Publications

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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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Conductive transport in heterogeneous materials composed of discrete particles is a fundamental problem for a number of applications. While analytical results and rigorous bounds on effective conductivity in mono-sized particle dispersions are well established in the literature, the methods used to arrive at these results often fail when the average size of particle clusters becomes large (i.e., near the percolation transition where particle contact networks dominate the bulk conductivity). Our aim is to develop general, efficient numerical methods that would allow us to explore this behavior and compare to a recent microstructural description of conduction in this regime. To this end, we present a finite element analysis approach to modeling heat transfer in granular media with the goal of predicting effective bulk thermal conductivities of particle-based heterogeneous composites. Our approach is verified against theoretical predictions for random isotropic dispersions of mono-disperse particles at various volume fractions up to close packing. Finally, we present results for the probability distribution of the effective conductivity in particle dispersions generated by Brownian dynamics, and suggest how this might be useful in developing stochastic models of effective properties based on the dynamical process involved in creating heterogeneous dispersions. © 2013 AIP Publishing LLC.

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Goma 6.0 is a finite element program which excels in analyses of multiphysical processes, particularly those involving the major branches of mechanics (viz. fluid/solid mechanics, energy transport and chemical species transport). Goma is based on a full-Newton-coupled algorithm which allows for simultaneous solution of the governing principles, making the code ideally suited for problems involving closely coupled bulk mechanics and interfacial phenomena. Example applications include, but are not limited to, coating and polymer processing flows, super-alloy processing, welding/soldering, electrochemical processes, and solid-network or solution film drying. This document serves as a user's guide and reference.

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A Conformal Decomposition Finite Element Method (CDFEM) is developed for modeling material death. Material death is used to model the continuous removal of material that exceeds a prescribed temperature. CDFEM allows for the moving front to move through the material without having to conform to the finite element geometry. The method is tested using 2-dimensional simulations of a 1-dimensional problem with an analytical solution. CDFEM is shown to be optimal for the chosen discretization with first order convergence in time and second order convergence in space. In comparison, a traditional element death algorithm does not converge at all on unstructured meshes. A correction is proposed for remedying this problem, resulting in first order convergence for traditional element death in space and time. Copyright © 2012 by ASME.