MCE Ph.D. Thesis Seminar

Granular materials are ubiquitous in both everyday life and various engineering and industrial applications, ranging from breakfast cereal to sand to rice to pills.  But despite the familiarity of granular materials, their behavior is complex and efforts to characterize it are currently broad research areas in physics and engineering.  Research of granular materials, as is the case with the research of other engineering materials such as rocks and metals, is beset with two gaps: the gap between reconciling macroscopic behavior with microscale—or particle-scale, in the case of granular materials—behavior, and the gap between reconciling experimental and computational results.  In this dissertation, we bridge these gaps through the "avatar paradigm.''  The avatar paradigm is a two-step process that numerically characterizes—from experimental images—and simulates the shapes and behavior of individual particles, which we call avatars.  First, we validate that our avatars are indeed capable of faithfully capturing particle kinematics and interparticle contact, then apply the characterization process, level set imaging (LS-imaging), to two experimental specimens to compute particle kinematics and contact statistics.  Then, we detail a computational method, the level set discrete element method (LS-DEM), that is able to simulate the behavior of avatars, and apply it (and LS-imaging) to two other experimental specimens, calibrating the model to one specimen and using the results to predict the behavior of the other, thus providing some reconciliation between experimental and computational results.  Finally, we use the avatar process to characterize and simulate yet another experimental specimen, this time analyzing the results at length scales ranging from particle behavior to local behavior to macroscopic behavior, further validating the ability of the avatar paradigm to bridge experiments and computations and showing its power to reconcile different length scales.