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At least 1,135 records · Page 63

Multilevel Sequential Monte Carlo Samplers for Normalizing Constants

This article considers the sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the discrete approximation error must be balanced. A multilevel strategy is utilized to substantially reduce the cost to obtain a given error level in the approximation as compared to standard estimators. Two estimators are considered and relative variance bounds are given. The theoretical results are numerically illustrated for two Bayesian inverse problems arising from elliptic partial differential equations (PDEs). The examples involve the inversion of observations of the solution of (i) a 1-dimensional Poisson equation to infer the diffusion coefficient, and (ii) a 2-dimensional Poisson equation to infer the external forcing.

97 MATHEMATICS AND COMPUTING↗

The application of far IR lasers to the investigation of the optical properties of materials

The effect of diffusion on the saturation and absorption properties of molecular gases is considered. The analysis starts with a simple derivation of the multi-level rate equations. Incorporating the diffusion term, calculations are carried out both for the homogeneous and inhomogeneous broadening cases. Both graphical and analytical solutions are obtained for the absorption coefficient and the saturation intensity. It is shown that the effect of diffusion is characterized by a diffusion function, which varies inversely with the radius of the beam at low pressures and small beam sizes. The analysis is done in terms of two parameters k1a and k2a, which are simple functions of the intensity of the beam I, the effective relaxation rate w, and the effective diffusion constant D the a is designated as the radius of the beam.

Stafsudd, O. M.↗

Fast and accurate implementation of Fourier spectral approximations of nonlocal diffusion operators and its applications

This work is concerned with the Fourier spectral approximation of various integral differential equations associated with some linear nonlocal diffusion and peridynamic operators under periodic boundary conditions. For radially symmetric kernels, the nonlocal operators under consideration are diagonalizable in the Fourier space so that the main computational challenge is on the accurate and fast evaluation of their eigenvalues or Fourier symbols consisting of possibly singular and highly oscillatory integrals. For a large class of fractional power-like kernels, we propose a new approach based on reformulating the Fourier symbols both as coefficients of a series expansion and solutions of some simple ODE models. We then propose a hybrid algorithm that utilizes both truncated series expansions and high order Runge–Kutta ODE solvers to provide fast evaluation of Fourier symbols in both one and higher dimensional spaces. It is shown that this hybrid algorithm is robust, efficient and accurate. As applications, we combine this hybrid spectral discretization in the spatial variables and the fourth-order exponential time differencing Runge–Kutta for temporal discretization to offer high order approximations of some nonlocal gradient dynamics including nonlocal Allen–Cahn equations, nonlocal Cahn–Hilliard equations, and nonlocal phase-field crystal models. Numerical results show the accuracy and effectiveness of the fully discrete scheme and illustrate some interesting phenomena associated with the nonlocal models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Where did the tumor start? An inverse solver with sparse localization for tumor growth models

In this work, we present a numerical scheme for solving an inverse problem for parameter estimation in tumor growth models for glioblastomas, a form of aggressive primary brain tumor. The growth model is a reaction–diffusion partial differential equation (PDE) for the tumor concentration. We use a PDE-constrained optimization formulation for the inverse problem. The unknown parameters are the reaction coefficient (proliferation), the diffusion coefficient (infiltration), and the initial condition field for the tumor PDE. Segmentation of magnetic resonance imaging (MRI) scans drive the inverse problem where segmented tumor regions serve as partial observations of the tumor concentration. Like most cases in clinical practice, we use data from a single time snapshot. Moreover, the precise time relative to the initiation of the tumor is unknown, which poses an additional difficulty for inversion. We perform a frozen-coefficient spectral analysis and show that the inverse problem is severely ill-posed. We introduce a biophysically motivated regularization on the structure and magnitude of the tumor initial condition. In particular, we assume that the tumor starts at a few locations (enforced with a sparsity constraint on the initial condition of the tumor) and that the initial condition magnitude in the maximum norm is equal to one. We solve the resulting optimization problem using an inexact quasi-Newton method combined with a compressive sampling algorithm for the sparsity constraint. Our implementation uses PETSc and AccFFT libraries. We conduct numerical experiments on synthetic and clinical images to highlight the improved performance of our solver over a previously existing solver that uses standard two-norm regularization for the calibration parameters. The existing solver is unable to localize the initial condition. Our new solver can localize the initial condition and recover infiltration and proliferation. In clinical datasets (for which the ground truth is unknown), our solver results in qualitatively different solutions compared to the two-norm regularized solver.

97 MATHEMATICS AND COMPUTING↗

Vapor transport processes of Ge-chalcogenides under normal and reduced gravity conditions

Experimental and theoretical studies of the GeSe-GeI4 system revealed the multicomponent, multireaction nature of this system and the existence of a diffusion boundary layer; they also yielded equations for the prediction of diffusion limited mass transport rates. Vapor transport and crystal growth experiments of the GeSe-GeI4 and GeSe-Xe systems on earth and in a microgravity environment demonstrated the effects of convection and of microgravity on mass flux and crystal morphology. The surface and bulk morphology of GeSe crystals obtained for both systems in microgravity is considerably improved relative to ground-based specimens. Unexpected crystal growth phenomena were observed for the GeSe-Xenon system on recent Shuttle flights.

Wiedemeier, H.↗

TRANSPORT OF SOLAR ENERGETIC PARTICLES ACCELERATED BY ICME SHOCKS: REPRODUCING THE RESERVOIR PHENOMENON

In this work, gradual solar energetic particle (SEP) events observed by multiple spacecraft are investigated with model simulations. Based on a numerical solution of the Fokker-Planck focused transport equation including perpendicular diffusion of particles, we obtained the fluxes of SEPs accelerated by an interplanetary coronal mass ejection driven shock as it propagates outward through the three-dimensional Parker interplanetary magnetic field. The shock is treated as a moving source of energetic particles with an assumed particle distribution function. We look at the time profiles of particle flux as they are observed simultaneously by multiple spacecraft located at different locations. The dependence of particle fluxes on different levels of perpendicular diffusion is determined. The main purpose of our simulation is to reproduce the reservoir phenomenon, during which it is frequently observed that particle fluxes are nearly the same at very different locations in the inner heliosphere, up to 5 AU, during the decay phase of gradual SEP events. The reservoir phenomenon is reproduced in our simulation under a variety of conditions of perpendicular diffusion of particles estimated from the nonlinear guiding center theory (NLGC). As the perpendicular diffusion coefficient increases, the nonuniformity of particle fluxes becomes smaller, making the reservoir phenomenon more prominent. However, if the shock acceleration strength decreases slower than r {sup -2.5} with the radial distance r, the reservoir phenomenon might disappear, with limited perpendicular diffusion constrained by the NLGC theory. Therefore, observation of the reservoir phenomenon in gradual SEP events can be used to test qualitatively theories of particle diffusion and shock acceleration.

79 ASTRONOMY AND ASTROPHYSICS↗

Evolution of the sun's polar fields during sunspot cycle 21 - Poleward surges and long-term behavior

Longitudinally averaged observations of the photospheric field during 1976-1986 are analyzed using a flux transport model. The way in which source eruptions, supergranular diffusion, and meridional flow collaborate to produce strong, highly concentrated polar fields near sunspot minimum is clarified as follows: (1) widespread eruptions of individual bipolar magnetic regions, with their leading polarity flux equatorward of their trailing polarity flux, collectively establish a large-scale separation of polarities in latitude; (2) the low-latitude, leading polarity flux diffuses across the equator and merges with its opposite hemisphere counterpart; and (3) meridional flow carries the resulting surplus of trailing polarity flux to the poles, and concentrates it there against the spreading effect of diffusion. Episodic 'surges' of flux to the poles are induced by fluctuations in the source eruption rate. Simulations indicate that relatively weak, trailing polarity surges may occur even in a steady flow field. However, in order to account for the giant surges of alternating polarity and the resulting oscillations in the polar field strength observed during 1980-1982, both accelerated flow and enhanced eruption rates are required.

Wang, Y.-M.↗

Convective diffusion in protein crystal growth

A protein crystal modeled as a flat plate suspended in the parent solution, with the normal to the largest face perpendicular to gravity and the protein concentration in the solution adjacent to the plate taken to be the equilibrium solubility, is studied. The Navier-Stokes equation and the equation for convective diffusion in the boundary layer next to the plate are solved to calculate the flow velocity and the protein mass flux. The local rate of growth of the plate is shown to vary significantly with depth due to the convection. For an aqueous solution of lysozyme at a concentration of 40 mg/ml, the boundary layer at the top of a 1-mm-high crystal has a thickness of 80 microns at 1 g, and 2570 microns at 10 to the -6th g.

Baird, J. K.↗

The Martian climate and energy balance models with CO2/H2O atmospheres

The analysis begins with a seasonal energy balance model (EBM) for Mars. This is used to compute surface temperature versus x = sin(latitude) and time over the seasonal cycle. The core model also computes the evolving boundaries of the CO2 icecaps, net sublimational/condensation rates, and the resulting seasonal pressure wave. Model results are compared with surface temperature and pressure history data at Viking lander sites, indicating fairly good agreement when meridional heat transport is represented by a thermal diffusion coefficient D approx. 0.015 W/sq. m/K. Condensational wind distributions are also computed. An analytic model of Martian wind circulation is then proposed, as an extension of the EMB, which incorporates vertical wind profiles containing an x-dependent function evaluated by substitution in the equation defining the diffusion coefficient. This leads to a parameterization of D(x) and of the meridional circulation which recovers the high surface winds predicted by dynamic Mars atmosphere models (approx. 10 m/sec). Peak diffusion coefficients, D approx. 0.6 w/sq m/K, are found over strong Hadley zones - some 40 times larger than those of high-latitude baroclinic eddies. When the wind parameterization is used to find streamline patterns over Martian seasons, the resulting picture shows overturning hemispheric Hadley cells crossing the equator during solstices, and attaining peak intensities during the south summer dust storm season, while condensational winds are most important near the polar caps.

Hoffert, M. I.↗

From clutter to clarity: Emergent neural operators via questionnaire metrics

Real-world datasets in chemical engineering and bioengineering processes—such as those from catalytic reactors, multiphase flows, polymerization reactors, bioreactors, and clinical trials—can often be unlabeled or disorganized, rendering the training of existing supervised learning models ineffective at learning the underlying dynamics. To salvage these datasets for decision-making, we first seek to obtain clarity from the cluttered data. Here, we present a framework for developing “structural” generative models, discovering emergent equations, and constructing efficient emulators from scrambled datasets by integrating unsupervised organizational learning techniques (Questionnaires) with advanced deep learning architectures (Deep Hidden Physics Models and Deep Operator Networks). Our approach is demonstrated on two illustrative model systems: (a) a 1D advection–diffusion partial differential equation representing a winding underground pipe and (b) an ensemble of Stuart–Landau oscillators, an agent-based system of coupled ordinary differential equations. In both cases, we successfully reconstruct meaningful spatial, temporal, and parameter embeddings from scrambled data, enabling good predictions of system dynamics. As a result, we highlight the framework’s potential for broader applications, enabling data-driven system identification in fields with inherently disorganized or hidden parameter spaces.

42 ENGINEERING↗

Large-scale Compression Acceleration during Magnetic Reconnection in a Low- β Plasma

In solar flares and other astrophysical systems, a major challenge for solving the particle acceleration problem associated with magnetic reconnection is the enormous scale separation between kinetic scales and the observed reconnection scale. Because of this, it has been difficult to draw any definite conclusions by just using kinetic simulations. A particle acceleration model that solves the energetic particle transport equation can capture the main acceleration physics found in kinetic simulations and thus provide a practical way to make observable predictions and directly compare model results with observations. Here we study compression particle acceleration in magnetic reconnection by solving the Parker (diffusion–advection) transport equation using velocity and magnetic fields from two-dimensional magnetohydrodynamics (MHD) simulations of a low-β high-Lundquist-number reconnection layer. We show that the compressible reconnection layer can give significant particle acceleration, leading to the formation of power-law particle energy distributions. We analyze the acceleration rate and find that the acceleration in the reconnection layer is a mixture of first- and second-order Fermi processes. When including a guide field, we find that the spectrum becomes steeper and both the power-law cutoff energy and maximum particle energy decrease as plasma becomes less compressible. This model produces a 2D particle distribution that one can use to generate a radiation map and directly compare with solar flare observations. This provides a framework to explain particle acceleration at large-scale astrophysical reconnection sites, such as solar flares.

79 ASTRONOMY AND ASTROPHYSICS↗

Simple analytical solutions for spherically symmetric production and modulation of energetic solar particles

Exact analytical solutions are presented for the standard time-independent spherically symmetric convection-diffusion-adiabatic deceleration equation governing the transport of cosmic rays in the interplanetary medium for the case in which particles are produced with spherical symmetry at the sun. It is assumed that the solar-wind speed is constant and radial, and that the spatial diffusion coefficient has a power-law dependence on momentum. The Green's function describing the modulation of a monoenergetic production of particles is presented. The solutions provide a useful basis for the study of time-integrated properties of energetic solar-flare particle spectra.

Gross, M. W.↗

Stochastic differential equation model for linear growth birth and death processes with immigration and emigration

This paper discusses on linear birth and death with immigration and emigration (BIDE) process to stochastic differential equation (SDE) model. Forward Kolmogorov equation in continuous time Markov chain (CTMC) with a central-difference approximation was used to find Fokker-Planckequation corresponding to a diffusion process having the stochastic differential equation of BIDE process. The exact solution, mean and variance function of BIDE process was found.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fuel Loading Optimization and Planning for the Versatile Test Reactor

The Versatile Test Reactor (VTR) mission is to enable accelerated testing of advanced reactor fuels and materials required for advanced reactor technologies. In service of this duty, the goal of the design is to maximize the peak fast flux and the experimental volume exposed to a fast flux above 4.0 × 1015n/cms s. Delivering the desired neutron fluence for each experiment requires the capability to optimize the fuel loading to achieve a specified cycle length and flux, while also satisfying other criteria such as thermal hydraulic design constraints. To achieve the desired conditions and cycle length, several measures may be taken, including optimization of the fuel loading pattern, moving partially-burned assemblies back and forth between the core and the in-vessel storage, and potentially shuffling fuel within the core. Optimizing in a "brute-force" manner by solving a wholecore transport equation for hundreds of configurations would be inefficient. A sufficiently refined DIF3D-VARIANT solution for the whole core requires on the order of 1 hour. Instead, we seek an approximate evaluation of the parameters for many variations on a base core configuration without directly solving a diffusion or transport equation for each.

fuel loading optimization↗

Expeditious modeling of vapor transport and reactions in polymeric materials

We present a methodology for approximating dynamic adsorption of vapor coupled with diffusion in polymeric materials. In previous publications, the dynamic adsorption was represented by ordinary differential equations (ODEs) and solved in concentration and parameter space. To accelerate the calculation, we have developed a statistical approximation method using computationally cheap surrogate models (e.g., algebraic polynomials) that replace the ODE solutions of adsorption and are coupled with the diffusion equations. Since the polynomial presentation of the adsorption term is obtained in a standard format prior to modeling coupled sorption‐diffusion, the adsorption operator can be expressed as input data in the transport code. Compared to conventional operator‐splitting methods, the polynomial approximation of adsorption offers better computational efficiency. The methodology is demonstrated and validated using a dynamic Langmuir adsorption model that is coupled to diffusion and absorption models and applied to a water vapor sorption‐diffusion process in polydimethylsiloxane polymers. © 2017 American Institute of Chemical Engineers AIChE J , 63: 4079–4089, 2017

Sun, Yunwei↗

Design and convergence analysis of the conforming virtual element method for polyharmonic problems

In the recent years, there has been a tremendous interest to numerical methods that approximate partial differential equations (PDEs) on computational meshes with arbitrarily-shaped polygonal/polyhedral (polytopal, for short) elements. A nonexhaustive list of such methods include the Mimetic Finite Difference method [4, 9, 21, 24, 28, 33, 35, 62, 64–67], the Polygonal Finite Element Method [68, 73, 74], the polygonal Discontinuous Galerkin Finite Element Methods [5, 7, 8, 10, 13–15, 18, 36, 38, 39, 41, 50], the Hybridizable Discontinuous Galerkin and Hybrid High-Order Methods [46–48, 51], the Gradient Discretization method [49, 53, 54], the Finite Volume Method [52], and the BEM-based FEM [71]. An alternative approach that also proved to be very successful is provided by the Virtual Element method (VEM), which was originally proposed in [19] for the numerical treatment of second-order elliptic problems [43, 44], and readily extended to linear and nonlinear elasticity [22, 25, 56], plate bending problems [37], Cahn-Hilliard equation [3], Stokes equations [2], Laplace-Beltrami equation [55], Darcy-Brinkam equation [76], discrete topology optimization problems [6], fracture networks problems [29], eigenvalue problems [59, 75]. The mixed virtual element formulation was proposed in [20, 34]; the nonconforming Virtual element formulations was proposed for second-order elliptic problems in [16], and later extended to general advection-reaction-diffusion problems, Stokes equation, the biharmonic problems, the iegenvalue problem, and the Schrodinger equation in [11, 30, 42, 45, 58, 80]. The p- and hp-version of the VEM were developed in [26, 27] and efficient multigrid methods for the resulting linear system of equations in [12]. A posteriori error estimates can be found in [40].

97 MATHEMATICS AND COMPUTING↗

Integral approximations to classical diffusion and smoothed particle hydrodynamics

The contribution of the paper is the approximation of a classical diffusion operator by an integral equation with a volume constraint. A particular focus is on classical diffusion problems associated with Neumann boundary conditions. By exploiting this approximation, we can also approximate other quantities such as the flux out of a domain. Our analysis of the model equation on the continuum level is closely related to the recent work on nonlocal diffusion and peridynamic mechanics. In particular, we elucidate the role of a volumetric constraint as an approximation to a classical Neumann boundary condition in the presence of physical boundary. The volume-constrained integral equation then provides the basis for accurate and robust discretization methods. An immediate application is to the understanding and improvement of the Smoothed Particle Hydrodynamics (SPH) method.

boundary conditions, smoothed particle hydrodynami↗