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George W. Woodruff School of Mechanical Engineering

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College of Engineering

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Advanced Mechanical Bipedal Experimental Robotics Lab

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Computational Reactor and Medical Physics Laboratory

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Cryo Lab

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Environmentally Conscious Design and Manufacturing

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Fusion Research Center

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Publication Search Results

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Multiscale Modeling of Hydrogen Embrittlement

(Georgia Institute of Technology, 2022-04-04) Zirkle, Theodore

Hydrogen embrittlement is a long-standing issue in materials science and engineering with a multitude of competing hypotheses and theories. Despite advances in experimental and computational capabilities, common understanding of contributing phenomena has not yet been achieved. Hence, a more complete understanding of hydrogen embrittlement processes operating at multiple length and time scales is still an open challenge that justifies the current research. In this thesis, a unique approach is taken to incorporate a wide range of experimental, computational, and analytical approaches across multiple length scales to produce a mechanistically motivated hydrogen embrittlement model for fracture and fatigue. This research describes and simulates the complex interplay between hydrogen, hydrogen-related defects, dislocations, and dislocation substructures. The model is developed in a crystal plasticity context and implemented in a finite element framework to simulate the hydrogen embrittlement of austenitic stainless steels, structural materials important in energy applications. The proposed research extends current understanding through the development of: i. a physically-based crystal plasticity model developed to capture the evolution of dislocation substructure and material behavior during cyclic loading, ii. a hydrogen transport and trapping model that considers dislocation-mediated transport mechanisms and a more complete set of hydrogen traps, and iii. a fully coupled chemo-mechanical model to capture the effects of hydrogen in reducing crack tip ductility, leading to embrittlement effects.
HIGH THROUGHPUT MECHANICAL PROPERTY CHARACTERIZATION OF STRUCTURAL ALLOYS USING SPHERICAL MICROINDENTATION

(Georgia Institute of Technology, 2021-07-27) Bhat, Anirudh Srinivas

Spherical indentation has been shown to be a reliable high throughput alternative to capture the complete elastic-plastic response of polycrystalline metal alloys when using the Pathak-Kalidindi (P-K) protocol. However, yielding initiates subsurface and due to the hydrostatic pressure associated with the constraint of the surrounding material, this occurs at a higher stress than it would for the same material under uniaxial load. Hence, the indentation stress is higher than uniaxial stress and the two are related by a scaling factor, referred to as the constraint factor. In the current work, some of the open questions in the use of spherical indentation to extract uniaxial stress-strain curves are addressed. The dependence of the mechanical properties of the material and the indentation strain on the constraint factor is investigated using FEA and experiments. Based on the P-K indentation strain definition, revisions are proposed to the classical equations for: 1) the representative uniaxial strain, which relates the indentation strain to an equivalent uniaxial strain and 2) the non-dimensional strain, which relates the indentation strain to the constraint factor. From these revised definitions, an inverse method has been developed using FEA simulations to estimate the uniaxial stress-strain from spherical indentation stress-strain curves. The inverse method is verified with FEA generated indentation stress-strain curves and experiments conducted on Al7050 and Al6061 samples of varying strengths and hardening behaviors. Finally, spherical indentation of a material exhibiting anisotropic mechanical response is studied. The uniaxial and spherical indentation mechanical response of samples of Inconel 718 that were additively manufactured using electron beam melting are critically evaluated. The variation of the experimentally obtained elastic spherical indentation response as a function of the orientation of the material is verified using FEA simulations.
Hydrogen effects on dislocation structures and interactions

(Georgia Institute of Technology, 2020-12-02) Costello, Luke L.

Hydrogen embrittlement (HE) is a complex process, in which the interactions of H atoms, vacancies, and dislocations lead to a macroscopic loss of ductility. Although this phenomenon is commonly observed, its microscopic origins remain unclear. In this thesis we study the process of HE, starting from the microscale, using atomistic simulations and modeling to connect with higher length scales. Passing information from physically realistic atomic scale simulations allows for improved understanding of the underlying mechanisms of H embrittlement and specifically how effects attributed to H contribute at the meso and macroscales. We study these contributions in three parts. First, a method for computing the distribution of H around an edge dislocation is presented and compared to an alternative approach. The presented method is then exercised in an example, studying the effect of H on the stacking fault width (SFW) of an extended edge dislocation. It is shown that H acts to decrease the SFW. Further, only the H very locally around and inside the dislocation cores and stacking fault contribute significantly to the observed decrease in the SFW. We then turn our focus to the role of H on the stabilization and clustering of vacancies. A new model is developed for the production of excess vacancies by plastic deformation. This model is integrated into an existing macroscale computational framework. Lastly, the role of H on the formation energy of vacancy clusters is studied using a hybrid molecular statics / Monte Carlo method. These calculations show that H tends to decrease the formation energy of vacancy clusters which leads to a decrease in the critical cluster size for void nucleation.
Effect of mesoscale inhomogeneities on planar shock response of materials

(Georgia Institute of Technology, 2017-04-28) Ferri, Brian Anthony

In all previous spall models, the source of spall failure in metals either comes from damage at the grain boundary or from void nucleation, growth, and coalescence. However, it has been observed in experiments that both phenomena occur in Aluminum 6061-T6, which is termed “combined failure” for the purposes of this thesis. Thus, the challenge undertaken in this thesis is to use a computational study to determine the role that each source of spall plays separately, and then in tandem to determine the traditional failure parameters for each source. The results of determining each failure model’s ideal parameters, which are representative of that source’s role in combined failure, is compared with data gathered from plate-flyer experiments to determine the accuracy of the model in both 1D and in 2D simulations. Sand is a heterogeneous granular material that has the capability of allowing a shock wave to propagate through it. The computational model and study presented in this thesis is phenomenologically similar, yet easier to conduct than a spall study on granular Aluminum. The study of sand using the same computational LS-DYNA method shows both an introduction to the process for completing the spall study on granular Aluminum, and it also yields interesting results in the wave phenomena as well as the effect of porosity on the average stress on the sand grains. With the conclusion of the sand study, the same process of creating the grain structure is applied to create the Aluminum grain structure for spall simulations, which are carried out in LS-DYNA using 2D cohesive elements. The results of the LS-DYNA Aluminum simulation are compared to both the 1D spall results as well as to the experimental data to determine model accuracy. The main findings from this thesis show that, first, a mutually exclusive combined failure linear relationship can be shown with the 1D simulation results, which gives insight into a method that could be used to choose a set of optimal failure parameters. Second, the 2D LS-DYNA homogeneous results had excellent agreement with the 1D homogeneous results, which gave confidence to the notion that the parametric studies in 1D simulations could be used to find parameter values that could be applied in the 2D models. Lastly, LS-DYNA was shown to be an effective way to simulate grain structure response to shock wave propagation and showed spall modeling was possible with 2D cohesive elements, which lays the groundwork for combined failure studies in 2D.
The concurrent atomistic-continuum method: Advancements and applications in plasticity of face-centered cubic metals

(Georgia Institute of Technology, 2016-11-09) Xu, Shuozhi

Metal plasticity is a multiscale phenomenon that is manifested by irreversible microstructure rearrangement associated with nucleation, multiplication, interaction, and migration of dislocations. Long range elastic interactions between dislocations and other crystal defects are important to describe, along with the nonlocal, nonlinear dislocation core field. These requirements necessitate multiscale modeling techniques which (i) describe certain lattice defects and their interactions using fully resolved atomistics, (ii) preserve the net Burgers vector and associated long range stress fields of curved mixed character dislocations in a sufficiently large continuum domain in a fully three-dimensional model, and (iii) employ the same governing equations and interatomic potentials in both atomistic and continuum domains to avoid the usage of phenomenological parameters/criteria and ad hoc procedures for passing dislocation segments between the two domains. One such approach is the concurrent atomistic-continuum (CAC) method. Unlike many other concurrent multiscale approaches, the continuum domain in CAC admits motion of dislocations and intrinsic stacking faults through a lattice without necessity of adaptive mesh refinement while employing an underlying interatomic potential as the only constitutive relation and is thus a suitable tool for dislocation-mediated metal plasticity phenomena. In this dissertation, the CAC method is advanced in multiple aspects and applied in a series of problems in plasticity of face-centered cubic (FCC) metals. First, four significant advancements in the CAC method have been made: (i) new types of finite elements are developed which yields a more accurate stacking fault energies and core structure in coarse-grained atomistic descriptions of dislocations, (ii) zero temperature, quasistatic CAC approaches are formulated to enable the constrained multiscale optimization for a sequence of non-equilibrium dislocation configurations in metals, (iii) mesh refinement schemes for both dynamic fracture and curved dislocation migration are implemented, and (iv) the code efficiency is improved using parallelized object-oriented programming. Subsequently, this enhanced CAC method is employed to study multiple plasticity problems in a variety of FCC metals, including screw dislocation cross-slip in Ni, edge dislocation bowing out from a row of collinear obstacles in Al, dislocation multiplication from Frank-Read sources in Cu, Ni, and Al, as well as sequential slip transfer of curved dislocations across a Σ3{111} coherent twin boundary and a Σ11{113} symmetric tilt grain boundary in Cu, Al, and Ni. This work makes significant contributions to the fields of mechanics of materials and multiscale modeling. It is anticipated that the finding in this dissertation will improve physical understanding of dislocation-mediated plastic deformation processes in FCC metals and may assist in formulating constitutive laws and rules used in computational techniques at higher length scales.
Exploration of forward and inverse protocols for property optimization of Ti-6Al-4V

(Georgia Institute of Technology, 2016-07-26) Priddy, Matthew William

The modeling and simulation of advanced engineering materials undergoing mechanical loading requires accurate treatment of relevant microstructure features, such as grain size and crystallographic texture, to determine the heterogeneous response to deformation. However, many models constructed for this purpose are not being fully realized in their predictive capability. Additionally, physics-based models can be combined with bottom-up deductive mappings and top-down inductive decision paths to increase their utility in materials selection and optimization. However, connecting these types of models or algorithms with experiments, rapid inverse property/response estimates, and design decision-making via integrated workflows has yet to become well-established for materials design and/or development. One material system primed for this type of concurrent advancement is alpha+beta titanium alloys, because its resultant microstructure and mechanical properties are highly dependent on material processing and composition. This dissertation seeks to advance a materials design process for fatigue resistance, strength, and elastic stiffness of Ti-6Al-4V through the advancement of various computational tools, as well as the integration of simulation-based tools and high-throughput experimental datasets. The microstructure-sensitive crystal plasticity finite element method (CPFEM) is utilized to explicitly account for the grain structure and crystallographic texture of Ti-6Al-4V. To improve the predictive capability of the CPFEM model, high throughput spherical indentation experimental datasets are used for model calibration because of their ability to extract elastic and plastic individual phase and grain properties from multiphase materials such as titanium alloys. The CPFEM can be used to capture the microstructure heterogeneity on fatigue crack driving forces, but these types of simulations are computationally expensive. Instead, an explicit integration of the relevant constitutive relations in the CPFEM model are combined with the materials knowledge system (MKS) approach for generating spatially local results of polycrystalline materials. These bottom-up simulation methods provide macroscopic properties from microstructure-level model inputs. For materials design, it is important to determine the inverse -- microstructure-level information from the macroscopic response -- which is referred to as top-down modeling. The Inductive Design Exploration Method (IDEM) offers a systematic approach to combining bottom-up simulations with top-down inductive design search. In this dissertation, a generalized framework of the IDEM is implemented to assess multi-objective design scenarios specific to the microstructure-sensitive datasets generated in this work.Th e general approach presented in this dissertation integrates CPFEM simulations with experimental spherical indentation for model refinement and also combines CPFEM with the MKS for computational-efficient generation of local quantities. These advancements are the basis for accelerated decision-support for materials design exploration when merged with the IDEM. Although performed with alpha+beta titanium, individual elements of the framework can be applied to a variety of engineering alloys for tasks such as extraction of model parameters from spherical indentation experiments, coupling MKS with crystal plasticity constitutive relations, and performing a top-down inductive design search with polycrystalline datasets.
Improvements to the computational pipeline in crystal plasticity estimates of high cycle fatigue of microstructures

(Georgia Institute of Technology, 2016-05-02) Kern, Paul Calvin

The objective of this work is to provide various improvements to the modeling and uncertainty quantification of fatigue lives of materials as understood via simulation of crystal plasticity models applied to synthetically reconstructed microstructures. A computational framework has been developed to automate standardized analysis of crystal plasticity models in the high cycle fatigue regime. This framework incorporates synthetic microstructure generation, simulation preparation, execution and post-processing to analysis statistical distributions related to fatigue properties. Additionally, an improved crack nucleation and propagation approach has been applied to Al 7075-T6 to improve predictive capabilities of the crystal plasticity model for fatigue in various loading regimes. Finally, sensitivities of fatigue response to simulation and synthetic microstructure properties have been explored to provide future guidance for the study of fatigue quantification based on crystal plasticity models.
Modeling microstructurally small crack growth in Al 7075-T6

(Georgia Institute of Technology, 2015-07-22) Hennessey, Conor Daniel

Fatigue of metals is a problem that affects almost all sectors of industry, from energy to transportation, and failures to account for fatigue or incorrect estimations of service life have cost many lives. To mitigate such fatigue failures, engineers must be able to reliably predict the fatigue life of components under service conditions. Great progress has been made in this regard in the past 40 years; however one aspect of fatigue that is still being actively researched is the behavior of microstructurally small cracks (MSCs), which can diverge significantly from that of long cracks. The portion of life spent nucleating and growing a MSC over the first few grains/phases can consume over 90% of the total fatigue life under High Cycle Fatigue (HCF) conditions and is the primary source of the scatter in fatigue lives. Therefore, the development of robust fatigue design methodologies requires that the MSC regime of crack growth can be adequately modeled. The growth of microstructurally small cracks is dominated by influence of the local heterogeneity of the microstructure and is a highly complex process. In order to successfully model the growth of these microstructurally small cracks (MSCs), two computational frameworks are necessary. First, the local behavior of the material must be modeled, necessitating a constitutive relation with resolution on the scale of grain size. Second, a physically based model for the nucleation and growth of microstructurally small fatigue cracks is needed. The overall objective of this thesis is best summarized as the introduction these two computational frameworks, a crystal plasticity constitutive model and fatigue model, specifically for aluminum alloy 7075-T6, a high-strength, low density, precipitation hardened alloy used extensively in aerospace applications. Results are presented from simulations conducted to study the predicted crack growth under a variety of loading conditions and applied strain ratios, including uniaxial tension-compression and simple shear at a range of applied strain amplitudes. Results from the model are compared to experimental results obtained by other researchers under similar loading conditions. A modified fatigue crack growth algorithm that captures the early transition to Stage II growth in this alloy will also be presented.
Cross-scale model validation with aleatory and epistemic uncertainty

(Georgia Institute of Technology, 2015-04-13) Blumer, Joel David

Nearly every decision must be made with a degree of uncertainty regarding the outcome. Decision making based on modeling and simulation predictions needs to incorporate and aggregate uncertain evidence. To validate multiscale simulation models, it may be necessary to consider evidence collected at a length scale that is different from the one at which a model predicts. In addition, traditional methods of uncertainty analysis do not distinguish between two types of uncertainty: uncertainty due to inherently random inputs, and uncertainty due to lack of information about the inputs. This thesis examines and applies a Bayesian approach for model parameter validation that uses generalized interval probability to separate these two types of uncertainty. A generalized interval Bayes’ rule (GIBR) is used to combine the evidence and update belief in the validity of parameters. The sensitivity of completeness and soundness for interval range estimation in GIBR is investigated. Several approaches to represent complete ignorance of probabilities’ values are tested. The result from the GIBR method is verified using Monte Carlo simulations. The method is first applied to validate the parameter set for a molecular dynamics simulation of defect formation due to radiation. Evidence is supplied by the comparison with physical experiments. Because the simulation includes variables whose effects are not directly observable, an expanded form of GIBR is implemented to incorporate the uncertainty associated with measurement in belief update. In a second example, the proposed method is applied to combining the evidence from two models of crystal plasticity at different length scales.
Modeling the effects of shot-peened residual stresses and inclusions on microstructure-sensitive fatigue of Ni-base superalloy components

(Georgia Institute of Technology, 2014-04-28) Musinski, William D.

The simulation and design of advanced materials for fatigue resistance requires an understanding of the response of their hierarchical microstructure attributes to imposed load, temperature, and environment over time. For Ni-base superalloy components used in aircraft jet turbine engines, different competing mechanisms (ex. surface vs. subsurface, crystallographic vs. inclusion crack formation, transgranular vs. intergranular propagation) are present depending on applied load, temperature, and environment. Typically, the life-limiting features causing failure in Ni-base superalloy components are near surface inclusions. Compressive surface residual stresses are often introduced in Ni-base superalloy components to help retard fatigue crack initiation and early growth at near surface inclusions and shift the fatigue crack initiation sites from surface to sub-surface locations, thereby increasing fatigue life. To model the effects of residual stresses, inclusions, and microstructure heterogeneity on fatigue crack driving force and fatigue scatter, a computational crystal plasticity framework is presented that imposes quasi-thermal eigenstrain to induce near surface residual stresses in polycrystalline Ni-base superalloy IN100 smooth specimens with and without nonmetallic inclusions. In addition, the effect of near surface inclusions in notched Ni-base superalloy components on MSC growth and fatigue life scatter was investigated in this work. A fatigue indicator parameter (FIP)-based microstructurally small crack (MSC) growth model incorporating crack tip/grain boundary effects was introduced and fit to experiments (in both laboratory air and vacuum) for the case of 1D crack growth and then computationally applied to 3D crack growth starting (1) from a focused ion beam (FIB) notch in a smooth specimen, (2) from a debonded inclusion located at different depths within notched components containing different notch root radii, and (3) from inclusions located at different depths relative to the surface in smooth specimens containing simulated shot peened induced residual stresses. Computational predictions in MSC growth rate scatter and distribution of fatigue life were in general accordance with experiments. The general approach presented in this Dissertation can be used to advance integrated computational materials engineering (ICME) by predicting variation of fatigue resistance and minimum life as a function of heat treatment/microstructure and surface treatments for a given alloy system and providing support for design of materials for enhanced fatigue resistance. In addition, this framework can reduce the number of experiments required to support modification of material to enhance fatigue resistance, which can lead to accelerated insertion (from design conception to production parts) of new or improved materials for specific design applications. Elements of the framework being advanced in this research can be applied to any engineering alloy.