My primary research focus is on modeling the deformation of crystalline solids to determine the relationship between a material’s microscopic structure and it’s response to mechanical loading at both the microscopic and macroscopic scales. Understanding of this relationship is critical in modern design of engineering components with existing materials, as well as aiding in future material design. Computational simulations provide a rapid and relatively inexpensive way to determine the deformation response of a particular material and microstructure, as well as a framework for models that describe the physical response of the material. As such, my research follows two paths: the use of novel methods to represent microstructures and determine their effects on a material’s deformation response, and the formation and implementation of new deformation models. Both paths require close collaborations with experimentalists to identify interesting problems, and to ensure proper material modeling.
To determine important features of a material, I work with experimentalists and use data from a number of experimental techniques. This contributes to an accurate representation of simulated polycrystals on multiple levels. Important features of a material’s microstructure are identified through data obtained from experiment’s that elucidate the geometric structure of materials (optical microscopy, high energy X-ray diffraction, 2D/2D electron backscatter diffraction). Distributions of crystallographic orientations are also obtained through various experimental techniques (high energy X-ray diffraction, 2D/2D electron backscatter diffraction). Other tests (macroscopic mechanical testing, high energy X-ray diffraction, scanning electron microscopy with digital image correlation) lend insight into macroscopic and microscopic deformation responses.
These data feed into both research paths. Concerning the representation of microstructures, geometric characterization data inform bulk features such as grain size, grain size distributions, and grain shape, which are controlled through the use of Voronoi/Laguerre tessellations. Additionally, fine features such as thermomechanical transformation structures and dual-phase geometric morphologies may be represented through more complex multilevel tessellation approaches. Tessellation methods allow for studies on geometric parameters’ influences on a material’s response due to the ability to parameterize geometric features, as well as the rapid generation of unique microstructures. Additionally, data on orientations distributions are used to generate representative orientation sets, as well as represent interesting processing phenomena such as microtexturing. Again, orientation distributions and enforcement/non-enforcement of microtexturing may be parameterized for rapid simulated studies.
Macroscopic and microscopic deformation data are used to both tune model parameters and determine the sensitivity of various metric to changes in model parameters. Additionally, simulated data allows for the comparison to specific measured variables, with the added benefit of the ability to track variables not measured by experiments (often due to experimental limitations), explaining the evolution of deformation in ways that experiments cannot. This may, conversely, expose the influence of various phenomena that may not be explicitly modeled – informing the scope and ability of deformation models.
Specifically, I’ve participated in studies on various microstructural variants of titanium alloys, as well as geological materials using the above described methods, and have developed a new model to approach the challenge of deformation induced crystallographic twinning. The pages below outline specific projects in detail.