Development of an automated characterization-representation framework for the modeling of polycrystalline materials in three dimensions

Over the past few years there have been significant advances in developing microstructure characterization methods that provide quantitative data describing the structure and crystallography of grain-level microstructures in three dimensions (3D). This work utilizes one such method, serial sectioning, with a focus on the automation of the process. The subsequent analysis and representation of the collected information can provide modeling and simulation efforts with a highly-refined and unbiased characterization of specific microstructural features. The grain structure of an engineering alloy could be translated directly into a 3D volume mesh for subsequent Finite Element (FE) analysis. However, this approach requires a multitude of data sets in order to appropriately sample the intrinsic heterogeneity observed in typical microstructures. In order to circumvent this issue, computation tools can be used to create synthetic microstructures that are statistically-equivalent to the measured structure. This manuscript will focus on the automation of the data collection process, the subsequent processing of the data, the robust quantitative characterization of the 3D structure, and the development of software programs that generate a host of synthetic structures which are analogous to the real material. Finally, this thesis will introduce new methods for inferring the 3D structure of a microstructure from only 2D sections. Importantly, the objective of this study is to provide a framework towards complete microstructure representation that is consistent with quantifiable experimental data.