SUBJECT: Ph.D. Proposal Presentation
BY: Ushasi Roy
TIME: Monday, February 4, 2019, 4:00 p.m.
PLACE: MRDC Building, 4211
TITLE: Microstructure Sensitive Multiscale Modelling of Fracture in Polycrystalline Metals
COMMITTEE: Dr. Min Zhou, Chair (ME)
Dr. David McDowell (ME)
Dr. Ting Zhu (ME)
Dr. Antonia Antoniou (ME)
Dr. Yavari Arash (CE)


The primary aim of this research is to predict the fracture behavior of ductile materials as functions of their microstructure. We develop a multiscale cohesive finite element based computational framework for predicting the macro-scale fracture measures such as the KIC, JIC of polycrystalline metals as functions of microstructural attributes. The computational approach involves embedding a microstructure region around the crack tip of a compact tension (CT) specimen subjected to mode-I loading. To track different mechanisms of crack propagation, an orientation sensitive cohesive model is implemented in the microstructure region, while the outer region uses a homogenized model. The framework allows exploration of the effect of microstructure on the macroscopic fracture measures and crack propagation mechanisms. It also captures the competition between (a) plasticity and fracture, and (b) intergranular and transgranular fracture mechanisms. The use of multiple statistically similar microstructures takes into account the stochasticity of fracture. Multiple characteristics of the microstructures like the grain size, texture are varied to establish a microstructure-fracture toughness correlation. Analytical models for predicting fracture toughness and micro-mechanisms of fracture will be taken up in future. This work would be concluded with an extension of this 2D framework into 3D along with crystal plasticity formulation in order to model plasticity considering most of its complexities simultaneously with fracture. Finally, the model would have the capabilities to predict the fracture behavior in polycrystalline elastic-plastic materials like metals as functions of microstructural attributes.