This dissertation presents a sampling-based method that can be used for uncertainty quantification and deterministic or probabilistic optimization. The objective is to simultaneously address several difficulties faced by classical techniques based on response values and their gradients. In particular, this research addresses issues with discontinuous and binary (pass or fail) responses, and multiple failure modes. All methods in this research are developed with the aim of addressing problems that have limited data due to high cost of computation or experiment, e.g. vehicle crashworthiness, fluid-structure interaction etc.The core idea of this research is to construct an explicit boundary separating allowable and unallowable behaviors, based on classification information of responses instead of their actual values. As a result, the proposed method is naturally suited to handle discontinuities and binary states. A machine learning technique referred to as support vector machines (SVMs) is used to construct the explicit boundaries. SVM boundaries can be highly nonlinear, which allows one to use a single SVM for representing multiple failure modes.One of the major concerns in the design and uncertainty quantification communities is to reduce computational costs. To address this issue, several adaptive sampling methods have been developed as part of this dissertation. Specific sampling methods have been developed for reliability assessment, deterministic optimization, and reliability-based design optimization. Adaptive sampling allows the construction of accurate SVMs with limited samples. However, like any approximation method, construction of SVM is subject to errors. A new method to quantify the prediction error of SVMs, based on probabilistic support vector machines (PSVMs) is also developed. It is used to provide a relatively conservative probability of failure to mitigate some of the adverse effects of an inaccurate SVM. In the context of reliability assessment, the proposed method is presented for uncertainties represented by random variables as well as spatially varying random fields.In order to validate the developed methods, analytical problems with known solutions are used. In addition, the approach is applied to some application problems, such as structural impact and tolerance optimization, to demonstrate its strengths in the context of discontinuous responses and multiple failure modes.

Cette thèse porte sur l'analyse de l'endommagement par fatigue et optimisation fiabiliste des structures soumises à des vibrations aléatoires. Le but de l'optimisation fiabiliste est de trouver le compromis entre le coût et la fiabilité. Plusieurs méthodes, telles que la méthode hybride et la méthode OSF ont été développées. Ces méthodes ont été appliquées dans des cas statiques et certains cas dynamiques spécifiques. Dans la réalité les structures sont soumises à des vibrations aléatoires qui peuvent provoquer un endommagement par fatigue. Dans cette thèse on présente la stratégie numérique de calcul de l'endommagement par fatigue dans le domaine fréquentiel et on propose une extension des méthodes RBDO dans le cas des structures soumises à des vibrations aléatoires. Aussi, une méthode RHM est développée. Enfin,une application industrielle qui porte sur la modélisation de la partie mécanique du banc HALT est présenté. / This thesis deals with the fatigue damage analysis and reliability-based design optimization (RBDO) of structures under random vibrations. The purpose of an RBDO method is to find the best compromise between cost and safety. Several methods, such as Hybrid method and OSF method have been developed. These methods have been applied in static cases and some specific dynamic cases. In fact, structures are subject to random vibrations which can cause a fatigue damage. In this thesis we present the strategy of calculation of the fatigue damage based on the Sines criterion in the frequency domain developed in our laboratory. Then, an extension of the RBDO methods in the case of structures subjected to random vibrations is proposed. Also, an RHM method is developed. Finally, we present an industrial application where we propose a model of the mechanical part of the HALT chamber.

This master thesis has been executed at Scania CV AB in Södertälje, Sweden. Scania is a manufacturer of heavy transport solutions, an industry which is changing rapidly in order to meet stricter regulations, ensuring a sustainable future. Continuous product improvements and new technologies are required to increase performance and to meet markets requirements. By implementing design optimization in the design process it enables the potential of supporting design exploration, which is beneficial when products with high performance are developed. The purpose was to show the potential of design optimization supported by simulation driven design as a tool in the development process. To examine an alternative way of working for design engineers, elaborating more competitive products in terms of economical and performance aspects. Furthermore, to minimize time and iterations between divisions by developing better initial concept proposals. The alternative working method was developed iteratively in parallel with a case study. The case study was a suction strainer and were used for method improvements and validation, as well as decision basis for the included sub-steps. The working method for implementing design optimization and simulation driven design ended up with a procedure consisted of three main phases, concept generation, detail design and verification. In the concept generation phase topology optimization was used, which turned out to be a beneficial method to find optimized solutions with few inputs. The detail design phase consisted of a parameterized CAD model of the concept which then was shape optimized. The shape optimization enabled design exploration of the concept which generated valuable findings to the product development. Lastly the optimized design was verified with more thorough methods, in this case verification with FE-experts. The working method was tested and verified on the case study component, this resulted in valuable knowledge for future designs for similar components. The optimized component resulted in a performance increase where the weight was decrease by 54% compared with a reference product.

Afin de rendre les piles à combustible à membrane échangeuse de protons viables économiquement dans le domaine automobile, des problèmes de durabilité et de coût sont à résoudre. La compréhension et le contrôle des dégradations à l'intérieur de la cellule et surtout de l'AME sont toujours le centre d’intérêt de nombreux laboratoires mais aussi d'industriels. Les milliers d'arrêt-démarrages subis par la pile provoquent une importante corrosion du support carbone. Le platine utilisé étant un catalyseur onéreux, la modélisation numérique permet l'analyse de phénomènes à moindre coût.Dans ces travaux, deux modèles ont été développés afin de modéliser les phases transitoires que sont les arrêt-démarrages. Tout d'abord, une étude sur les performances de la pile a été effectuée en utilisant le modèle. Le couplage entre les modèles le long du canal et dent/canal est introduit. Ensuite, une analyse des phénomènes se déroulant durant les arrêt-démarrages est effectuée. Des phases temporelles sont proposées afin de découper ces différents phénomènes. Le mécanisme des courants inverses (durant lequel la corrosion du carbone apparaît) est minutieusement détaillé avec l'aide du modèle. L'accent est porté sur les hétérogéneités de dégradations apparaissant entre l'entrée et la sortie mais aussi entre le canal et la dent. Enfin, le modèle est utilisé afin de simuler et proposer des stratégies de mitigations. Les tendances attendues par la littérature sont confirmées mais aussi évaluées. Parmi les idées suggerées, l'optimisation du design dent/canal tout au long du canal est proposée afin de limiter les dégradations. / In order to make Proton Exchange Membrane Fuel Cells economically viable for an automotive application, durability and cost problems have to be addressed. Understanding and mitigating degradations inside the cell especially in the MEA are still the focus of several laboratories and also industrials. The several thousands startups and shutdowns that the fuel cell underwent induce severe corrosion of the carbon support. As the catalyst used is expensive, namely platinum, modeling is a great asset to comprehend and analyze this phenomenon costwise.In this work, two models were developed for modeling the transient phases that are the startup and shutdown. First a performance study is presented to validate the use of the model and to introduce the coupling between the along the channel model and the rib/channel model. Then an analysis of the phenomena occurring during the startup (and shutdown) is carried out. Phases are suggested to break down the different phenomena. The reverse-current decay mechanism, when carbon corrosion occurs, is thoroughly detailed using the model. Degradation heterogeneities are highlighted whether they are between inlet and outlet or rib and channel. Finally the model is used to emulate and suggest mitigation strategies. Degradation trends are confirmed and evaluated. New ideas like an original flow field design are tested to mitigate degradation.

O mercado de tintas e vernizes é um dos maiores demandantes de solventes. Nos últimos anos, a reformulação de sistemas solventes tem ganhado forca, e três são as razões principais para isso: redução de custo, mantendo o desempenho; melhoria do desempenho; e busca por solventes menos agressivos ao homem e a natureza, quer seja voluntariamente ou por imposição de legislação. Dentre as varias propriedades necessárias de um solvente para formulação de tintas e vernizes, a taxa de evaporação e os parâmetros de solubilidade de Hansen são os mais importantes. Em sua grande maioria, os ajustes e substituições de formulação de solventes são realizados pelo método da tentativa e erro, que é caro e demorado. A teoria e modelos sobre os parâmetros de solubilidade já são bastante conhecidos, mas pouco foi explorado sobre modelos para prever a taxa de evaporação de solventes e misturas com base no método do evaporômetro determinado pela ASTM D3539. O objetivo deste trabalho é avaliar os modelos disponíveis em literatura para cálculo da taxa de evaporação de solventes e suas misturas, e por fim, com base em conceitos de otimização e projeto de mistura auxiliado por computador (Computer-Aided Mixture/Blend Design), propor uma metodologia para obter misturas de custo otimizado que satisfaçam as restrições de evaporação e solubilidade. Devido às equações das restrições dos modelos das propriedades, este problema de otimização é classificado como programação não-linear (NLP Non-Linear Programming). Embora os modelos de taxa de evaporação dos solventes e das misturas não apresentem resultados consistentes para todo e qualquer caso, devido a desvios muitas vezes causados pelos solventes de rápida evaporação, estes modelos associados à teoria de solubilidade de Hansen se tornam uma ferramenta de grande importância na formulação de sistemas solventes. Os resultados observados com esta metodologia têm grande concordância com os resultados obtidos experimentalmente. / Paint and coatings are one of the most solvent demanding markets. In recent years, reformulation of solvent systems has gained strength, and there are three main reasons: cost reduction maintaining performance, performance improvement, and the search for less aggressive solvents to human and environment, voluntarily or by legislation. Among several properties required for these solvents, evaporation rate and Hansen solubility parameters are the most important ones. Most adjustments and replacements of solvents in formulation are performed by trial and error methods, which are expensive and time consuming. The solubility parameters theory and models are already well known but little was explored about models to predict solvents and mixtures evaporation rate based on the evaporometer method determined by ASTM D3539. The object of this study is to evaluate the available models for calculating the evaporation rate of solvents and their mixtures, and then, based on optimization concepts and computer-aided Mixture/Blend Design, to propose a methodology to obtain cost-optimized mixtures that meet evaporation and solubility constraints. Due to the equations restrictions of properties models, this optimization problem is classified as NLP - Non-Linear Programming. Although evaporation rate models of solvents and mixtures do not show consistent results for every case most deviations were caused by fast evaporation solvents -, these models associated with the Hansen solubility theory become an important tool in the solvent systems formulation. The results observed with this method have good agreement with experimental results.

The present thesis deals with the analysis of Environmental Control System (ECS) as a part of the aircraft conceptual design. The research focuses on developing methods for modelling, simulation and optimization of current and future cooling technologies suitable for aircraft applications. The work started with a pre-study in order to establish the suitability of different cooling technologies for ECS application. Therefore, five technologies namely, Bootstrap (BS), Reverse-Bootstrap (RBS), vapour cycle system (VCS), magnetic cooling (MC) and thermo-electric cooling (EC), were assessed from a theoretical point of view by the method of benchmarking. This resulted into the selection of three most suitable technologies that were further modelled and simulated in Dymola. In order to compare the optimum designs for each technology, the models were optimized using the modeFRONTIER software. The comparison was performed based on the optimum ratio of maximum power of cooling and minimum fuel penalty. The results showed that VCS has the “best” performances compared to BS and RBS. In addition to the active technologies, passive cooling methods such as liquid cooling by means of jet-fuel and poly-alpha-olefin were considered to address high heat transfer rates. In order to apply the cooling technologies in the ECS, concept system architectures were formulated using the functional analysis. This led to the identification of basic functions, components and sub-systems interaction. Based on the comparison carried out previously and the functional analysis, two ECS architectures were developed. Design optimization procedure was applied further in order to assess each concept and also to study the differences between the two concept architectures. The results depict the complex interaction of different key parameters of the architectures and their influence on the outcome. The study culminated with a proposed methodology for formulation of systems architecture using information from the optimization results and a robust functional analysis method. To sum up, the thesis proposes a simulation-based optimization method that allows inclusion of ECS system in aircraft conceptual design phase. The study also proves the complexity of the conceptual design stage for ECS architectures which highly influences the design of the combat aircraft.

Os materiais compósitos (composites) poliméricos reforçados são bem conhecidos por sua excelente combinação de alta rigidez estrutural e baixo peso. Sua inerente anisotropia permite ao projetista customizar as propriedades do material juntamente com as características geométricas e funcionais da peça de maneira a se obter o desempenho desejado. Desta forma, é de fundamental importância que o projetista disponha de ferramentas de auxílio para análise e otimização que possibilitem dimensionar de modo rápido e seguro a peça a ser fabricada considerando-se os requisitos estruturais, características funcionais e restrições impostas pelo processo de fabricação. Dentre esses requisitos, considera-se o comportamento dinâmico de componentes fabricados a partir destes materiais. Sendo assim, confeccionou-se amostras na forma de vigas através do processo de hand-lay-up (moldagem manual) seguido de uma moldagem sob pressão e aquecimento. Um banco de ensaios foi montado com amostras a base de resina epoxi e fibra de vidro possuindo diferentes sequências de empilhamento de lâminas para a realização de uma análise modal. A partir dos resultados obtidos experimentalmente, buscou-se verificar a influência da sequência de empilhamento das lâminas nas frequências naturais e nos fatores de amortecimento modal. Tais experimentos foram também utilizados para validar os resultados do modelo teórico proveniente de uma análise numérica realizada pelo método dos elementos finitos. Finalizando, o trabalho propõe um ciclo de desenvolvimento de projeto para estes componentes integrando procedimentos de simulação numérica e experimentais visando a otimização do projeto do componente com maior rapidez, confiabilidade e menor custo. / The composite materials are well known by their excellent combination of high structural stiffness and low weight. Their inherent anisotropy allows the designer to tailor the material in order to achieve the desired performance requirements. Thus, it is of fundamental importance to develop tools that allow the designer to obtain optimized designs considering the structural requirements, functional characteristics and restrictions imposed by the production process. Within these requirements, this work considers the dynamic behavior of components manufactured from polymer reinforced materials (epoxy and glass fiber). To this end, some beams were made using the hand-lay-up process followed by a molding under pressure and heating. A set of experimental dynamic tests were carried out using samples with different fiber orientations and stacking sequences. From the results, the influence of the fibers orientations as well as the stacking sequences on the natural frequencies and modal damping were investigate. Also, these experiments were used to validate the theoretical model and the results obtained from the finite element analysis. Finally, it was proposed a design cycle which integrates experimental and theoretical procedures in order to get optimized designs in a faster and reliable way.

Os materiais compósitos (composites) poliméricos reforçados são bem conhecidos por sua excelente combinação de alta rigidez estrutural e baixo peso. Sua inerente anisotropia permite ao projetista customizar as propriedades do material juntamente com as características geométricas e funcionais da peça de maneira a se obter o desempenho desejado. Desta forma, é de fundamental importância que o projetista disponha de ferramentas de auxílio para análise e otimização que possibilitem dimensionar de modo rápido e seguro a peça a ser fabricada considerando-se os requisitos estruturais, características funcionais e restrições impostas pelo processo de fabricação. Dentre esses requisitos, considera-se o comportamento dinâmico de componentes fabricados a partir destes materiais. Sendo assim, confeccionou-se amostras na forma de vigas através do processo de hand-lay-up (moldagem manual) seguido de uma moldagem sob pressão e aquecimento. Um banco de ensaios foi montado com amostras a base de resina epoxi e fibra de vidro possuindo diferentes sequências de empilhamento de lâminas para a realização de uma análise modal. A partir dos resultados obtidos experimentalmente, buscou-se verificar a influência da sequência de empilhamento das lâminas nas frequências naturais e nos fatores de amortecimento modal. Tais experimentos foram também utilizados para validar os resultados do modelo teórico proveniente de uma análise numérica realizada pelo método dos elementos finitos. Finalizando, o trabalho propõe um ciclo de desenvolvimento de projeto para estes componentes integrando procedimentos de simulação numérica e experimentais visando a otimização do projeto do componente com maior rapidez, confiabilidade e menor custo. / The composite materials are well known by their excellent combination of high structural stiffness and low weight. Their inherent anisotropy allows the designer to tailor the material in order to achieve the desired performance requirements. Thus, it is of fundamental importance to develop tools that allow the designer to obtain optimized designs considering the structural requirements, functional characteristics and restrictions imposed by the production process. Within these requirements, this work considers the dynamic behavior of components manufactured from polymer reinforced materials (epoxy and glass fiber). To this end, some beams were made using the hand-lay-up process followed by a molding under pressure and heating. A set of experimental dynamic tests were carried out using samples with different fiber orientations and stacking sequences. From the results, the influence of the fibers orientations as well as the stacking sequences on the natural frequencies and modal damping were investigate. Also, these experiments were used to validate the theoretical model and the results obtained from the finite element analysis. Finally, it was proposed a design cycle which integrates experimental and theoretical procedures in order to get optimized designs in a faster and reliable way.

Multidisciplinary design optimization (MDO) refers to the process of designing systems characterized by the interaction of multiple interconnected disciplines. High-fidelity MDO usually requires large computational resources due to the computational cost of achieving multidisciplinary consistent solutions by coupling high-fidelity physics-based solvers. Gradient-based minimization algorithms are generally applied to find local minima, due to their efficiency in solving problems with a large number of design variables. This represents a limitation to performing global MDO and integrating black-box type analysis tools, usually not providing gradient information. The latter issues generally inhibit a wide use of MDO in complex industrial applications. An architecture named multi-criterion adaptive sampling MDO (MCAS-MDO) is presented in the current research for complex simulation-based applications. This research aims at building a global derivative-free optimization tool able to employ high-fidelity/expensive black-box solvers for the analysis of the disciplines. MCAS-MDO is a surrogate-based architecture featuring a variable level of coupling among the disciplines and is driven by a multi-criterion adaptive sampling (MCAS) assessing coupling and sampling uncertainties. MCAS uses the dynamic radial basis function surrogate model to identify the optimal solution and explore the design space through parallel infill of new solutions. The MCAS-MDO is tested versus a global derivative-free multidisciplinary feasible (MDF) approach, which solves fully-coupled multidisciplinary analyses, for two analytical test problems. Evaluation metrics include number of function evaluations required to achieve the optimal solution and sample distribution. The MCAS-MDO outperforms the MDF showing a faster convergence by clustering refined function evaluations in the optimum region. The architecture is applied to a steady fluid-structure interaction (FSI) problem, namely the design of a tapered three-dimensional carbon fiber-reinforced plastic hydrofoil for minimum drag. The objective is the design of shape and composite material layout subject to hydrodynamic, structural, and geometrical constraints. Experimental data are available for the original configuration of the hydrofoil and allow validating the FSI analysis, which is performed coupling computational fluid dynamics, solving the Reynolds averaged Navier-Stokes equations, and finite elements, solving the structural equation of elastic motion. Hydrofoil forces, tip displacement, and tip twist are evaluated for several materials providing qualitative agreement with the experiments and confirming the need for the two-way versus one-way coupling approach in case of significantly compliant structures. The free-form deformation method is applied to generate shape modifications of the hydrofoil geometry. To reduce the global computational expense of the optimization, a design space assessment and dimensionality reduction based on the Karhunen–Loève expansion (KLE) is performed off-line, i.e. without the need for high-fidelity simulations. It provides with a selection of design variables for the problem at hand through basis rotation and re-parametrization. By using the KLE, an efficient design space is identified for the current problem and the number of design variables is reduced by 92%. A sensitivity analysis is performed prior to the optimization to assess the variability associated with the shape design variables and the composite material design variable, i.e. the fiber orientation. These simulations are used to initialize the surrogate model for the optimization, which is carried out for two models: one in aluminum and one in composite material. The optimized designs are assessed by comparison with the original models through evaluation of the flow field, pressure distribution on the body, and deformation under the hydrodynamic load. The drag of the aluminum and composite material hydrofoils is reduced by 4 and 11%, respectively, increasing the hydrodynamic efficiency by 4 and 7%. The optimized designs are obtained by evaluating approximately 100 designs. The quality of the results indicates that global derivative-free MDO of complex engineering applications using expensive black-box solvers can be achieved at a feasible computational cost by minimizing the design space dimensionality and performing an intelligent sampling to train the surrogate-based optimization.

The objective of this study is to develop an integrated multibody dynamics computational framework for the deterministic and reliability-based design optimization of wind turbine drivetrains to obtain an optimal wind turbine gear design that ensures a target reliability under wind load and gear manufacturing uncertainties. Gears in wind turbine drivetrains are subjected to severe cyclic loading due to variable wind loads that are stochastic in nature. Thus, the failure rate of drivetrain systems is reported to be relatively higher than the other wind turbine components. It is known in wind energy industry that improving reliability of drivetrain designs is one of the key issues to make wind energy competitive as compared to fossil fuels. Furthermore, a wind turbine is a multi-physics system involving random wind loads, rotor blade aerodynamics, gear dynamics, electromagnetic generator and control systems. This makes an accurate prediction of product life of drivetrains challenging and very limited studies have been carried out regarding design optimization including the reliability-based design optimization (RBDO) of geared systems considering wind load and manufacturing uncertainties. In order to address these essential and challenging issues on design optimization of wind turbine drivetrains under wind load and gear manufacturing uncertainties, the following issues are discussed in this study: (1) development of an efficient numerical procedure for gear dynamics simulation of complex multibody geared systems based on the multi-variable tabular contact search algorithm to account for detailed gear tooth contact geometry with profile modifications or surface imperfections; (2) development of an integrated multibody dynamics computational framework for deterministic and reliability-based design optimization of wind turbine drivetrains using the gear dynamics simulation software developed in (1) and RAMDO software by incorporating wide spatiotemporal wind load uncertainty model, pitting gear tooth contact fatigue model, and rotor blade aerodynamics model using NREL AeroDyn/FAST; and (3) deterministic and reliability-based design optimization of wind turbine drivetrain to minimize total weight of a drivetrain system while ensuring 20-year reliable service life with wind load and gear manufacturing uncertainties using the numerical procedure developed in this study. To account for the wind load uncertainty, the joint probability density function (PDF) of 10-minute mean wind speed (V₁₀) and 10-minute turbulence intensity (I₁₀) is introduced for wind turbine drivetrain dynamics simulation. To consider wide spatiotemporal wind uncertainty (i.e., wind load uncertainty for different locations and in different years), uncertainties of all the joint PDF parameters of V₁₀, I₁₀ and copula are considered, and PDF for each parameter is identified using 249 sets of wind data. This wind uncertainty model allows for the consideration of a wide range of probabilistic wind loads in the contact fatigue life prediction. For a given V₁₀ and I₁₀ obtained from the stochastic wind model, the random time-domain wind speed data is generated using NREL TurbSim, and then inputted into NREL FAST to perform the aerodynamic simulation of rotor blades to predict the transmitted torque and speed of the main shaft of the drivetrain that are sent to the multibody gear dynamics simulation as an input. In order to predict gear contact fatigue life, a high-fidelity gear dynamics simulation model that considers the detailed gear contact geometry as well as the mesh stiffness variation needs to be developed to find the variability of maximum contact stresses under wind load uncertainty. This, however, leads to a computationally intensive procedure. To eliminate the computationally intensive iterative online collision detection algorithm, a numerical procedure for the multibody gear dynamics simulation based on the tabular contact search algorithm is proposed. Look-up contact tables are generated for a pair of gear tooth profiles by the contact geometry analysis prior to the dynamics simulation and the contact points that fulfill the non-conformal contact condition and mesh stiffness at each contact point are calculated for all pairs of gears in the drivetrain model. This procedure allows for the detection of gear tooth contact in an efficient manner while retaining the precise contact geometry and mesh stiffness variation in the evaluation of mesh forces, thereby leading to a computationally efficient gear dynamics simulation suited for the design optimization procedure considering wind load uncertainty. Furthermore, the accuracy of mesh stiffness model introduced in this study and transmission error of gear tooth with tip relief are discussed, and a wind turbine drivetrain model developed using this approach is validated against test data provided in the literature. The gear contact fatigue life is predicted based on the gear tooth pitting fatigue criteria and is defined by the sum of the number of stress cycles required for the fatigue crack initiation and the number required for the crack to propagate from the initial to the critical crack length based on Paris-Erdogan equation for Mode II fracture. All the above procedures are integrated into the reliability-based design optimization software RAMDO for design optimization and reliability analysis of wind turbine drivetrains under wind load and manufacturing uncertainties. A 750kW GRC wind turbine gearbox model is used to perform the design optimization and the reliability analysis. A deterministic design optimization (DDO) is performed first using an averaged joint PDF of wind load to ensure a 20-year service life. To this end, gear face width and tip relief (profile modification) are selected as design variables and optimized such that 20-year fatigue life is ensured while minimizing the total weight of drivetrains. It is important to notice here that an increase in face width leads to a decrease in the fatigue damage, but an increase in total weight. On the other hand, the tip relief has almost no effect on the total weight, but it has a major impact on the fatigue damage. It is shown in this study that the optimum tip relief allows for lowering the greatest maximum shear stresses on the tooth surface without relying heavily on face width widening to meet the 20-year fatigue life constraint and it leads to reduction of total drivetrain weight by 8.4%. However, if only face width is considered as design variable, total weight needs to be increased by 4.7% to meet the 20-year fatigue life constraint. Furthermore, the reliability analysis at the DDO optimum design is carried out considering the large spatiotemporal wind load uncertainty and gear manufacturing uncertainty. Local surrogate models at DDO optimum design are generated using Dynamic Kriging method in RAMDO software to evaluate the gear contact fatigue damage. 49.5% reliability is obtained at the DDO optimum design, indicating that the probability of failure is 50.5%, which is as expected for the DDO design. RBDO is, therefore, necessary to further improve the reliability of the wind turbine drivetrain. To this end, the sampling-based reliability analysis is carried out to evaluate the probability of failure for each design using the Monte Carlo Simulation (MCS) method. However, the use of a large number of MCS sample points leads to a large number of contact fatigue damage evaluation time using the 10-minute multibody drivetrain dynamics simulation, resulting in the RBDO calculation process being computational very intensive. In order to overcome the computational difficulty resulting from the use of high-fidelity wind turbine drivetrain dynamics simulation, intermediate surrogate models are created prior to the RBDO process using the Dynamic Kriging method in RAMDO and used throughout the entire RBDO iteration process. It is demonstrated that the RBDO optimum obtained ensures the target 97.725 % reliability (two sigma quality level) with only 1.4 % increase in the total weight from the baseline design with 8.3 % reliability. This result clearly indicates the importance of incorporating the tip relief as a design variable that prevents larger increase in the face width causing an increase in weight. This, however, does not mean that a larger tip relief is always preferred since an optimum tip relief amount depends on stochastic wind loads and an optimum tip relief cannot be found deterministically. Furthermore, accuracy of the RBDO optimum obtained using the intermediate surrogate models is verified by the reliability analysis at the RBDO optimum using the local surrogate models. It is demonstrated that the integrated design optimization procedure developed in this study enables the cost effective and reliable design of wind turbine drivetrains.