as backscatter peaks, there was good agreement between simulated responses and the experimental data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Molecular Dynamics Modeling of PPTA Crystals in Aramid Fibers

In this work, molecular dynamics modeling is used to study the mechanical properties of PPTA crystallites, which are the fundamental microstructural building blocks of polymer aramid bers such as Kevlar. Particular focus is given to constant strain rate axial loading simulations of PPTA crystallites, which is motivated by the rate-dependent mechanical properties observed in some experiments with aramid bers. In order to accommodate the covalent bond rupture that occurs in loading a crystallite to failure, the reactive bond order force eld ReaxFF is employed to conduct the simulations. Two major topics are addressed: The rst is the general behavior of PPTA crystallites under strain rate loading. Constant strain rate loading simulations of crystalline PPTA reveal that the crystal failure strain increases with increasing strain rate, while the modulus is not a ected by the strain rate. Increasing temperature lowers both the modulus and the failure strain. The simulations also identify the C N bond connecting the aromatic rings as weakest primary bond along the backbone of the PPTA chain. The e ect of chain-end defects on PPTA micromechanics is explored, and it is found that the presence of a chain-end defect transfers load to the adjacent chains in the hydrogen-bonded sheet in which the defect resides, but does not in uence the behavior of any other chains in the crystal. Chain-end defects are found to lower the strength of the crystal when clustered together, inducing bond failure via stress concentrations arising from the load transfer to bonds in adjacent chains near the defect site. The second topic addressed is the nature of primary and secondary bond failure in crystalline PPTA. Failure of both types of bonds is found to be stochastic in nature and driven by thermal uctuations of the bonds within the crystal. A model is proposed which uses reliability theory to model bonds under constant strain rate loading as components with time-dependent failure rate functions. The model is shown to work well for predicting the onset of primary backbone bond failure, as well as the onset of secondary bond failure via chain slippage for the case of isolated non-interacting chain-end defects.

36 MATERIALS SCIENCE↗

Revisiting stochastic variability of AGNs with structure functions

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

79 ASTRONOMY AND ASTROPHYSICS↗

Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence

Particle-laden turbulent flows subject to radiative heating are relevant in many applications, for example concentrated solar power receivers. Efficient and accurate simulations provide valuable insights and enable optimization of such systems. However, as there are many uncertainties inherent in such flows, uncertainty quantification is fundamental to improve the predictive capabilities of the numerical simulations. For large-scale, multi-physics problems exhibiting high-dimensional uncertainty, characterizing the stochastic solution presents a significant computational challenge as most strategies require a large number of high-fidelity solves. This requirement might result in an infeasible number of simulations when a typical converged high-fidelity simulation requires intensive computational resources. To reduce the cost of quantifying high-dimensional uncertainties, we investigate the application of a non-intrusive, bi-fidelity approximation to estimate statistics of quantities of interest associated with an irradiated particle-laden turbulent flow. This method exploits the low-rank structure of the solution to accelerate the stochastic sampling and approximation processes by means of cheaper-to-run, lower fidelity representations. Here, the application of this bi-fidelity approximation results in accurate estimates of the quantities of interest statistics, while requiring a small number of high-fidelity model evaluations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ENSO Recharge Oscillator Theory Integrating the Southward Wind Shift

The El Niño–Southern Oscillation (ENSO) is one of the most‐well understood climate phenomena, and the Recharge Oscillator (RO) theory is widely used to conceptualize its physics in observations and models. ENSO‐associated equatorial zonal wind anomalies shift southward in boreal winter, contributing to ENSO termination. Thus far, this effect has not been explicitly described in the RO framework. Here we derive a new form of the RO under the low‐frequency limit that incorporates the seasonal migration of zonal wind anomalies. In our theory, the Bjerknes feedback depends on the central latitude of zonal wind anomalies, decaying exponentially as winds shift away from the equator. Meanwhile, wind anomalies centered off the equator induce equatorial wave adjustment and thereby have a delayed effect on sea surface temperature anomalies. A stochastic RO simulation with a prescribed wind shift reproduces about half the amplitude of ENSO seasonal synchronization as well as ENSO combination tones.

54 ENVIRONMENTAL SCIENCES↗

On the inclusion of the diagonal Born-Oppenheimer correction in surface hopping methods

The diagonal Born-Oppenheimer correction (DBOC) stems from the diagonal second derivative coupling term in the adiabatic representation, and it can have an arbitrary large magnitude when a gap between neighbouring Born-Oppenheimer (BO) potential energy surfaces (PESs) is closing. Nevertheless, DBOC is typically neglected in mixed quantum-classical methods of simulating nonadiabatic dynamics (e.g., fewest-switch surface hopping (FSSH) method). A straightforward addition of DBOC to BO PESs in the FSSH method, FSSH+D, has been shown to lead to numerically much inferior results for models containing conical intersections. More sophisticated variation of the DBOC inclusion, phase-space surface-hopping (PSSH) was more successful than FSSH+D but on model problems without conical intersections. This work comprehensively assesses the role of DBOC in nonadiabatic dynamics of two electronic state problems and the performance of FSSH, FSSH+D, and PSSH methods in variety of one- and two-dimensional models. Our results show that the inclusion of DBOC can enhance the accuracy of surface hopping simulations when two conditions are simultaneously satisfied: (1) nuclei have kinetic energy lower than DBOC and (2) PESs are not strongly nonadiabatically coupled. The inclusion of DBOC is detrimental in situations where its energy scale becomes very high or even diverges, because in these regions PESs are also very strongly coupled. In this case, the true quantum formalism heavily relies on an interplay between diagonal and off-diagonal nonadiabatic couplings while surface hopping approaches treat diagonal terms as PESs and off-diagonal ones stochastically.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A general framework for quantitatively assessing ecological stochasticity

Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. Here we propose a general mathematical framework to quantify ecological stochasticity under different situations in which deterministic factors drive the communities more similar or dissimilar than null expectation. An index, normalized stochasticity ratio ( NST ), was developed with 50% as the boundary point between more deterministic (<50%) and more stochastic (>50%) assembly. NST was tested with simulated communities by considering abiotic filtering, competition, environmental noise, and spatial scales. All tested approaches showed limited performance at large spatial scales or under very high environmental noise. However, in all of the other simulated scenarios, NST showed high accuracy (0.90 to 1.00) and precision (0.91 to 0.99), with averages of 0.37 higher accuracy (0.1 to 0.7) and 0.33 higher precision (0.0 to 1.8) than previous approaches. NST was also applied to estimate stochasticity in the succession of a groundwater microbial community in response to organic carbon (vegetable oil) injection. Our results showed that community assembly was shifted from more deterministic ( NST = 21%) to more stochastic ( NST = 70%) right after organic carbon input. As the vegetable oil was consumed, the community gradually returned to be more deterministic ( NST = 27%). In addition, our results demonstrated that null model algorithms and community similarity metrics had strong effects on quantifying ecological stochasticity.

54 ENVIRONMENTAL SCIENCES↗

A guidance and navigation system for continuous low thrust vehicles

A midcourse guidance and navigation system for continuous low thrust vehicles is described. A set of orbit elements, known as the equinoctial elements, are selected as the state variables. The uncertainties are modelled statistically by random vector and stochastic processes. The motion of the vehicle and the measurements are described by nonlinear stochastic differential and difference equations respectively. A minimum time nominal trajectory is defined and the equation of motion and the measurement equation are linearized about this nominal trajectory. An exponential cost criterion is constructed and a linear feedback guidance law is derived to control the thrusting direction of the engine. Using this guidance law, the vehicle will fly in a trajectory neighboring the nominal trajectory. The extended Kalman filter is used for state estimation. Finally a short mission using this system is simulated. The results indicate that this system is very efficient for short missions.

Tse, C. J. C.↗

Atmospheric PSF Interpolation for Weak Lensing in Short Exposure Imaging Data

A main science goal for the Large Synoptic Survey Telescope (LSST) is to measure the cosmic shear signal from weak lensing to extreme accuracy. One difficulty, however, is that with the short exposure time ({approx_equal}15 seconds) proposed, the spatial variation of the Point Spread Function (PSF) shapes may be dominated by the atmosphere, in addition to optics errors. While optics errors mainly cause the PSF to vary on angular scales similar or larger than a single CCD sensor, the atmosphere generates stochastic structures on a wide range of angular scales. It thus becomes a challenge to infer the multi-scale, complex atmospheric PSF patterns by interpolating the sparsely sampled stars in the field. In this paper we present a new method, psfent, for interpolating the PSF shape parameters, based on reconstructing underlying shape parameter maps with a multi-scale maximum entropy algorithm. We demonstrate, using images from the LSST Photon Simulator, the performance of our approach relative to a 5th-order polynomial fit (representing the current standard) and a simple boxcar smoothing technique. Quantitatively, psfent predicts more accurate PSF models in all scenarios and the residual PSF errors are spatially less correlated. This improvement in PSF interpolation leads to a factor of 3.5 lower systematic errors in the shear power spectrum on scales smaller than {approx} 13, compared to polynomial fitting. We estimate that with psfent and for stellar densities greater than {approx_equal}1/arcmin{sup 2}, the spurious shear correlation from PSF interpolation, after combining a complete 10-year dataset from LSST, is lower than the corresponding statistical uncertainties on the cosmic shear power spectrum, even under a conservative scenario.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A framework to analyze the stochastic harmonics and resonance of wind energy grid interconnection

This study addresses a modeling and analysis methodology for investigating the stochastic harmonics and resonance concerns of wind power plants (WPPs). Wideband harmonics from modern wind turbines are observed to be stochastic, associated with real power production, and they may adversely interact with the grid impedance and cause unexpected harmonic resonance if not comprehensively addressed in the planning and commissioning of the WPPs. These issues should become more critical as wind penetration levels increase. We thus propose a planning study framework comprising the following functional steps: First, the best-fitted probability density functions (PDFs) of the harmonic components of interest in the frequency domain are determined. In operations planning, maximum likelihood estimations followed by a chi-square test are used once field measurements or manufacturers' data are available. Second, harmonic currents from the WPP are represented by randomly-generating harmonic components based on their PDFs (frequency spectrum) and then synthesized for time-domain simulations via inverse Fourier transform. Finally, we conduct a comprehensive assessment by including the impacts of feeder configurations, harmonic filters, and the variability of parameters. We demonstrate the efficacy of the proposed study approach for a 100-MW offshore WPP consisting of 20 units of 5-MW full-converter turbines, a realistic benchmark system adapted from a WPP under development in Korea, and discuss lessons learned through this research.

17 WIND ENERGY↗

The Fragment Molecular Orbital Method Based on Long-Range Corrected Density-Functional Tight-Binding

The presently available linear scaling approaches to density-functional tight-binding (DFTB) based on the fragment molecular orbital (FMO) method are severely impacted by the problem of artificial charge transfer due to the self-interaction error (SIE), which hampers the simulation of zwitterionic systems such as biopolymers or ionic liquids. Here we report an extension of FMO-DFTB where we included a long-range corrected (LC) functional designed to mitigate the DFTB SIE, called the FMO-LC-DFTB method, resulting in a robust method which succeeds in simulating zwitterionic systems. Both energy and analytic gradient are developed for the gas phase and the polarizable continuum model of solvation. The scaling of FMO-LC-DFTB with system size N is shown to be almost linear, O( N 1.13–1.28 ), and its numerical accuracy is established for a variety of representative systems including neutral and charged polypeptides. It is shown that pair interaction energies between fragments for two mini-proteins are in excellent agreement with results from long-range corrected density functional theory. Here the new method was employed in long time scale (1 ns) molecular dynamics simulations of the tryptophan cage protein (PDB: 1L2Y) in the gas phase for four different protonation states and in stochastic global minimum structure searches for 1-ethyl-3-methylimidazolium nitrate ionic liquid clusters containing up to 2300 atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tracking control of colloidal particles through non-homogeneous stationary flows

We consider the problem of controlling the trajectory of a single colloidal particle in a fluid with steady non-homogeneous flow. We use a Langevin equation to describe the dynamics of this particle, where the friction term is assumed to be given by the Faxén's Theorem for the force on a sphere immersed in a stationary flow. We use this description to propose an explicit control force field to be applied on the particle such that it will follow asymptotically any given desired trajectory, starting from an arbitrary initial condition. We show that the dynamics of the controlled particle can be mapped into a set of stochastic harmonic oscillators and that the velocity gradient of the solvent induces an asymmetric coupling between them. We study the particular case of a Brownian particle controlled through a plane Couette flow and show explicitly that the velocity gradient of the solvent renders the dynamics non-stationary and non-reversible in time. We quantify this effect in terms of the correlation functions for the position of the controlled particle, which turn out to exhibit contributions depending exclusively on the non-equilibrium character of the state of the solvent. In order to test the validity of our model, we perform simulations of the controlled particle moving in a simple shear flow, using a hybrid method combining molecular dynamics and multi-particle collision dynamics. We confirm numerically that the proposed guiding force allows for controlling the trajectory of the micro-sized particle by obligating it to follow diverse specific trajectories in fluids with homogeneous shear rates of different strengths. In addition, we find that the non-equilibrium correlation functions in simulations exhibit the same qualitative behavior predicted by the model, thus revealing the presence of the asymmetric non-equilibrium coupling mechanism induced by the velocity gradient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Analytic Criterion for Turbulent Disruption of Planetary Resonances

Mean motion commensurabilities in multi-planet systems are an expected outcome of protoplanetary disk-driven migration, and their relative dearth in the observational data presents an important challenge to current models of planet formation and dynamical evolution. One natural mechanism that can lead to the dissolution of commensurabilities is stochastic orbital forcing, induced by turbulent density fluctuations within the nebula. While this process is qualitatively promising, the conditions under which mean motion resonances can be broken are not well understood. In this work, we derive a simple analytic criterion that elucidates the relationship among the physical parameters of the system, and find the conditions necessary to drive planets out of resonance. Subsequently, we confirm our findings with numerical integrations carried out in the perturbative regime, as well as direct N-body simulations. Our calculations suggest that turbulent resonance disruption depends most sensitively on the planet–star mass ratio. Specifically, for a disk with properties comparable to the early solar nebula with α=10{sup −2}, only planet pairs with cumulative mass ratios smaller than (m{sub 1}+m{sub 2})/M≲10{sup −5}∼3M{sub ⊕}/M{sub ⊙} are susceptible to breaking resonance at semimajor axis of order a∼0.1 au. Although turbulence can sometimes compromise resonant pairs, an additional mechanism (such as suppression of resonance capture probability through disk eccentricity) is required to adequately explain the largely non-resonant orbital architectures of extrasolar planetary systems.

79 ASTRONOMY AND ASTROPHYSICS↗

The second-moment climatology of the GATE rain rate data

The first part of this paper presents the description of the GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment (GATE) 1 rain-rate data and its two-dimensional spectral and correlation characteristics, which has made it possible to accomplish the following: to show the concentration of a significant power along the frequency axis in the spatiotemporal spectra; to detect a diurnal cycle (which has a range of variation of about 3.4-5.4 mm/n) as one of the sources of bias in the rain statistics of satellite data; to study the distinction between the north-south and east-west transport of spatial rain-rate field and character of its anisotropy; to evaluate the scales of the distinction between second-moment estimates associated with ground and satellite samples; and to determine the appropriate spatial and temporal scales of simple linear stochastic models fitted to averaged rain-rate fields. The second part of this paper is devoted to an analysis of the diffusion of the rain rate by establishing a relationship between the parameters of the multivariate autoregressive model and the coefficients of a diffusion equation. This analysis led to the use of rain data to estimate the rain advection velocity as well as other coefficients of the diffusion equation of the corresponding field. The results obtained can be used for comparison with corresponding estimates of other sources of data (satellite, Tropical Oceans Global Atmosphere Coupled Ocean - Atmosphere Response Experiment (TOGA, COARE) or simulated by physical models), for generating multiple samples of any size, for solving the inverse problems of some of the hydrodynamic equations, and in some other areas of rain data analysis and modeling.

Polyak, Ilya↗

A Framework for Incorporating General Domain Knowledge into Latent Dirichlet Allocation using First-Order Logic

Topic models have been used successfully for a variety of problems, often in the form of application-specific extensions of the basic Latent Dirichlet Allocation (LDA) model. Because deriving these new models in order to encode domain knowledge can be difficult and time-consuming, we propose the Fold-all model, which allows the user to specify general domain knowledge in First-Order Logic (FOL). However, combining topic modeling with FOL can result in inference problems beyond the capabilities of existing techniques. We have therefore developed a scalable inference technique using stochastic gradient descent which may also be useful to the Markov Logic Network (MLN) research community. Experiments demonstrate the expressive power of Fold-all, as well as the scalability of our proposed inference method.

97 MATHEMATICS AND COMPUTING↗

Numerical simulation of a turbulent flame stabilized behind a rearward-facing step

Flow of combustible mixtures in a plane channel past a smooth contraction followed by an abrupt expansion, in a typical dump combustor configuration, is modeled by a two-dimensional numerical technique based on the random vortex method. Both the inert and the reacting case are considered. In the latter, the flame is treated as an interface, self-advancing at a prescribed normal burning speed, while the dynamic effects of expansion due to the exothermicity of combustion are expressed by volumetric source lines delineated by its front. Solutions are shown to be in satisfactory agreement with experimental results, especially with respect to global properties such as the average velocity profiles and the reattachment length. The stochastic turbulent velocity components manifest interesting differences, especially near the walls where three-dimensional effects of turbulence are expected to be of importance.

Hsiao, C. C.↗

Closures and Simulation for Thermal Radiation Transport in Stochastic Media with Nonlinear Temperature Dependence

Because of the practical challenge of rendering very complex realistic spatial structures for numerical work, it is common practice to resort to characterizing such media as stochastic mixtures of materials, ideally parametrized with low order statistics such as the mean, variance, and correlation functions of the now random material properties. This enables realizations of the medium to be repeatedly generated and radiation transport computations to, in principle, be performed for a large ensemble of these realizations to obtain a statistically well-characterized radiation field. Statistical post-processing yields desired quantities such as conditional and unconditional mean radiation flux and probability distributions of transmitted radiation. However, such computations prove expensive for all but the simplest stochastic geometries and are most suited for benchmarking approximate models. The most common approximations lead to homogenized media so that transport computations are required only on a single medium realization but by construct provide only limited statistical information on the radiation field. Almost all approximate approaches to this problem attempt to develop equations for low order moments of the radiation intensity (mean, second moment, correlation function) but inevitably encounter a closure problem: the equation for any statistical moment will contain terms depending on unknown higher-order moments. Thus, the challenge shifts to one of developing closure relations that relate the unknown moments to the lower order moments. Under very special conditions, an exact closure can be derived but in general closures are heuristically stated constitutive relations. Also, closure approaches depend on whether the mixing statistics are spatially and/or temporally continuous as in fluctuating turbulent fields, or discontinuous as in randomly mixed solid chunks of material. Thus, unconditional averaging is generally applied in the former case but conditional averaging is more appropriate when the mixing is discontinuous. In this work, the emphasis is on binary statistical mixtures of immiscible fluids as as such the quantities of interest are averages (flux, temperature) conditioned on the material type.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Theory of magnetic field line random walk in noisy reduced magnetohydrodynamic turbulence

When a magnetic field consists of a mean part and fluctuations, the stochastic wandering of its field lines is often treated as a diffusive process. Under suitable conditions, a stable value is found for the mean square transverse displacement per unit parallel displacement relative to the mean field. Here, we compute the associated field line diffusion coefficient for a highly anisotropic 'noisy' reduced magnetohydrodynamic model of the magnetic field, which is useful in describing low frequency turbulence in the presence of a strong applied DC mean magnetic field, as may be found, for example, in the solar corona, or in certain laboratory devices. Our approach is nonperturbative, based on Corrsin's independence hypothesis, and makes use of recent advances in understanding factors that control decorrelation over a range of parameters described by the Kubo number. Both Bohm and quasilinear regimes are identified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗