THE SCHOOL OF MATERIALS SCIENCE AND ENGINEERING

GEORGIA INSTITUTE OF TECHNOLOGY

Under the provisions of the regulations for the degree

DOCTOR OF PHILOSOPHY

on Friday, July 17, 2020

1:00 PM
via

BlueJeans Video Conferencing

https://gatech.bluejeans.com/736230983

will be held the

DISSERTATION DEFENSE

for

Eric Hoar

"Materials-Affected Manufacturing: Simulating the Microstructure Evolution of Metal Alloys Through Processing”

Committee Members:

Prof. Hamid Garmestani, Advisor, MSE

Prof. Steven Liang, ME

Prof. Chaitanya Deo, NRE

Prof. Surya Kalidindi, ME/MSE

Prof. Naresh Thadhani, MSE

Abstract:

Three microstructural evolution models are developed and presented which utilize different processing techniques, microstructural features, and modeling technique for forward or inverse modeling.  The first model is an inverse model capable of predicting the initial microstructure required to obtain a desired final microstructure for use in nuclear forensics applications.  This inverse model describes the microstructure evolution of a monotectoid Zr-18wt.%Nb alloy by specifying the crystallographic orientation of the bcc beta-phase ZrNb.  By modeling the evolution of the crystallographic orientation the model attempts to provide information on how the material was processed and a framework which allows for the optimization of the mechanical material properties.  The second model is a forward model which utilizes two-point correlation functions to describe the phase distribution of the dual phase Ti-6Al-4V alloy in order to predict the final microstructure obtained after a known initial microstructure undergoes a specified processing procedure.  This model uses statistical continuum theory to describe the deformation of the two-point correlation functions and reconstructs the deformed statistics by systematic deformation of the initial two-point correlation function.  The last model is an inverse model which predicts the initial microstructure required to obtain a desired final microstructure using the two-point correlation functions described in the second model.  This model attempts to provide a computational model capable of providing optimization of material microstructure and thus mechanical properties for industrial applications.  Ultimately, the goal of these models is to reduce the industrial requirement of trial-and-error experiments for the development of new processing procedures and provide an avenue for the development of these new procedures through computational simulations.