<p>There is a growing need to understand the deformation mechanisms in titanium alloys due to their widespread use in the aerospace industry (especially within gas turbine engines), variation in their properties and performance based on their microstructure, and their tendency to undergo premature failure due to dwell and high cycle fatigue well below their yield strength. Crystal plasticity finite element (CPFE) modeling is a popular computational tool used to understand deformation in these polycrystalline alloys. With the advancement in experimental techniques such as electron backscatter diffraction, digital image correlation (DIC) and high-energy x-ray diffraction, more insights into the microstructure of the material and its deformation process can be attained. This research leverages data from a number of experimental techniques to develop well-informed and calibrated CPFE models for titanium alloys at multiple length-scales and use them to further understand the deformation in these alloys.</p> <p>The first part of the research utilizes experimental data from high-energy x-ray diffraction microscopy to initialize grain-level residual stresses and capture the correct grain morphology within CPFE simulations. Further, another method to incorporate the effect of grain-level residual stresses via geometrically necessary dislocations obtained from 2D material characterization is developed and implemented within the CPFE framework. Using this approach, grain level information about residual stresses obtained spatially over the region of interest, directly from the EBSD and high-energy x-ray diffraction microscopy, is utilized as an input to the model.</p> <p>The second part of this research involves calibrating the CPFE model based upon a systematic and detailed optimization routine utilizing experimental data in the form of macroscopic stress-strain curves coupled with lattice strains on different crystallographic planes for the α and β phases, obtained from high energy X-ray diffraction experiments for multiple material pedigrees with varying β volume fractions. This fully calibrated CPFE model is then used to gain a comprehensive understanding of deformation behavior of Ti-6Al-4V, specifically the effect of the relative orientation of the α and β phases within the microstructure.</p> <p>In the final part of this work, large and highly textured regions, referred to as macrozones or microtextured regions (MTRs), with sizes up to several orders of magnitude larger than that of the individual grains, found in dual phase Titanium alloys are modeled using a reduced order simulation strategy. This is done to overcome the computational challenges associated with modeling macrozones. The reduced order model is then used to investigate the strain localization within the microstructure and the effect of varying the misorientation tolerance on the localization of plastic strain within the macrozones.</p>

<p>With the emergence of additive manufacturing (AM), there is a need to understand the role of microstructures resulting from AM on the mechanical performance of the material. Ti-6Al-4V alloys are widely used within the aerospace industry as well as other industries to achieve high strength, low weight premium performance parts. There is a desire to utilize AM to produce Ti-6Al-4V, although these materials need to be qualified prior to their use in safety critical applications. Within the qualification of AM Ti-6Al-4V in aeronautics, fatigue loading is a crucial aspect to. It has been seen that within AM Ti-6Al-4V, prior β boundaries can be locations of microscopic localization of plastic strain which often lead to fatigue crack initiation. This thesis aims to further understand and predict the role of AM Ti-6Al-4V microstructures in dictating fatigue behavior. Specifically, the goal was to gauge the contributions of two microstructural features resulting from AM, prior β boundaries and α lathe-shaped grains, to the localization behavior. With the need to understand and predict the emergent behavior of the material system, crystal plasticity finite element (CPFE) methods were used in this thesis as the main method. </p> <p><br></p> <p>Within the context of CPFE, there is an existing gap in the current literature of realistic synthetic microstructures of Ti-6Al-4V that capture both the prior β boundaries and α lathes. With the ability to generate realistic FE models, the effects of the microstructural features can be better studied and characterized. The first portion of this thesis focuses on the generation of such synthetic microstructures which are simulated within the CPFE framework. An emphasis is placed on modeling the prior β boundaries and α grains. As these generated models are statistically equivalent to actual microstructures, material characterization via EBSD was performed on specimen that were used in the experimental fatigue testing. With the framework’s ability to generate synthetic microstructures that consider one prior β grain or multiple β grains (and thus prior β boundaries), simulations were conducted on both conditions of microstructures. </p> <p><br></p> <p>In the second portion of this thesis, simulations are conducted on two conditions of synthetic microstructures: models which contain 𝛼 lathes associated with one prior 𝛽 grain and models which contain multiple prior 𝛽 boundaries and the respective 𝛼 lathes. The goals of the simulations included: (1) lifing the different synthetic microstructures using a fatigue lifing model by way of the accumulated plastic strain energy density (APSED), (2) analyzing the microscopic localization of APSED at the prior β boundaries, and (3) analyzing the effects of the α lathes on the microscopic localization. This investigation aimed to further shed light on the effects of the additive manufacturing process and the implications of the resulting microstructure on the fatigue properties of AM Ti-6Al-4V. Furthermore, physics-based prognosis strategies similar to what is employed here will enable the rapid qualification of materials/structures and the ability to tailor component design on fatigue performance. </p>