Credible, Automated Meshing of Images (CAMI)
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The subject of this work is the development of models for the numerical simulation of matter, momentum, and energy balance in heterogeneous materials. These are materials that consist of multiple phases or species or that are structured on some (perhaps many) scale(s). By computational mechanics we mean to refer generally to the standard type of modeling that is done at the level of macroscopic balance laws (mass, momentum, energy). We will refer to the flow or flux of these quantities in a generalized sense as transport. At issue here are the forms of the governing equations in these complex materials which are potentially strongly inhomogeneous below some correlation length scale and are yet homogeneous on larger length scales. The question then becomes one of how to model this behavior and what are the proper multi-scale equations to capture the transport mechanisms across scales. To address this we look to the area of generalized stochastic process that underlie the transport processes in homogeneous materials. The archetypal example being the relationship between a random walk or Brownian motion stochastic processes and the associated Fokker-Planck or diffusion equation. Here we are interested in how this classical setting changes when inhomogeneities or correlations in structure are introduced into the problem. Aspects of non-classical behavior need to be addressed, such as non-Fickian behavior of the mean-squared-displacement (MSD) and non-Gaussian behavior of the underlying probability distribution of jumps. We present an experimental technique and apparatus built to investigate some of these issues. We also discuss diffusive processes in inhomogeneous systems, and the role of the chemical potential in diffusion of hard spheres is considered. Also, the relevance to liquid metal solutions is considered. Finally we present an example of how inhomogeneities in material microstructure introduce fluctuations at the meso-scale for a thermal conduction problem. These fluctuations due to random microstructures also provide a means of characterizing the aleatory uncertainty in material properties at the mesoscale.
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Imported oil exacerabates our trade deficit and funds anti-American regimes. Nuclear Energy (NE) is a demonstrated technology with high efficiency. NE's two biggest political detriments are possible accidents and nuclear waste disposal. For NE policy, proliferation is the biggest obstacle. Nuclear waste can be reduced through reprocessing, where fuel rods are separated into various streams, some of which can be reused in reactors. Current process developed in the 1950s is dirty and expensive, U/Pu separation is the most critical. Fuel rods are sheared and dissolved in acid to extract fissile material in a centrifugal contactor. Plants have many contacts in series with other separations. We have taken a science and simulation-based approach to develop a modern reprocessing plant. Models of reprocessing plants are needed to support nuclear materials accountancy, nonproliferation, plant design, and plant scale-up.
Solidification and blood flow seemingly have little in common, but each involves a fluid in contact with a deformable solid. In these systems, the solid-fluid interface moves as the solid advects and deforms, often traversing the entire domain of interest. Currently, these problems cannot be simulated without innumerable expensive remeshing steps, mesh manipulations or decoupling the solid and fluid motion. Despite the wealth of progress recently made in mechanics modeling, this glaring inadequacy persists. We propose a new technique that tracks the interface implicitly and circumvents the need for remeshing and remapping the solution onto the new mesh. The solid-fluid boundary is tracked with a level set algorithm that changes the equation type dynamically depending on the phases present. This novel approach to coupled mechanics problems promises to give accurate stresses, displacements and velocities in both phases, simultaneously.
Processes that involve particle-laden fluids are common in geomechanics and especially in the petroleum industry. Understanding the physics of these processes and the ability to predict their behavior requires the development of coupled fluid-flow and particle-motion computational methods. This paper outlines an accurate and robust coupled computational scheme using the lattice-Boltzmann method for fluid flow and the discrete-element method for solid particle motion. Results from several two-dimensional validation simulations are presented. Simulations reported include the sedimentation of an ellipse, a disc and two interacting discs in a closed column of fluid. The recently discovered phenomenon of drafting, kissing, and tumbling is fully reproduced in the two-disc simulation.