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At least 289 records · Page 16

Asymptotically Compatible Reproducing Kernel Collocation and Meshfree Integration for Nonlocal Diffusion

Reproducing kernel (RK) approximations are meshfree methods that construct shape functions from sets of scattered data. We present an asymptotically compatible (AC) RK collocation method for nonlocal diffusion models with Dirichlet boundary condition. The numerical scheme is shown to be convergent to both nonlocal diffusion and its corresponding local limit as nonlocal interaction vanishes. The analysis is carried out on a special family of rectilinear Cartesian grids for a linear RK method with designed kernel support. The key idea for the stability of the RK collocation scheme is to compare the collocation scheme with the standard Galerkin scheme, which is stable. In addition, assembling the stiffness matrix of the nonlocal problem requires costly computational resources because high-order Gaussian quadrature is necessary to evaluate the integral. We thus provide a remedy to the problem by introducing a quasi-discrete nonlocal diffusion operator for which no numerical quadrature is further needed after applying the RK collocation scheme. The quasi-discrete nonlocal diffusion operator combined with RK collocation is shown to be convergent to the correct local diffusion problem by taking the limits of nonlocal interaction and spatial resolution simultaneously. The theoretical results are then validated with numerical experiments. We additionally illustrate a connection between the proposed technique and an existing optimization based approach based on generalized moving least squares.

97 MATHEMATICS AND COMPUTING↗

Scattering of light in a spherical multilayer atmosphere

The problem of radiation diffusion in the atmosphere of a planet illuminated by solar rays was examined. The basic equations of the problem were obtained and the solution was found for the case when the absorption coefficient in the atmosphere is constant. The assumption was introduced of exponential variation of absorptivity with altitude, and a first approximation solution was proposed.

Titarchuk, L. G.↗

A fractional model for anomalous diffusion with increased variability: Analysis, algorithms and applications to interface problems

Fractional equations have become the model of choice in several applications where heterogeneities at the microstructure result in anomalous diffusive behavior at the macroscale. Here, we introduce a new fractional operator characterized by a doubly-variable fractional order and possibly truncated interactions. Under certain conditions on the model parameters and on the regularity of the fractional order we show that the corresponding Poisson problem is well-posed. Additionally, we introduce a finite element discretization and describe an efficient implementation of the finite-element matrix assembly in the case of piecewise constant fractional order. Through several numerical tests, we illustrate the improved descriptive power of this new operator across media interfaces. Furthermore, we present one-dimensional and two-dimensional h-convergence results that show that the variable-order model has the same convergence behavior as the constant-order model.

97 MATHEMATICS AND COMPUTING↗

Generalized theory of diffusion based on kinetic theory

Here, we propose to use spin hydrodynamics, a two-fluid model of spin propagation, as a generalization of the diffusion equation. We show that in the dense limit spin hydrodynamics reduces to Fick's law and the diffusion equation. In the opposite limit spin hydrodynamics is equivalent to a collisionless Boltzmann treatment of spin propagation. Spin hydrodynamics avoids unphysical effects that arise when the diffusion equation is used to describe to a strongly interacting gas with a dilute corona. We apply spin hydrodynamics to the problem of spin diffusion in a trapped atomic gas. We find that the observed spin relaxation rate in the high-temperature limit [Sommer et al., Nature (London) 472, 201 (2011)] is consistent with the diffusion constant predicted by kinetic theory.

74 ATOMIC AND MOLECULAR PHYSICS↗

Multilevel well modeling in aggregation-based nonlinear multigrid for multiphase flow in porous media

A full approximation scheme (FAS) nonlinear multigrid solver for two-phase flow and transport problems driven by wells with multiple perforations is developed here. It is an extension to our previous work on FAS solvers for diffusion and transport problems. The solver is applicable to discrete problems defined on unstructured grids as the coarsening algorithm is aggregation-based and algebraic. To construct coarse basis that can better capture the radial flow near wells, coarse grids in which perforated well cells are not near the coarse-element interface are desired. This is achieved by an aggregation algorithm proposed in this paper that makes use of the location of well cells in the cell-connectivity graph. Numerical examples in which the FAS solver is compared against Newton's method on benchmark problems are given. In particular, for a refined version of the SAIGUP model, the FAS solver is at least 35% faster than Newton's method for time steps with a CFL number greater than 10.

58 GEOSCIENCES↗

Turbo fluid machinery and diffusers

The general theory behind turbo devices and diffusers is explained. Problems and the state of research on basic equations of flow and experimental and measuring methods are discussed. Conventional centrifugation-type compressor and fan diffusers are considered in detail.

Sakurai, T.↗

Calculations of the cosmic ray modulation in interplanetary space taking into account the possible dependence of the transport travel for the scattering of the particles and of the velocity of the solar winds on the angles they make with the helioequator plane: The case of isotropic diffusion

The modulation of galactic cosmic rays is studied by the magnetic heterogeneities stream on the assumption that the diffusion coefficient is reduced whereas the solar wind velocity is increased with the growth of the angle between the sun's rotation axis and the direction of solar plasma motion. The stationary plane problem of isotropic diffusion is solved as it applies to two cases: (1) with due account of particle retardation by the antiphermium mechanism; and (2) without an account of the above mechanism. This problem is solved by the grid method in the polar coordinate system. The results of the calculations are followed by a discussion of the method of solution and of the errors.

Dorman, L. I.↗

Diffusion analysis for two-phase metal-matrix composite

Diffusion controlled filament matrix interaction in a metal matrix composite, where the filaments and matrix comprise a two phase binary alloy system, was mathematically modeled. The problem of a diffusion controlled, two phase moving interface by means of a one dimensional, variable grid, finite difference technique was analyzed. Concentration dependent diffusion coefficients and equilibrium solubility limits were used, and the change in filament diameter and compositional changes in the matrix were calculated as a function of exposure time at elevated temperatures. With the tungsten nickel (W-Ni) system as a model composite system, unidirectional composites containing from 0.06 to 0.44 initial filament volume fraction were modeled. Compositional changes in the matrix were calculated by superposition of the contributions from neighboring filaments. Alternate methods for determining compositional changes between first and second nearest neighbor filaments were also considered. The results show the relative importance of filament volume fraction, filament diameter, exposure temperature, and exposure time as they affect the rate and extent of filament matrix interaction.

Tenney, D. R.↗

A comparative study of Full Navier-Stokes and Reduced Navier-Stokes analyses for separating flows within a diffusing inlet S-duct

A three-dimensional implicit Full Navier-Stokes (FNS) analysis and a 3D Reduced Navier Stokes (RNS) initial value space marching solution technique has been applied to a class of separated flow problems within a diffusing S-duct configuration characterized by vortex-liftoff. Both the FNS and the RNS solution technique were able to capture the overall flow physics of vortex lift-off, and gave remarkably similar results which agreed reasonably well with the experimental measured averaged performance parameters of engine face total pressure recovery and distortion. However, the Full Navier-Stokes and Reduced Navier-Stokes also consistently predicted separation further downstream in the M2129 inlet S-duct than was indicated by experimental data, thus compensating errors were present in the two Navier-Stokes analyses. The difficulties encountered in the Navier-Stokes separations analyses of the M2129 inlet S-duct center primarily on turbulence model issues, and these focused on two distinct but different phenomena, namely, (1) characterization of low skin friction adverse pressure gradient flows, and (2) description of the near wall behavior of flows characterized by vortex lift-off.

Anderson, B. H.↗

A comparative study of full Navier-Stokes and Reduced Navier-Stokes analyses for separating flows within a diffusing inlet S-duct

A three-dimensional implicit Full Navier-Stokes (FNS) analysis and a 3D Reduced Navier-Stokes (RNS) initial value space marching solution technique has been applied to a class of separate flow problems within a diffusing S-duct configuration characterized as vortex-liftoff. Both Full Navier-Stokes and Reduced Navier-Stokes solution techniques were able to capture the overall flow physics of vortex lift-off, however more consideration must be given to the development of turbulence models for the prediction of the locations of separation and reattachment. This accounts for some of the discrepancies in the prediction of the relevant inlet distortion descriptors, particularly circumferential distortion. The 3D RNS solution technique adequately described the topological structure of flow separation associated with vortex lift-off.

Anderson, B. H.↗

Generative AI models for learning flow maps of stochastic dynamical systems in bounded domains

Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeling of interior stochastic dynamics and boundary interactions. Despite the success of machine learning-based methods in learning SDEs, existing learning methods are not applicable to SDEs in bounded domains because they cannot accurately capture the particle exit dynamics. We present a unified hybrid data-driven approach that combines a conditional diffusion model with an exit prediction neural network to capture both interior stochastic dynamics and boundary exit phenomena. Our ML model consists of two major components: a neural network that learns exit probabilities using binary cross-entropy loss with rigorous convergence guarantees, and a training-free diffusion model that generates state transitions for non-exiting particles using closed-form score functions. The two components are integrated through a probabilistic sampling algorithm that determines particle exit at each time step and generates appropriate state transitions. Here, the performance of the proposed approach is demonstrated via three test cases: a one-dimensional simplified problem for theoretical verification, a two-dimensional advection-diffusion problem in a bounded domain, and a three-dimensional problem of interest to magnetically confined fusion plasmas.

Bounded domains↗

Two-Level Least Squares Methods in Krylov Subspaces

Two-level least squares acceleration approaches are applied to the Chebyshev acceleration method and the restarted conjugate residual method in solving systems of linear algebraic equations with sparse unsymmetric coefficient matrices arising from finite volume or finite element approximations of boundary-value problems on irregular grids. Application of the proposed idea to other iterative restarted processes also is considered. The efficiency of the algorithms suggested is investigated numerically on a set of model Dirichlet problems for the convection-diffusion equation.

97 MATHEMATICS AND COMPUTING↗

FuseIM: Fusing Probabilistic Traversals for Influence Maximization on Exascale Systems

Probabilistic breadth-first traversals (BPTs) are used in many network science and graph machine learning applications. In this paper, we are motivated by the application of BPTs in stochastic diffusion-based graph problems such as influence maximization. These applications heavily rely on BPTs to implement a Monte-Carlo sampling step for their approximations. Given the large sampling complexity, stochasticity of the diffusion process, and the inherent irregularity in real-world graph topologies, efficiently parallelizing these BPTs remains significantly challenging. In this paper, we present a new algorithm to fuse massive number of concurrently executing BPTs with random starts on the input graph. Our algorithm is designed to fuse BPTs by combining separate traversals into a unified frontier on distributed multi-GPU systems. To show the general applicability of the fused BPT technique, we have incorporated it into two state-of-the-art influence maximization parallel implementations (gIM and Ripples). Our experiments on up to 4K nodes of the OLCF Frontier supercomputer (32,768 GPUs and 196K CPU cores) show strong scaling behavior, and that fused BPTs can improve the performance of these implementations up to 34x (for gIM) and ~360x (for Ripples).

Neff, Reece W.↗

Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems

We develop a framework for goal-oriented optimal design of experiments (GOODE) for large-scale Bayesian linear inverse problems governed by PDEs. This framework differs from classical Bayesian optimal design of experiments (ODE) in the following sense: we seek experimental designs that minimize the posterior uncertainty in the experiment end-goal, e.g. a quantity of interest (QoI), rather than the estimated parameter itself. This is suitable for scenarios in which the solution of an inverse problem is an intermediate step and the estimated parameter is then used to compute a QoI. In such problems, a GOODE approach has two benefits: the designs can avoid wastage of experimental resources by a targeted collection of data, and the resulting design criteria are computationally easier to evaluate due to the often low-dimensionality of the QoIs. We present two modified design criteria, A-GOODE and D-GOODE, which are natural analogues of classical Bayesian A- and D-optimal criteria. We analyze the connections to other ODE criteria, and provide interpretations for the GOODE criteria by using tools from information theory. Then, we develop an efficient gradient-based optimization framework for solving the GOODE optimization problems. Additionally, we present comprehensive numerical experiments testing the various aspects of the presented approach. The driving application is the optimal placement of sensors to identify the source of contaminants in a diffusion and transport problem. As a result, we enforce sparsity of the sensor placements using an L1-norm penalty approach, and propose a practical strategy for specifying the associated penalty parameter.

97 MATHEMATICS AND COMPUTING↗

The mobility and diffusion of ions in gases

Experimental and theoretical aspects of the mobility and diffusion of ions in gases are studied in detail. Some of the subjects discussed include ion-ion interaction, boundary condition and ion and electron behavior. Also discussed in separate chapters are the problems of the diffusion coefficients and the afterglow techniques. Finally, a special chapter studies the kinetic theory of diffusion and mobility, stressing the low-, medium- and high-field theory.

Mcdaniel, E. W.↗

Theoretical investigations of plasma processes in the ion bombardment thruster

A physical model for a thruster discharge was developed, consisting of a spatially diverging plasma sustained electrically between a small ring cathode and a larger ring anode in a cylindrical chamber with an axial magnetic field. The associated boundary-value problem for the coupled partial differential equations with mixed boundary conditions, which describe the electric potential and the plasma velocity fields, was solved in closed form. By means of quantum-mechanical perturbation theory, a formula for the number S(E) of atoms sputtered on the average by an ion of energy E was derived from first principles. The boundary-value problem describing the diffusion of the sputtered atoms through the surrounding rarefied electron-ion plasma to the system surfaces of ion propulsion systems was formulated and treated analytically. It is shown that outer boundary-value problems of this type lead to a complex integral equation, which requires numerical resolution.

Wilhelm, H. E.↗

ASCEND: Asymptotically compatible strong form foundations for nonlocal discretization

Nonlocal models naturally handle a range of physics of interest to SNL, but discretization of their underlying integral operators poses mathematical challenges to realize the accuracy and robustness commonplace in discretization of local counterparts. This project focuses on the concept of asymptotic compatibility, namely preservation of the limit of the discrete nonlocal model to a corresponding well-understood local solution. We address challenges that have traditionally troubled nonlocal mechanics models primarily related to consistency guarantees and boundary conditions. For simple problems such as diffusion and linear elasticity we have developed complete error analysis theory providing consistency guarantees. We then take these foundational tools to develop new state-of-the-art capabilities for: lithiation-induced failure in batteries, ductile failure of problems driven by contact, blast-on-structure induced failure, brittle/ductile failure of thin structures. We also summarize ongoing efforts using these frameworks in data-driven modeling contexts. This report provides a high-level summary of all publications which followed from these efforts.

97 MATHEMATICS AND COMPUTING↗

Modeling Mesoscale Processes of Scalable Synthesis (Final Report)

The main objective of the center is to develop tools that can help for the understanding of equilibrium and non-equilibrium properties of nanoparticles in aqueous electrolytes. To achieve this goal, we need to develop new computational methodologies that can integrate molecular level description such as the electronic structure analysis to mesoscale description such as generalized hydrodynamics. The challenge is to develop systematic coarse graining techniques that can adaptively choose the level of description needed for the particular task. For example, if bonding breaking is involved, then one should use appropriate models from quantum mechanics to accurately model the time scale and molecular mechanism for the breaking process. However, to model transport process or the process of self-assembly, much less detailed models can be used. There are two main components to this task. One is to develop accurate models that bridge different levels of description. The classical example is the QM/MM model that bridges quantum mechanics and molecular mechanics for studying chemical reactions of large molecules. This work was awarded the Nobel prize this year. For our purpose, we also need to develop methods that bridge molecular and continuum levels of description. Another main task is to develop systematic coarse-graining methods that can give rise to accurate mesoscale and macroscale models, starting from more detailed models at the atomic or molecular scale. None of these ideas are new. By now they have been fashionable topics for quite some time. But neither problem is satisfactorily resolved. The main problem is that uncontrolled approximations are used. As a result, we have very little idea about the validity and accuracy of these models. The main purpose of the center is to exploit the Mori-Zwanzig formalism to achieve the goals stated above. The Mori-Zwanzig formalism is a general tool for eliminating degrees of freedom from existing models. What is attractive about this formalism is its generality. The flip side is that it is also somewhat of a tautology. In order to make it a practical tool, one has to make approximations and this is where the trouble comes. Instead of focusing on Mori-Zwanzig formalism, the PI proposes to study the closely related renormalization group formalism (RG). Like Mori-Zwanzig, RG is a general strategy for eliminating small scale degrees of freedom in a model. Unlike Mori-Zwanzig, RG has the advantage that at least for some problems, one can write a PDE (partial differential equation) type of model for the exact RG flow, without any approximation. This gives us a solid starting point for discussing and analyzing approximations. The PI studied approximate RG flows for turbulent diffusion and related problems. However, extending it to more practical problems proved to be hard. The second line that the PI has pursued is to develop special numerical algorithms for studying particularly important events for dynamics processes in meso-scale systems. The PI succeeded in doing so for the problem of understanding phase transition in metallic systems.

97 MATHEMATICS AND COMPUTING↗