Professor Nicholas Zabaras "Predictive Materials Science: Information Theoretic Approach"
Date: Thu 16 Feb 2012, 09:30 - 10:15
Location: SEMS Seminar Room
Prof Nicholas Zabaras, Materials Process Design and Control Laboratory, Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14850-9470 USA
We will briefly discuss a number of fundamental problems in predictive materials modeling to account for uncertainties in models, microstructure data, and coarse graining. As an example, we will introduce predictive multiscale models for deformation processes of polycrystalline materials. We will address methods for quantifying uncertainty in polycrystal microstructures and computing the probability distribution of the observed macroscale properties. A surrogate reduced order stochastic model will be introduced to address location-dependence of microstructures. A multiscale forging problem will be discussed to study the effects of uncertain initial grain size distribution and texture on the macroscopic properties. To address issues of complexity, we will finally pose multiscale stochastic problems as inference problems in graphs.