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<p>The superior high-temperature elastic-plastic properties coupled with greater damage tolerance when compared with monolithic ceramics make ceramic matrix composites, CMCs, promising candidates for challenging applications such as engine components, rocket nozzles, cutting tools and nuclear energy reactor core components. Anelastic recovery is the time-dependent back strain observed upon the load removal following creep. In whisker-reinforced CMCs this can be a factor limiting operating conditions. Plastic strain misfit between two phases is thought to be the main driver in terms of the interactions within a percolating network. However, the network deformation mechanisms are still unclear and a previous neutron diffraction study showed an unexpected decrease of peak width after creep contradicting the theoretical predictions.</p> <p>In this contribution, the finite element method (FEM) is applied to a representative volume element (RVE) with proper boundary conditions in order to simulate the creep deformation and hot pressing processes. Three geometries have been generated and studied: a 3D randomly-oriented short-fiber unit cell without fiber to fiber contact, generated by a random sequential adsorption algorithm; 3D regularly aligned single fiber unit cells; and 2D regularly aligned percolating unit cells. Deformation mechanism has been studied from an energy point of view and compared with a modified analytical model. Then a virtual diffraction model has been developed providing a framework to transfer information between the FEM simulations (strain fields) and the diffraction pattern in terms of the peak width (full width at half maximum: <strong><em>FWHM</em></strong>) and peak position as a measure of stress distribution and mean stress state respectively. Furthermore, the coupling effects of external stress, deformation mode, and thermal stress on the diffraction patterns have been studied.</p> <p>The critical importance of a percolating whisker network for the anelastic recovery is demonstrated based on the 3D multi-whisker random unit cell. Whisker bending is shown to be the dominant mechanism over contact effects during the creep deformation of a composite containing a well aligned percolating whisker network based on the 2D unit cell model. Good qualitative agreement was found between our FEM simulations and the analytical model of Wilkinson and Pompe with regards to the maximum recoverable strain and the characteristic relaxation time. The analytical model captures all the critical factors characterizing the strain recovery, e.g., the effect of creep pre-exponent constant, whisker Young’s modulus and aspect ratio. Furthermore, it is found that the deformation from an initial stress-free state inevitably introduces peak broadening of whiskers inside the matrix. Several factors determine the peak-width and -shift, i.e., creep strain, applied stress, aspect ratio and geometry. However, thermal stress from the cooling stages following creep and hot pressing processes shelters this broadening effect and complicates the trends. Wide-ranging peak-width changes from narrowing to broadening are predicted depending on the geometry and applied stress. The peak position is shifted to a lower angle due to this thermal effect. This clearly explains the contradicting phenomena motivating this work and leads to that recommendation that a diffraction source with high angular resolution is needed to detect the subtle change of peak profile during creep.</p> / Doctor of Philosophy (PhD)

The physical and mechanical characteristics of carbon fiber reinforced polymers (CFRP) and Ti6Al4V make them widely used in the aerospace industry. The hybrid structure of CFRP/ Ti6Al4V material has been used in the new generation of aircraft manufacturing. The drilling process of these materials is often associated with unfavorable machining defects such as delamination, burr formation, reduced surface integrity, and tensile residual stresses. These machining defects are attributed to high thermal load, continuous chip morphology, and poor chips evacuation efficiency. Vibration-assisted drilling (VAD) uses an intermittent cutting process to control the uncut chip thickness and chip morphology. VAD has potential advantages include low thermal load, high chips evacuation effectiveness, and longer tool life. This thesis presents an experimental investigation into the effect of VAD machining parameters on the cutting energy, CFRP delamination, surface integrity, geometrical geometry, Ti6Al4V burr formation, induced residual stresses, and tool wear during the drilling process of CFRP, Ti6Al4V, and CFRP/Ti6Al4V stacked materials. Moreover, a kinematics model is developed to link the observed results to the independent machining parameters (i.e., cutting speed, feed rate, modulation amplitude, and modulation frequency). The experimental work covers a wide range of machining parameters using four levels of frequencies (83.3, 125, 1500, and 2150 Hz). The VAD results show up to 56 % reduction in the cutting temperature with a significant enhancement in the CFRP entry and exit delamination, geometrical accuracy, surface integrity, and burr formation. The use of VAD also generates compressive stresses, hence improving the part fatigue life. / Thesis / Doctor of Philosophy (PhD)

Additive manufacturing (AM) technology is a key emerging field transforming how customized products with complex shapes are manufactured. AM is the process of layering materials to produce objects from three-dimensional (3D) models. AM technology can be used to print objects with complicated geometries and a broad range of material properties. However, the issue of ensuring the quality of printed products during the process remains an obstacle to industry-level adoption. Furthermore, the characteristics of AM processes typically involve complex process dynamics and interactions between machine parameters and desired qualities. The issues associated with quality assurance in AM processes underscore the need for research into smart quality assurance systems. To study the complex physics behind process interaction challenges in AM processes, this dissertation proposes the development of a data-driven smart quality assurance framework that incorporates in-process sensing and machine learning-based modeling by correlating the relationships among parameters, signatures, and quality. High-fidelity AM simulation data and the increasing use of sensors in AM processes help simulate and monitor the occurrence of defects during a process and open doors for data-driven approaches such as machine learning to make inferences about quality and predict possible failure consequences. To address the research gaps associated with quality assurance for AM processes, this dissertation proposes several data-driven approaches based on the design of experiments (DoE), forward prediction modeling, and an inverse design methodology. The proposed approaches were validated for AM processes such as fused filament fabrication (FFF) using polymer and hydrogel materials and laser powder bed fusion (LPBF) using common metal materials. The following three novel smart quality assurance systems based on a parameter–signature–quality (PSQ) framework are proposed: 1. A customized in-process sensing platform with a DOE-based process optimization approach was proposed to learn and optimize the relationships among process parameters, process signatures, and parts quality during bioprinting processes. This approach was applied to layer porosity quantification and quality assurance for polymer and hydrogel scaffold printing using an FFF process. 2. A data-driven surrogate model that can be informed using high-fidelity physical-based modeling was proposed to develop a parameter–signature–quality framework for the forward prediction problem of estimating the quality of metal additive-printed parts. The framework was applied to residual stress prediction for metal parts based on process parameters and thermal history with reheating effects simulated for the LPBF process. 3. Deep-ensemble-based neural networks with active learning for predicting and recommending a set of optimal process parameter values were developed to optimize optimal process parameter values for achieving the inverse design of desired mechanical responses of final built parts in metal AM processes with fewer training samples. The methodology was applied to metal AM process simulation in which the optimal process parameter values of multiple desired mechanical responses are recommended based on a smaller number of simulation samples. / Doctor of Philosophy / Additive manufacturing (AM) is the process of layering materials to produce objects from three-dimensional (3D) models. AM technology can be used to print objects with complicated geometries and a broad range of material properties. However, the issue of ensuring the quality of printed products during the process remains a challenge to industry-level adoption. Furthermore, the characteristics of AM processes typically involve complex process dynamics and interactions between machine parameters and the desired quality. The issues associated with quality assurance in AM processes underscore the need for research into smart quality assurance systems. To study the complex physics behind process interaction challenges in AM processes, this dissertation proposes a data-driven smart quality assurance framework that incorporates in-process sensing and machine-learning-based modeling by correlating the relationships among process parameters, sensor signatures, and parts quality. Several data-driven approaches based on the design of experiments (DoE), forward prediction modeling, and an inverse design methodology are proposed to address the research gaps associated with implementing a smart quality assurance system for AM processes. The proposed parameter–signature–quality (PSQ) framework was validated using bioprinting and metal AM processes for printing with polymer, hydrogel, and metal materials.

Welding is used extensively in aerospace, automotive, chemical, manufacturing, electronic and power-generation industries. Thermally-induced residual stresses due to welding can significantly impair the performance and reliability of welded structures. Numerical simulation of weld pool dynamics is important as experimental measurements of velocities and temperature profiles are difficult due to the small size of the weld pool and the presence of the arc. From a structural integrity perspective of welded structures, it is necessary to have an accurate spatial and temporal thermal distribution in the welded structure before stress analysis is performed. Existing research on weld pool dynamics simulation has ignored the effect of fluid flow in the weld pool on the temperature field of the welded joint. Previous research has established that the weld pool depth/width (D/W) ratio and Heat Affected Zone (HAZ) are significantly altered by the weld pool dynamics. Hence, for a more accurate estimation of the thermally-induced stresses it is desired to incorporate the weld pool dynamics into the analysis. Moreover, the effects of microstructure evolution in the HAZ on the mechanical behavior of the structure need to be included in the analysis for better mechanical response prediction. In this study, a three-dimensional model for the thermo-mechanical analysis of Gas Tungsten Arc (GTA) welding of thin stainless steel butt-joint plates has been developed. The model incorporates the effects of thermal energy redistribution through weld pool dynamics into the structural behavior calculations. Through material modeling the effects of microstructure change/phase transformation are indirectly included in the model. The developed weld pool dynamics model includes the effects of current, arc length, and electrode angle on the heat flux and current density distributions. All the major weld pool driving forces are included, namely surface tension gradient, plasma drag force, electromagnetic force, and buoyancy. The weld D/W predictions are validated with experimental results. They agree well. The effects of welding parameters (like welding speed, current, arc length, etc.) on the weld D/W ratio are documented. The workpiece deformation and stress distributions are also highlighted. The transverse and longitudinal residual stress distribution plots across the weld bead and their variations with welding speed and current are also provided. The mathematical framework developed here serves as a robust tool for better prediction of weld D/W ratio and thermally-induced stress evolution and distribution in a welded structure by coupling the different fields in a welding process. / Ph. D.

Miniaturizing circuit size and increasing power density are the latest trends in modern power electronics development. In order to meet the requirements of higher frequency and higher power density in power electronics applications, planar interconnections are utilized to achieve a higher integration level. Power switching devices, passive power components, and EMI (Electromagnetic Interference) filters can all be integrated into planar power modules by using planar metallization, which is a technology involving electrical, mechanical, material, and thermal issues. By processing high dielectric materials, magnetic materials, or silicon chips using compatible manufacturing procedures, and by carefully designing structures and interconnections, we can realize the conventional discrete inductors, capacitors, and switch circuits with planar modules. Compared with conventional discrete components, the integrated planar modules have several advantages including lower profiles, better form factors, and less labor-intensive processing steps. In addition, planar interconnections reduce the wire bond inductive and resistive parasitic parameters, especially for high frequency applications. However, planar integration technology is a packaging approach with a large contact area between different materials. This may result in unknown failure mechanisms in power applications. Extensive research has already been done to study the performance, processing, and reliability of the planar interconnects in thin film structures. The thickness of the thin films used in integrated circuits (IC) or microelectronics applications ranges from the magnitude of nanometers to that of micrometers. In this work, we are interested in adopting planar interconnections to Integrated Power Electronics Modules (IPEM). In Integrated Power Electronics Modules (IPEMs), copper traces, especially bus traces, need to conduct current ranging from a few amps to tens of amps. One of the major differences between IC and IPEM is that the metal layer in IPEMs (normally >75µm) is much thicker than that of the thin films in IC (normally <1µm). The other major difference, which is also a feature of IPEM, is that the planar metallization is deposited on different brittle substrates. In active IPEM, switching devices are in a bare die form with no encapsulation. The copper deposition is on top of the silicon chips and the insulation polyimide layer. One of the key elements for passive IPEM and the EMI IPEM is the integrated inductor-capacitor (LC) module, which realizes equivalent inductors and capacitors in one single module. The deposition processes for silicon substrates and ceramic substrates are compatible and both the silicon and ceramic materials are brittle. Under high current and high temperature conditions, these copper depositions on brittle materials will cause detrimental failure spots. Over the last few years, the design, manufacture, optimization, and testing of the IPEMs has been developed and well documented. Up to this time , the research on failure mechanisms of conventional integrated power modules has led to the understanding of failures centered on wire bond or solder layer. However, investigation on the reliability and failure modes of IPEM is lacking, particularly that which uses metallization on brittle substrates for high current operations. In this study, we conduct experiments to measure and calculate the residual stresses induced during the process. We also, theoretically model and simulate the thermo-mechanical stresses caused by the mismatch of thermal expansion coefficients between different materials in the integrated power modules. In order to verify the simulation results, the integrated power modules are manufactured and subjected to the lifetime tests, in which both power cycling and temperature cycling tests are carried out. The failure mode analysis indicates that there are different failure modes for copper films under tensile or compressive stresses. The failure detection process verifies that delamination and silicon cracks happen to copper films due to compressive and tensile stresses respectively. This study confirms that the high stresses between the metallization and the silicon are the failure drivers in integrated power electronics modules.. We also discuss the driving forces behind several different failure modes. Further understanding of thesefailure mechanisms enables the failure modes to be engineered for safer electrical operation of IPEM modules and helps to enhance the reliability of system-level operation. It is also the basis to improve the design and to optimize the process parameters so that IPEM modules can have a high resistance to recognized failures. / Ph. D.

<p>The Powder Bed Fusion (PBF) process is increasingly employed by industry to fabricate complex parts with stringent standard criteria. However, fabricating parts free of defects using this process is still a major challenge. As reported in the literature, thermally induced abnormalities form the majority of generated defects and are largely attributed to thermal evolution. Various methodologies have been introduced in the literature to eliminate or mitigate such abnormalities. However, most of these methodologies are post-process in nature, lacking adaptability and customization to accommodate different geometries or materials. Consequently, they fall short of adequately addressing these challenges. Monitoring and controlling temperature, along with its distribution throughout each layer during fabrication, is an effective and efficient proxy to control the thermal evolution of the process. This, in turn, provides a real-time solution to effectively overcome such challenges. </p> <p>The objective of this dissertation is to introduce a novel online thermography and closedloop hybrid-control (NOTCH)©, an ultra-fast and practical control approach, to modify the scan strategy in metal PBF in real time. This methodology employs different mathematical-thermophysical concept-based or thermophysical-based models combined with optimization algorithms designed to optimize the printing sequence of islands/stripes/zones in order to avoid or mitigate residual stress and distortion. This methodology is adaptable to different geometries, dimensions, and materials, and is capable of being used with machines having varying ranges of specifications. </p> <p>NOTCH’s objective is to achieve a uniform temperature distribution throughout an entire layer and through the printed part (between layers) to mitigate residual stress and thermally related distortion. To attain this objective, this study explores modifying or optimizing the printing sequence of islands/stripes in an island or the strip scanning strategy. This dissertation presents three key contributions: </p> <p>First, this work introduces two potential models: the Genetic Algorithm Maximum Path (GAMP) strategy and Generalized Advanced Graph Theory. Preliminary results for a printed/simulated prototype are presented. These models, along with the Tessellation algorithm (developed in my M.Sc. thesis), were employed within NOTCH.</p> <p>Second, I developed two optimization algorithms based on the greedy and evolutionary approaches. Both algorithms are direct-derivative-free methods. The greedy optimization provides a definitive solution at each printing step, selecting the island/stripe that ensures the highest temperature uniformity. Conversely, the evolutionary algorithm seeks to obtain the final optimal solution at the end of the printing process, i.e., the printing sequence with the highest uniformity in the last printing step. This approach is inspired by the concept of Random Search algorithms, offering a non-definitive solution to find an optimal solution. </p> <p>Last, this work presents the NOTCH methodology, enabling real-time modification of printing sequences through the integration of a novel thermography methodology (developed in my M.Sc. thesis), developed models, and optimization algorithms.</p> <p><br></p>

<div>Defects are unavoidable, life-limiting and dominant sites of damage and subsequent failure in a material. Ni-based superalloys are commonly used in high temperature applications and inevitably found to have defects in the form of inclusions, voids and microscopic cracks which are below the resolution of standard inspection techniques. A mechanistic understanding of the role of defects in such industrially relevant bulk polycrystalline material is essential for philosophies of design and durability to follow and ensure structural integrity of components in the inevitable presence of such defects. The current understanding of defect-mediated damage, in bulk Ni superalloys, is limited by experimental techniques that can capture the local micromechanical state of the material surrounding the defect. In this work, we combine mechanical testing with in-situ, non-destructive 3-D X-ray characterization techniques to obtain rich multi-modal datasets at the microscale to interrogate complex defect-microstructure interactions and elucidate the mechanisms of failure around defects. The attenuated X-ray beam, after passage through the material, is utilized through computed micro-tomography to characterize the defects owing to its sensitivity to density differences in the material. The diffracted X-ray beam, after illuminating the material, is employed through high energy diffraction microscopy in various modes to interrogate the evolving micromechanical state around the discovered defects.</div><div>Three case studies are performed with specimens made of a Ni-based superalloy specially designed and fabricated to have internal defects in the form of: (i) an inclusion, (ii) a microscopic crack, and (iii) voids. In each case, the grain scale information is investigated to reveal heterogeneity in the local micromechanical state of the material as a precursor for the onset of failure. Models and simulations based on finite element or crystal plasticity are utilized, wherever necessary, to assess the factors essential to the underlying mechanism of failure. In the first case study, the detrimental effects of an inclusion in initiating a crack upon cyclic loading is interrogated and the state of bonding, residual stresses, and geometrical stress concentrations around the inclusion are demonstrated to be of utmost importance. In the second case study, the propagation of a short fatigue crack through the microstructure is examined to reveal the crystallographic nature of crack growth through the (i) alignment of the crack plane with the most active slip system, (ii) the correlation between the crack growth rate and the maximum resolved shear stresses, and (iii) the dependence of the crack growth direction on microplasticity within grains ahead of the crack front. In the third case study, the role of voids in ductile failure under tensile loading is explored to illuminate the activation and operation of distinct mechanisms of inter-void shear and necking under the control of the local state of stress triaxiality and the local plasticity within the grains at critical sites of fracture.</div><div>In summary, a grain scale description of the micromechanical state has been unambiguously determined through experiments to examine the heterogeneity around defects in the material. It has enabled us to identify and isolate the nature of factors essential to the activation of specific mechanisms at the onset failure. The grain scale thus provides an ideal physical basis to understand the fundamentals of defect mediated damage and failure instilling trust in the predictive capabilities of models that incorporate the response of the grain structure. The generated datasets can be used to instantiate and calibrate such models at the grain level for higher fidelity. </div>

Neste trabalho, propõe-se um modelo numérico-computacional representativo dos processos de tratamento térmico, que seja uma ferramenta eficiente e forneça meios para um entendimento efetivo do mecanismo de geração de tensões residuais durante a têmpera de aços. Foram investigados os fenômenos térmicos, mecânicos e de transformação de fase observados na têmpera, bem como o acoplamento entre esses três fenômenos. O modelo utiliza o Método dos Elementos Finitos (MEF) e o programa ABAQUS®, além de rotinas numéricas em FORTRAN responsáveis pela resolução do problema termo-mecânico-microestrutural acoplado. A utilização de sub-rotinas, que implementam uma alteração na formulação (matemática e numérica) do programa de Elementos Finitos, permite incluir no modelo as informações presentes em uma curva CRC (curva de resfriamento contínuo) do aço SAE 4140, implementando o cálculo de deformações da peça simulada de modo incremental e cumulativo. Os resultados mostram que a utilização das sub-rotinas desenvolvidas neste trabalho permitiu implementar, conjuntamente com o programa ABAQUS®, o cálculo das frações volumétricas, durezas, distorções e tensões que surgem em um tratamento térmico de têmpera, simulando as transformações martensítica, perlítica, bainítica e ferrítica. Os resultados dos modelos foram equivalentes aos relatados pela literatura, principalmente no que se refere às durezas e tensões associadas a cada transformação de fase. Em particular, os resultados indicam que a transformação martensítica está sempre associada à formação de tensões compressivas. Ensaios experimentais foram realizados a fim de validar os modelos computacionais propostos, utilizando-se um teste Jominy adaptado e instrumentado, de modo a permitir a amostragem da variação de temperaturas no material. Ensaios metalográficos permitiram correlacionar as frações volumétricas transformadas durante a têmpera do corpo de prova Jominy aos valores calculados pelo modelo numérico acoplado. / The objective of this work is to analyze residual strains and stresses and volumetric expansion due to phase transformations that occur during quenching of a steel body, as well as to predict these phase transformations. The coupled thermo-mechanical-phase transformation problem was analyzed, specifically in terms of the quenching process. Different computational models were presented, based on the finite element software ABAQUS® and on the use of FORTRAN subroutines. The continuous-cooling-transformation (CCT) diagrams of SAE 4140 steel are represented differently in each model, depending on the transformed phases and correspondent volumetric expansion. These subroutines include information from the CCT diagrams of SAE 4140 into a FORTRAN code. The subroutine calculates all the microstructures resulting from quenching (ferrite, pearlite, bainite, and martensite), depending on cooling rate. The numerical analysis conducted in this work provided results in terms of the temperature and stresses developed during quenching. The properties determined in this work are hardness, yield strength, volumetric fraction and distortion. Hardness has been predicted by the use of analytical equations. The finite element analyses were able to explain and reproduce phenomena observed during quenching of a steel cylinder. In particular, numerical results indicated that martensite formation is always related to a compressive stress field. The results of the models are in qualitative agreement with data provided by literature, particularly, in relation to the stresses originated by each different phase transformation during quenching process. Experimental testing was conducted, based on the analysis of the quenching of a Jominy probe, in order to validate the computational model developed in this work.