This research aims to understand the reliability of Sn-Ag-Cu solder interconnects used in plastic ball grid array (PBGA) packages using microstructure evolution, laser moiré interferometry and finite-element modeling. A particle coarsening based microstructure evolution of the solder joint material during thermal excursions was studied for extended periods of time lasting for several months. The microstructure evolution and particle coarsening was quantified, and acceleration factors were determined between benign field-use conditions and accelerated thermal cycling (ATC) conditions for PBGA packages with different form factors and for two different lead-free solder alloys. A new technique using laser moiré interferometry was developed to assess the deformation behavior of Sn-Ag-Cu based solder joints during thermal excursions. This technique can used to estimate the fatigue life of solder joints quickly in a matter of few days instead of months and can be extended to cover a wide range of temperature regimes. Finite-element analysis (FEA) in conjunction with experimental data from the ATC for different lead-free PBGA packages was used to develop a fatigue life model that can be used to predict solder joint fatigue life for any PBGA package. The proposed model will be able to predict the mean number of cycles required for crack initiation and crack growth rate in a solder joint.

[Truncated abstract. Please see pdf format for complete text.] Over the years much work has been done on studying sequence effects under multilevel loading. Yet, the underlying fatigue mechanisms responsible for such interactions are not fully understood. The study of fatigue under complex loading histories begins by investigating strain interaction effects arising from simple 2-step loading sequences. Fatigue for all investigations were conducted under uniaxial push-pull mode in strain-control. Fatigue is traditionally classified as either low or high cycle fatigue (LCF and HCF respectively). The boundary for LCF and HCF is not well-defined even though the fatigue life of LCF is typically dominated by crack “initiation”, while for HCF, fatigue life is usually dominated by stable crack growth. The terms LCF and HCF, apart from referring to the low and high number of fatigue cycles required for failure, also bear little physical meaning in terms of describing the state of fatigue imposed. As a result, conventional definitions of the two distinct regimes of fatigue are challenged and a new method of classifying the boundary between the two regimes of fatigue is proposed. New definitions are proposed and the terms plastically dominant fatigue (PDF) and elastically dominant fatigue (EDF) are introduced as suitable replacements for LCF and HCF respectively. PDF refers to the condition of a material undergoing significant reverse plasticity during cyclic loading, while for EDF, minimal reverse plasticity is experienced. Systematic testing of three materials, 316 L stainless steel, 6061-T6 aluminium alloy and 4340 high strength steel, was performed to fully investigate the cycle ratio trends and “damage” accumulation behaviour which resulted from a variety of loading conditions. Results from this study were carried over to investigate more complex multilevel loading sequences and possible mechanisms for interaction effects observed both under 2-step and multi-step sequences were proposed. Results showed that atypical cycle ratio trends could result from loading sequences which involve combinations of strain amplitudes from different fatigue regimes (i.e. PDF or EDF). Mean strain effects on fatigue life were also studied. The objective of this study was to identify regimes of fatigue which are significantly influenced by mean strains. Results indicated that mean strains affected EDF but not PDF. 2-step tests, similar to those performed in earlier studies were conducted to investigate the effects of mean strain on variable amplitude loading. Again, atypical cycle ratio trends were observed for loading sequences involving combinations of PDF and EDF. It is understood that fatigue crack growth interaction behaviour and mean stress effects are two dominant mechanisms which can be used to explain cycle ratio trends observed. The significance and importance of proper PDF/EDF definition and specification are also stressed. The study of fracture mechanics is an important component of any fatigue research. Fatigue crack growth in 4140 high strength steel CT specimens, under conditions of plane stress and plane strain were studied. In this investigation, the effects of R and overload ratios were also studied for both plane stress and plane strain conditions. Results indicate that differences in the point of crack “initiation” under both plane stress and plane strain conditions decrease with increasing load range, while the extent of crack retardation as a result of overloading, is greater under plane stress than plane strain conditions. The extent of crack growth retardation increases with decreasing R ratios and increasing overload ratios. The final phase of this project involves the proposal of two practical models used to predict cumulative “damage” and fatigue crack propagation in metals. The cumulative “damage” model proposed takes the form of a power law and the exponent which governs “damage” accumulation can easily be calculated by knowing the failure life, Nf, for a given strain or load level. Predictions for the “damage” model performed better when compared to other popular cumulative “damage” models. The second model proposed predicts fatigue crack growth behaviour from known monotonic and smooth specimen fatigue data. There are several benefits of having a model that can predict fatigue crack growth from monotonic and smooth specimen fatigue data: a) traditionally, engineers had to rely on expensive and time-consuming crack propagation tests to evaluate and select materials for maximum fatigue resistance, and b) monotonic and smooth specimen fatigue data are readily available. The crack propagation model is proposed to alleviate the material selection process by providing engineers a means to rapidly eliminate and narrow down selections for possible material candidates.

Este trabalho propõe um modelo matemático destinado à estimativa da profundidade de carbonatação e à previsão de vida útil de projeto de estruturas de concreto, envolvendo variáveis de entrada de fácil obtenção (como resistência à compressão, tipo de cimento, umidade relativa, entre outras). Com base no conhecimento de experts (grupo focal) criou-se o banco de dados que deu origem ao modelo, o qual considera as principais variáveis de influência na ação da carbonatação, incluindo: às características do concreto (resistência à compressão do concreto aos 28 dias, o tipo de cimento empregado, o teor de adição, quando houver); às condições de exposição (macro clima - ambiente interno ou externo, protegido ou não da chuva); e, às condições ambientais (umidade relativa média da região de exposição da estrutura e o teor de CO2 do ambiente). O modelo matemático proposto baseou-se no ajuste de dados considerando as leis físico-químicas pertinentes, o qual foi testado com dados de investigações experimentais realizadas por outros pesquisadores. Os resultados indicam que o mesmo representa a ação da carbonatação do concreto, apresentando potencial de generalização. Também foi empregado para a previsão de vida útil de projeto, com uma abordagem probabilística via Simulação de Monte Carlo (SMC) e Análise de confiabilidade, inserindo as variabilidades existentes no processo de degradação. Os resultados das simulações demonstram que o modelo pode ser empregado para estimativa de vida útil via processos estocásticos. O modelo foi desenvolvido essencialmente para servir como um suporte para a análise da durabilidade de estruturas de concreto armado em ambiente urbano, podendo ser empregado tanto para a estimativa da profundidade de carbonatação do concreto quanto para a previsão de vida útil de projeto de estruturas novas ou existentes, com abordagem determinística ou probabilística. As maiores vantagens do modelo são relacionadas à entrada de dados os quais podem ser obtidos com relativa facilidade, à facilidade de aplicação e ao potencial de generalização. / This research work proposes a mathematical model to estimate carbonation depths and the service life prediction of concrete structures using easily accessible input variables (such as compressive strength, cement type, relative humidity, etc.). The model was designed using a database which was developed using the knowledge of experts (focus group). This database assesses the main variables that affect carbonation in concrete (compressive strength at 28 days, type of cement, concentration of addition, if applicable), exposure conditions (macroclimate – indoors or outdoors, exposure to rain) and environmental conditions (mean relative humidity and carbon dioxide concentration of the area where the structure is located). The proposed model was tested using experimental data from other researchers and the results suggest that it accurately represents the effects of carbonation in concrete, with results that can be expanded to other structures. The mathematical model was also applied to forecasts of the service life of a project using the probabilistic approach of Monte Carlo methods (MC) and an analysis of reliability that accounted for the intrinsic variability found in decay processes. The results of the simulations show that the model can be used to estimate the service life of a project using a stochastic technique. The model was developed to serve mainly as a supporting feature in the assessment of durability in reinforced concrete structures in urban environments and can be applied both to estimates of carbonation depths and to the service life prediction of projects of new or existing structures, using deterministic or probabilistic approaches. The major benefits offered by this model are related to the input of data, which are readily available, its ease of use and its potential for application in general situations.

Orientador: Prof. Dr. Wesley Góis / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Mecânica, 2015. / O objetivo deste trabalho é realizar uma revisão sobre a metodologia clássica de previsão de falha por fadiga, Método S-N (Método Vida sob Tensão) para o desenvolvimento de uma ferramenta computacional com fins acadêmicos, cujo propósito é auxiliar docentes e discentes durante o ensino dessa metodologia em disciplinas da graduação. O algoritmo foi implementado em linguagem MatLab® e utiliza como dados de entrada a variação temporal do tensor de tensões para determinada região de um componente estrutural, bem como suas propriedades mecânicas. Durante todo processo interativo, a ferramenta apresenta em forma de "passo-a-passo" os fundamentos teóricos de previsão de falha por fadiga (Teoria da Elasticidade, Equação de Basquin, Critérios de Falha, Contagem de Ciclos, Regra de Dano Acumulativo, etc.). Essa é a grande vantagem do programa, pois proporciona dinamicamente a base teórica para a sua utilização, ao contrário de ferramentas puramente comerciais, que normalmente já pressupõem que o usuário tenha o conhecimento teórico para sua utilização. Por fim, como forma de validação da ferramenta, foram simulados, com auxílio da ferramenta desenvolvida neste trabalho, exercícios clássicos da literatura. alternativa, que mais recentemente vem sendo explorada, como solução para as limitações da formulação clássica do Método dos Elementos Finitos (MEF) ¿ de modo a estudar o impacto da mesma numa possível redução dos problemas de instabilidade numérica previamente citada. O algoritmo desenvolvido ao longo do trabalho é baseado no algoritmo apresentado em SIGMUND (2001), assim como alguns exemplos utilizados como referência. Por fim, exemplos numéricos apresentados ao longo do trabalho comprovam a redução parcial, ou em certos casos, completa do problema de instabilidade de tabuleiro de xadrez, demonstrando a viabilidade da utilização do MEFG como uma alternativa para obtenção da distribuição ótima de material no interior do domínio de projeto da estrutura. / The objective of this paper is to perform a revision of the classical methodology for fatigue life prediction, the Stress-Life Approach, to proceed with the development of a computational tool for academic purposes, for the use of masters and scholars during the teaching of this methodology. The algorithm was developed in Matlab® and it uses as input the temporal variation of stress tensor for a region of a structural component and its mechanical properties. During all of the interactive process, the tool shows "step-by-step" all the theoretical fundaments related to the methodology (Elasticity Theory, Basquin¿s Equation, Failure Criteria, Cycle Counting Methods, Palmgren-Miner¿s Linear Damage Rule, etc.). This is the main advantage of the software, since it offers dynamically the theoretical concepts to be used, unlike purely commercial tools, which normally consider that the users have a previous knowledge. Finally, the validation step of the tool considers the resolution of classical exercises.

Este trabalho propõe um modelo matemático destinado à estimativa da profundidade de carbonatação e à previsão de vida útil de projeto de estruturas de concreto, envolvendo variáveis de entrada de fácil obtenção (como resistência à compressão, tipo de cimento, umidade relativa, entre outras). Com base no conhecimento de experts (grupo focal) criou-se o banco de dados que deu origem ao modelo, o qual considera as principais variáveis de influência na ação da carbonatação, incluindo: às características do concreto (resistência à compressão do concreto aos 28 dias, o tipo de cimento empregado, o teor de adição, quando houver); às condições de exposição (macro clima - ambiente interno ou externo, protegido ou não da chuva); e, às condições ambientais (umidade relativa média da região de exposição da estrutura e o teor de CO2 do ambiente). O modelo matemático proposto baseou-se no ajuste de dados considerando as leis físico-químicas pertinentes, o qual foi testado com dados de investigações experimentais realizadas por outros pesquisadores. Os resultados indicam que o mesmo representa a ação da carbonatação do concreto, apresentando potencial de generalização. Também foi empregado para a previsão de vida útil de projeto, com uma abordagem probabilística via Simulação de Monte Carlo (SMC) e Análise de confiabilidade, inserindo as variabilidades existentes no processo de degradação. Os resultados das simulações demonstram que o modelo pode ser empregado para estimativa de vida útil via processos estocásticos. O modelo foi desenvolvido essencialmente para servir como um suporte para a análise da durabilidade de estruturas de concreto armado em ambiente urbano, podendo ser empregado tanto para a estimativa da profundidade de carbonatação do concreto quanto para a previsão de vida útil de projeto de estruturas novas ou existentes, com abordagem determinística ou probabilística. As maiores vantagens do modelo são relacionadas à entrada de dados os quais podem ser obtidos com relativa facilidade, à facilidade de aplicação e ao potencial de generalização. / This research work proposes a mathematical model to estimate carbonation depths and the service life prediction of concrete structures using easily accessible input variables (such as compressive strength, cement type, relative humidity, etc.). The model was designed using a database which was developed using the knowledge of experts (focus group). This database assesses the main variables that affect carbonation in concrete (compressive strength at 28 days, type of cement, concentration of addition, if applicable), exposure conditions (macroclimate – indoors or outdoors, exposure to rain) and environmental conditions (mean relative humidity and carbon dioxide concentration of the area where the structure is located). The proposed model was tested using experimental data from other researchers and the results suggest that it accurately represents the effects of carbonation in concrete, with results that can be expanded to other structures. The mathematical model was also applied to forecasts of the service life of a project using the probabilistic approach of Monte Carlo methods (MC) and an analysis of reliability that accounted for the intrinsic variability found in decay processes. The results of the simulations show that the model can be used to estimate the service life of a project using a stochastic technique. The model was developed to serve mainly as a supporting feature in the assessment of durability in reinforced concrete structures in urban environments and can be applied both to estimates of carbonation depths and to the service life prediction of projects of new or existing structures, using deterministic or probabilistic approaches. The major benefits offered by this model are related to the input of data, which are readily available, its ease of use and its potential for application in general situations.

Este trabalho propõe um modelo matemático destinado à estimativa da profundidade de carbonatação e à previsão de vida útil de projeto de estruturas de concreto, envolvendo variáveis de entrada de fácil obtenção (como resistência à compressão, tipo de cimento, umidade relativa, entre outras). Com base no conhecimento de experts (grupo focal) criou-se o banco de dados que deu origem ao modelo, o qual considera as principais variáveis de influência na ação da carbonatação, incluindo: às características do concreto (resistência à compressão do concreto aos 28 dias, o tipo de cimento empregado, o teor de adição, quando houver); às condições de exposição (macro clima - ambiente interno ou externo, protegido ou não da chuva); e, às condições ambientais (umidade relativa média da região de exposição da estrutura e o teor de CO2 do ambiente). O modelo matemático proposto baseou-se no ajuste de dados considerando as leis físico-químicas pertinentes, o qual foi testado com dados de investigações experimentais realizadas por outros pesquisadores. Os resultados indicam que o mesmo representa a ação da carbonatação do concreto, apresentando potencial de generalização. Também foi empregado para a previsão de vida útil de projeto, com uma abordagem probabilística via Simulação de Monte Carlo (SMC) e Análise de confiabilidade, inserindo as variabilidades existentes no processo de degradação. Os resultados das simulações demonstram que o modelo pode ser empregado para estimativa de vida útil via processos estocásticos. O modelo foi desenvolvido essencialmente para servir como um suporte para a análise da durabilidade de estruturas de concreto armado em ambiente urbano, podendo ser empregado tanto para a estimativa da profundidade de carbonatação do concreto quanto para a previsão de vida útil de projeto de estruturas novas ou existentes, com abordagem determinística ou probabilística. As maiores vantagens do modelo são relacionadas à entrada de dados os quais podem ser obtidos com relativa facilidade, à facilidade de aplicação e ao potencial de generalização. / This research work proposes a mathematical model to estimate carbonation depths and the service life prediction of concrete structures using easily accessible input variables (such as compressive strength, cement type, relative humidity, etc.). The model was designed using a database which was developed using the knowledge of experts (focus group). This database assesses the main variables that affect carbonation in concrete (compressive strength at 28 days, type of cement, concentration of addition, if applicable), exposure conditions (macroclimate – indoors or outdoors, exposure to rain) and environmental conditions (mean relative humidity and carbon dioxide concentration of the area where the structure is located). The proposed model was tested using experimental data from other researchers and the results suggest that it accurately represents the effects of carbonation in concrete, with results that can be expanded to other structures. The mathematical model was also applied to forecasts of the service life of a project using the probabilistic approach of Monte Carlo methods (MC) and an analysis of reliability that accounted for the intrinsic variability found in decay processes. The results of the simulations show that the model can be used to estimate the service life of a project using a stochastic technique. The model was developed to serve mainly as a supporting feature in the assessment of durability in reinforced concrete structures in urban environments and can be applied both to estimates of carbonation depths and to the service life prediction of projects of new or existing structures, using deterministic or probabilistic approaches. The major benefits offered by this model are related to the input of data, which are readily available, its ease of use and its potential for application in general situations.

Standard crystalline silicon photovoltaic (PV) modules are designed to continuously convert solar energy into electricity for 25 years. However, the continual generation of electricity by the PV modules throughout their designed service life has been a concern. The key challenge has been the untimely fatigue failure of solder interconnections of solar cells in the modules due to accelerated thermo-mechanical degradation. The goal of this research is to provide adequate information for proper design of solar cell solder joint against fatigue failure through the study of cyclic thermo-mechanical stresses and strains in the joint. This is carried-out through finite element analysis (FEA) using ANSYS software to develop the solar cell assembly geometric models followed by simulations. Appropriate material constitutive model for solder alloy is employed to predict number of cycles to failure of solder joint, hence predicting its fatigue life. The results obtained from this study indicate that intermetallic compound thickness (TIMC); solder joint thickness (TSJ) and width (WSJ) have significant impacts on fatigue life of solder joint. The impacts of TIMC and TSJ are such that as the thicknesses increases solder joint fatigue life decreases. Conversely, as solder joint width (WSJ) increases, fatigue life increases. Furthermore, optimization of the joint is carried-out towards thermo-mechanical reliability improvement. Analysis of results shows the design with optimal parameter setting to be: TIMC -2.5μm, TSJ -20μm and WSJ -1000μm. In addition, the optimized model has 16,264 cycles to failure which is 18.82% more than the expected 13,688 cycles to failure of a PV module designed to last for 25 years.

This study aims to investigate the mechanical and fatigue behavior of additively manufactured metallic materials. Several challenges associated with different metal additive manufacturing (AM) techniques (i.e. laser-powder bed fusion and direct laser deposition) have been addressed experimentally and numerically. Experiments have been carried out to study the effects of process inter-layer time interval – i.e. either building the samples one-at-a-time or multi-at-a-time (in-parallel) – on the microstructural features and mechanical properties of 316L stainless steel samples, fabricated via a direct laser deposition (DLD). Next, the effect of building orientation – i.e. the orientation in which AM parts are built – on microstructure, tensile, and fatigue behaviors of 17-4 PH stainless steel, fabricated via a laser-powder bed fusion (L-PBF) method was investigated. Afterwards, the effect of surface finishing – here, as-built versus machined – on uniaxial fatigue behavior and failure mechanisms of Inconel 718 fabricated via a laser-powder bed fusion technique was sought. The numerical studies, as part of this dissertation, aimed to model the mechanical behavior of AM materials, under monotonic and cyclic loading, based on the observations and findings from the experiments. Despite significant research efforts for optimizing process parameters, achieving a homogenous, defectree AM product – immediately after fabrication – has not yet been fully demonstrated. Thus, one solution for ensuring the adoption of AM materials for application should center on predicting the variations in mechanical behavior of AM parts based on their resultant microstructure. In this regard, an internal state variable (ISV) plasticity-damage model was employed to quantify the damage evolution in DLD 316L SS, under tensile loading, using the microstructural features associated with the manufacturing process. Finally, fatigue behavior of AM parts has been modeled based on the crack-growth concept. Using the FASTRAN code, the fatigue-life of L-PBF Inconel 718 was accurately calculated using the size and shape of process-induced voids in the material. In addition, the maximum valley depth of the surface profile was found to be an appropriate representative of the initial surface flaw for fatigue-life prediction of AM materials in an as-built surface condition.

Assessment of machine health and prediction of future failures are critical for maintenance decisions. Many of the existing methods use unsupervised techniques to construct health indicators by measuring the disparity between the current state and either the healthy or the faulty states of the system. This approach can work well, but if the resulting health indicators are insufficient there is no easy way to steer the algorithm towards better ones. In this thesis a new method for health indicator construction is investigated that aims to solve this issue. It is based on measuring distance after transforming the sensor data into a new space using a feed-forward neural network. The feed-forward neural network is trained using a multi-objective optimization algorithm, NSGA-II, to optimize criteria that are desired in a health indicator. Thereafter the constructed health indicator is passed into a gated recurrent unit for remaining useful life prediction. The approach is compared to benchmarks on the NASA Turbofan Engine Degradation Simulation dataset and in regard to the size of the neural networks, the model performs relatively well, but does not outperform the results reported by a few of the more recent methods. The method is also investigated on a simulated dataset based on elevator weights with two independent failures. The method is able to construct a single health indicator with a desirable shape for both failures, although the latter estimates of time until failure are overestimated for the more rare failure type. On both datasets the health indicator construction method is compared with a baseline without transformation function and does in both cases outperform it in terms of the resulting remaining useful life prediction error using the gated recurrent unit. Overall, the method is shown to be flexible in generating health indicators with different characteristics and because of its properties it is adaptive to different remaining useful life prediction methods. / Estimering av maskinhälsa och prognos av framtida fel är kritiska steg för underhållsbeslut. Många av de befintliga metoderna använder icke-väglett (unsupervised) lärande för att konstruera hälsoindikatorer som beskriver maskinens tillstånd över tid. Detta sker genom att mäta olikheter mellan det nuvarande tillståndet och antingen de friska eller fallerande tillstånden i systemet. Det här tillvägagångssättet kan fungera väl, men om de resulterande hälsoindikatorerna är otillräckliga så finns det inget enkelt sätt att styra algoritmen mot bättre. I det här examensarbetet undersöks en ny metod för konstruktion av hälsoindikatorer som försöker lösa det här problemet. Den är baserad på avståndsmätning efter att ha transformerat indatat till ett nytt vektorrum genom ett feed-forward neuralt nätverk. Nätverket är tränat genom en multi-objektiv optimeringsalgoritm, NSGA-II, för att optimera kriterier som är önskvärda hos en hälsoindikator. Därefter används den konstruerade hälsoindikatorn som indata till en gated recurrent unit (ett neuralt nätverk som hanterar sekventiell data) för att förutspå återstående livslängd hos systemet i fråga. Metoden jämförs med andra metoder på ett dataset från NASA som simulerar degradering hos turbofan-motorer. Med avseende på storleken på de använda neurala nätverken så är resultatet relativt bra, men överträffar inte resultaten rapporterade från några av de senaste metoderna. Metoden testas även på ett simulerat dataset baserat på elevatorer som fraktar säd med två oberoende fel. Metoden lyckas skapa en hälsoindikator som har en önskvärd form för båda felen. Dock så överskattar den senare modellen, som använde hälsoindikatorn, återstående livslängd vid estimering av det mer ovanliga felet. På båda dataseten jämförs metoden för hälsoindikatorkonstruktion med en basmetod utan transformering, d.v.s. avståndet mäts direkt från grund-datat. I båda fallen överträffar den föreslagna metoden basmetoden i termer av förutsägelsefel av återstående livslängd genom gated recurrent unit- nätverket. På det stora hela så visar sig metoden vara flexibel i skapandet av hälsoindikatorer med olika attribut och p.g.a. metodens egenskaper är den adaptiv för olika typer av metoder som förutspår återstående livslängd.

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