The probabilistic design of dynamic systems with degrading components is difficult. Design of dynamic systems typically involves the optimization of a time-invariant performance measure, such as Energy, that is estimated using a dynamic response, such as angular speed. The mechanistic models developed to approximate this performance measure are too complicated to be used with simple design calculations and lead to lengthy simulations. When degradation of the components is assumed, in order to determine suitable service times, estimation of the failure probability over the product lifetime is required. Again, complex mechanistic models lead to lengthy lifetime simulations when the Monte Carlo method is used to evaluate probability. Based on these problems, an efficient methodology is presented for probabilistic design of dynamic systems and to estimate the cumulative distribution function of the time to failure of a performance measure when degradation of the components is assumed. The four main steps include; 1) transforming the dynamic response into a set of static responses at discrete cycle-time steps and using Singular Value Decomposition to efficiently estimate a time-invariant performance measure that is based upon a dynamic response, 2) replacing the mechanistic model with an approximating function, known as a “metamodel” 3) searching for the best design parameters using fast integration methods such as the First Order Reliability Method and 4) building the cumulative distribution function using the summation of the incremental failure probabilities, that are estimated using the set-theory method, over the planned lifetime. The first step of the methodology uses design of experiments or sampling techniques to select a sample of training sets of the design variables. These training sets are then input to the computer-based simulation of the mechanistic model to produce a matrix of corresponding responses at discrete cycle-times. Although metamodels can be built at each time-specific column of this matrix, this method is slow especially if the number of time steps is large. An efficient alternative uses Singular Value Decomposition to split the response matrix into two matrices containing only design-variable-specific and time-specific information. The second step of the methodology fits metamodels only for the significant columns of the matrix containing the design variable-specific information. Using the time-specific matrix, a metamodel is quickly developed at any cycle-time step or for any time-invariant performance measure such as energy consumed over the cycle-lifetime. In the third step, design variables are treated as random variables and the First Order Reliability Method is used to search for the best design parameters. Finally, the components most likely to degrade are modelled using either a degradation path or a marginal distribution model and, using the First Order Reliability Method or a Monte Carlo Simulation to estimate probability, the cumulative failure probability is plotted. The speed and accuracy of the methodology using three metamodels, the Regression model, Kriging and the Radial Basis Function, is investigated. This thesis shows that the metamodel offers a significantly faster and accurate alternative to using mechanistic models for both probabilistic design optimization and for estimating the cumulative distribution function. For design using the First-Order Reliability Method to estimate probability, the Regression Model is the fastest and the Radial Basis Function is the slowest. Kriging is shown to be accurate and faster than the Radial Basis Function but its computation time is still slower than the Regression Model. When estimating the cumulative distribution function, metamodels are more than 100 times faster than the mechanistic model and the error is less than ten percent when compared with the mechanistic model. Kriging and the Radial Basis Function are more accurate than the Regression Model and computation time is faster using the Monte Carlo Simulation to estimate probability than using the First-Order Reliability Method.

Vários problemas de interesse em Ciência e Engenharia são formulados como problemas de otimização. A complexidade dos problemas modernos tem levado ao desenvolvimento de modelos matemáticos de complexidade crescente, resultando em modelos de simulação computacionalmente custosos. Algoritmos Genéticos (AG), inspirados na Teoria de Evolução por seleção natural, são ferramentas versáteis em problemas difíceis de busca e otimização. Entretanto, eles usualmente requerem um elevado número de avaliações até a obtenção de uma solução viável ou satisfatória. Em um cenário de simulações dispendiosas, o uso de Algoritmos Genéticos pode tornar-se proibitivo. Uma possível solução para este problema é o uso de um metamodelo, para ser usado no processo de otimização no lugar do modelo de simulação. Nesta tese desenvolveu-se uma metodologia para o uso combinado de AG e metamodelos para otimização mono- e multi-objetivo de alto custo computacional, onde metamodelos baseados em similaridade são incorporados nos AG com o objetivo de melhorar o seu desempenho. A metodologia foi aplicada em problemas de otimização coletados da literatura, e em problemas de Otimização Estrutural, demonstrando sua aplicabilidade e estabelecendo esta como uma alternativa para o melhoramento de soluções em um contexto de orçamento fixo de simulações.

Addressing Quality of Service and specification of quality attributes has been gaining a growing importance in the software engineering area. The research presented in this study investigates different approaches to specification of Quality of Service. UML profile for Quality of Service is one of the standards of the Quality of Service specification and is described in the QoS specification context. The research aim of this thesis is the evaluation of the UML profile for Quality of Service against the following criteria: expressiveness, reusability, understandability, applicability and tool support, as well as further comparison of the profile with other Quality of Service specification languages. To perform that, several tasks and activities were conducted, such as a survey on different QoS specification languages, an examination of the UML profile for Quality of Service, the formulation of the evaluation criteria, and the appliance of the criteria in the evaluation and comparison processes. This study is performed from the perspective of readers and users of the profile that are not UML experts but have sufficient knowledge of UML in terms of software systems analysis and design. The context of the UML profile and Quality of Service aspects include basic concepts of the UML 2.0 and Quality of Service which will be described along the thesis. The main contribution of the thesis is the evaluation of the UML profile for Quality of Service against a set of criteria, followed by explanations on the contents of the profile and how Quality of Service is specified within it. The presented comparison of the UML profile and other Quality of Service specification languages could be the basis for a user to decide what language to use in a particular situation. This study can be comprehended as a starting point for further evaluation of the UML profile and its comparison with other quality specification languages.

Dans le contexte actuel de transition énergétique, les acteurs de la production électrique (dont EDF) s'orientent de plus en plus vers les technologies "bas carbone", permettant de développer leur mix énergétique et d'assurer une production toujours plus respectueuse de l'environnement. Parmi l'ensemble des alternatives progressivement industrialisées au cours de ces dernières décennies, l'énergie éolienne voit son développement s'accélérer. De nouveaux projets voient le jour, notamment avec le développement de parcs éoliens posés en mer le long des côtes françaises.Afin de garantir une sécurité maximale des installations vis-à-vis des défaillances mécaniques, les ingénieurs doivent mettre en place un ensemble de vérifications ayant pour but d'assurer l'intégrité structurelle pendant une durée de vie donnée. Cette étape, nécessaire à la certification et donc à l'industrialisation du projet, exige un investissement numérique important. Dans le cas particulier de l'estimation de l'endommagement à durée de vie, un ensemble complet d'analyses doit être effectué afin de simuler les réactions structurelles en différents points de la conception et ce, pour l'ensemble des conditions environnementales de chargement possibles (cas de charge). Au total, quelques milliers de simulations correspondant à l'ensemble des situations probables sont à prévoir pour la seule estimation de l'endommagement à durée de vie. De plus, la prise en compte des différents phénomènes physiques du problème (aérodynamique, hydrodynamique, mécanique élastique), ainsi que la considération des non-linéarités des réponses liées à l'asservissement de la turbine, impliquent l'utilisation de codes de résolution temporels et multi-physiques coûteux pour chacune des situations de chargement à simuler.Afin de réduire l'investissement lié à l'estimation de cet endommagement, l'utilisation de méthodes numériques de substitution (également appelées métamodèles) est une alternative prometteuse. Ces méthodologies ont montré leur efficacité dans divers domaines de l'ingénierie permettant d'approcher, par diverses hypothèses statistiques, la réponse de modèles numériques en ne considérant qu'un nombre réduit de simulations.Ce travail de thèse s'est focalisé sur le développement d'outils numériques pour le dimensionnement efficace des structures éoliennes en mer et plus particulièrement sur l'utilisation des métamodèles de Krigeage (ou méthode de régression par processus gaussien) pour l'estimation de l'endommagement mécanique. Sous certaines hypothèses, cette méthode de substitution se prête particulièrement bien à l'approximation des réponses de modèles physiques, notamment grâce à la mise en place facilitée d'architectures itératives d'enrichissement ("active learning strategy"). Deux domaines ont principalement été étudiés : l'estimation rapide des quantités d'endommagement structurel par le développement de la méthode "Adaptive Kriging for Damage Assessment" (AK-DA) et les possibilités d'utilisation de cette dernière dans le cadre d'études de la fiabilité conceptuelle au regard de la tenue à l'endommagement. L'applicabilité de ces méthodes a été illustrée via l'utilisation d'exemples numériques inspirés du contexte industriel et de ses contraintes. / The mechanical certification of wind turbine structures is required for the funding of newoffshore projects on the French coasts. In order to ensure a maximal safety level of installations,a series of structural analyzes are required by the certification bodies. Amongst all, thedamage based computations represent an important numerical effort for EDF. The presentedworks focus on the applicability and the performances of Kriging metamodels for the estimationof the lifetime cumulated damage of offshore wind turbine structures (AK-DA approach)and the damage based reliability assessment of new designs (AK-MCS/AK-DA coupling).

Engenharia Dirigida por Modelos, ou Model Driven Engineering (MDE), é uma abordagem para desenvolvimento de software a partir de modelos. Código-fonte ou artefatos executáveis são gerados de forma automática, total ou parcialmente, a partir de transformações descritas por funções de mapeamento. Com isso, obtém-se as vantagens de desenvolver software em nível de abstração maior em relação às linguagens de programação tradicionais e da possibilidade de gerar implementações do mesmo sistema para diversas plataformas a partir do mesmo modelo. Uma das áreas de pesquisa da MDE é a formalização de teorias e conceitos relacionados a essa abordagem, tais como modelos, metamodelos, relação de conformidade, operações sobre metamodelos, etc. Embora existam na literatura propostas de formalização, observam-se lacunas e falta de consenso geral, o que leva autores a introduzir suas próprias definições quando desejam apresentar desenvolvimentos ou deduções, as quais nem sempre se encaixam entre si. Alguns autores consideram que, enquanto uma completa formalização de conceitos e relações da MDE não for estabelecida, seus potenciais podem não ser plenamente atingidos. A partir de estudos de proposições existentes na literatura, identificação de lacunas e necessidades, este trabalho apresenta uma proposta de arcabouço teórico para MDE, baseada nas teorias de conjuntos e linguagens, e em lógica de primeira ordem. Conceitos e operações relacionados à MDE são definidos sobre uma base comum e, a partir dela, algumas formulações originais são desenvolvidas, tais como a função de mesclagem de metamodelos e uma definição de modelos executáveis, que podem servir como base para a construção de motores de execução de modelos, consolidando e ampliando o conhecimento da área teórica da MDE. Do ponto de vista de aplicabilidade prática, a proposta é validada por meio de uma ferramenta de prova de conceito, criada também como parte desta pesquisa, e pela apresentação de exemplos de aplicações. / Model Driven Engineering (MDE) is a software development approach in which models are essential artifacts to build software systems. Source code or executable artifacts are automatically generated, completely or partially, by transformations described by mapping functions. Two main advantages can be obtained: software development in a higher level of abstraction than that of traditional programming languages and the possibility of generating implementations of the same system for multiple platforms from the same source model. One of the research fields of MDE is the formalization of theories and concepts related to this approach, such as models, metamodels, conformity relationship, operations over metamodels, etc. Although there are proposals of formalization in the literature, some gaps and a lack of general consensus can be identified, which leads some authors to introduce their own definitions when they want to present their work. These definitions not always fit to each other. Some authors claim that unless a complete formalization of MDE concepts and relations is given, the potentials of this approach may not be fully unfolded. Starting from studies on existing proposals, gaps and requirements, this work proposes a theoretical framework for MDE based on the set theory, language theory and first order logic. Concepts and operations related to MDE are defined over a common basis and some original formulations are developed, such as the metamodel merging function and definitions about executable models, which can be used as a foundation to build model execution engines, consolidating and expanding the theoretical field of MDE. From the applicability point of view, the proposal is validated by a proof-of-concept tool, created as part of this research, and by examples of applications.

Made available in DSpace on 2015-03-04T18:51:15Z (GMT). No. of bitstreams: 1 Goliatt tese.pdf: 3293381 bytes, checksum: e89a55efe1733bca4d491ccb2aca5af1 (MD5) Previous issue date: 2010-06-24 / Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior / Vários problemas de interesse em Ciência e Engenharia são formulados como problemas de otimização. A complexidade dos problemas modernos tem levado ao desenvolvimento de modelos matemáticos de complexidade crescente, resultando em modelos de simulação computacionalmente custosos. Algoritmos Genéticos (AG), inspirados na Teoria de Evolução por seleção natural, são ferramentas versáteis em problemas difíceis de busca e otimização. Entretanto, eles usualmente requerem um elevado número de avaliações até a obtenção de uma solução viável ou satisfatória. Em um cenário de simulações dispendiosas, o uso de Algoritmos Genéticos pode tornar-se proibitivo. Uma possível solução para este problema é o uso de um metamodelo, para ser usado no processo de otimização no lugar do modelo de simulação. Nesta tese desenvolveu-se uma metodologia para o uso combinado de AG e metamodelos para otimização mono- e multi-objetivo de alto custo computacional, onde metamodelos baseados em similaridade são incorporados nos AG com o objetivo de melhorar o seu desempenho. A metodologia foi aplicada em problemas de otimização coletados da literatura, e em problemas de Otimização Estrutural, demonstrando sua aplicabilidade e estabelecendo esta como uma alternativa para o melhoramento de soluções em um contexto de orçamento fixo de simulações.

Une prédiction fidèle des écoulements hypersoniques à haute enthalpie est capitale pour les missions d'entrée atmosphérique. Cependant, la présence d'incertitudes est inévitable, sur les conditions de l'écoulement libre comme sur d'autres paramètres des modèles physico-chimiques. Pour cette raison, une quantification rigoureuse de l'effet de ces incertitudes est obligatoire pour évaluer la robustesse et la prédictivité des simulations numériques. De plus, une reconstruction correcte des paramètres incertains à partir des mesures en vol peut aider à réduire le niveau d'incertitude sur les sorties. Dans ce travail, nous utilisons un cadre statistique pour la propagation directe des incertitudes ainsi que pour la reconstruction inverse des conditions de l'écoulement libre dans le cas d'écoulements de rentrée atmosphérique. La possibilité d'exploiter les mesures de flux thermique au nez du véhicule pour la reconstruction des variables de l'écoulement libre et des paramètres incertains du modèle est évaluée pour les écoulements de rentrée hypersoniques. Cette reconstruction est réalisée dans un cadre bayésien, permettant la prise en compte des différentes sources d'incertitudes et des erreurs de mesure. Différentes techniques sont introduites pour améliorer les capacités de la stratégie statistique de quantification des incertitudes. Premièrement, une approche est proposée pour la génération d'un métamodèle amélioré, basée sur le couplage de Kriging et Sparse Polynomial Dimensional Decomposition. Ensuite, une méthode d'ajoute adaptatif de nouveaux points à un plan d'expériences existant est présentée dans le but d'améliorer la précision du métamodèle créé. Enfin, une manière d'exploiter les sous-espaces actifs dans les algorithmes de Markov Chain Monte Carlo pour les problèmes inverses bayésiens est également exposée. / Accurate prediction of hypersonic high-enthalpy flows is of main relevance for atmospheric entry missions. However, uncertainties are inevitable on freestream conditions and other parameters of the physico-chemical models. For this reason, a rigorous quantification of the effect of uncertainties is mandatory to assess the robustness and predictivity of numerical simulations. Furthermore, a proper reconstruction of uncertain parameters from in-flight measurements can help reducing the level of uncertainties of the output. In this work, we will use a statistical framework for direct propagation of uncertainties and inverse freestream reconstruction applied to atmospheric entry flows. We propose an assessment of the possibility of exploiting forebody heat flux measurements for the reconstruction of freestream variables and uncertain parameters of the model for hypersonic entry flows. This reconstruction is performed in a Bayesian framework, allowing to account for sources of uncertainties and measurement errors. Different techniques are introduced to enhance the capabilities of the statistical framework for quantification of uncertainties. First, an improved surrogate modeling technique is proposed, based on Kriging and Sparse Polynomial Dimensional Decomposition. Then a method is proposed to adaptively add new training points to an existing experimental design to improve the accuracy of the trained surrogate model. A way to exploit active subspaces in Markov Chain Monte Carlo algorithms for Bayesian inverse problems is also proposed.

Engenharia Dirigida por Modelos, ou Model Driven Engineering (MDE), é uma abordagem para desenvolvimento de software a partir de modelos. Código-fonte ou artefatos executáveis são gerados de forma automática, total ou parcialmente, a partir de transformações descritas por funções de mapeamento. Com isso, obtém-se as vantagens de desenvolver software em nível de abstração maior em relação às linguagens de programação tradicionais e da possibilidade de gerar implementações do mesmo sistema para diversas plataformas a partir do mesmo modelo. Uma das áreas de pesquisa da MDE é a formalização de teorias e conceitos relacionados a essa abordagem, tais como modelos, metamodelos, relação de conformidade, operações sobre metamodelos, etc. Embora existam na literatura propostas de formalização, observam-se lacunas e falta de consenso geral, o que leva autores a introduzir suas próprias definições quando desejam apresentar desenvolvimentos ou deduções, as quais nem sempre se encaixam entre si. Alguns autores consideram que, enquanto uma completa formalização de conceitos e relações da MDE não for estabelecida, seus potenciais podem não ser plenamente atingidos. A partir de estudos de proposições existentes na literatura, identificação de lacunas e necessidades, este trabalho apresenta uma proposta de arcabouço teórico para MDE, baseada nas teorias de conjuntos e linguagens, e em lógica de primeira ordem. Conceitos e operações relacionados à MDE são definidos sobre uma base comum e, a partir dela, algumas formulações originais são desenvolvidas, tais como a função de mesclagem de metamodelos e uma definição de modelos executáveis, que podem servir como base para a construção de motores de execução de modelos, consolidando e ampliando o conhecimento da área teórica da MDE. Do ponto de vista de aplicabilidade prática, a proposta é validada por meio de uma ferramenta de prova de conceito, criada também como parte desta pesquisa, e pela apresentação de exemplos de aplicações. / Model Driven Engineering (MDE) is a software development approach in which models are essential artifacts to build software systems. Source code or executable artifacts are automatically generated, completely or partially, by transformations described by mapping functions. Two main advantages can be obtained: software development in a higher level of abstraction than that of traditional programming languages and the possibility of generating implementations of the same system for multiple platforms from the same source model. One of the research fields of MDE is the formalization of theories and concepts related to this approach, such as models, metamodels, conformity relationship, operations over metamodels, etc. Although there are proposals of formalization in the literature, some gaps and a lack of general consensus can be identified, which leads some authors to introduce their own definitions when they want to present their work. These definitions not always fit to each other. Some authors claim that unless a complete formalization of MDE concepts and relations is given, the potentials of this approach may not be fully unfolded. Starting from studies on existing proposals, gaps and requirements, this work proposes a theoretical framework for MDE based on the set theory, language theory and first order logic. Concepts and operations related to MDE are defined over a common basis and some original formulations are developed, such as the metamodel merging function and definitions about executable models, which can be used as a foundation to build model execution engines, consolidating and expanding the theoretical field of MDE. From the applicability point of view, the proposal is validated by a proof-of-concept tool, created as part of this research, and by examples of applications.

There is an increasing trend to consider the processes of an organization as one of its highly valuable assets. Processes are the reusable assets of an organization which define the procedures of routine working for accomplishing its goals. The software industry has the potential to become one of the most internationally dispersed high-tech industry. With growing importance of software and services sector, standardization of processes is also becoming crucial to maintain credibility in the market. Software development processes follow a lifecycle that is very similar to the software development lifecycle. Similarly, multiple phases of a process development lifecycle follow an iterative/incremental approach that leads to continuous process improvement. This incremental approach calls for a refinement based strategy to develop, execute and maintain software development processes. This thesis develops a conceptual foundation for refinement based development of software processes keeping in view the precise requirements for each individual phase of process development lifecycle. It exploits model driven engineering to present a multi-metamodel framework for the development of software processes, where each metamodel corresponds to a different phase of a process. A process undergoes a series of refinements till it is enriched with execution capabilities. Keeping in view the need to comply with the adopted standards, the architecture of process modeling approach exploits the concept of abstraction. This mechanism also caters for special circumstances where a software enterprise needs to follow multiple process standards for the same project. On the basis of the insights gained from the examination of contemporary offerings in this domain, the proposed process modeling framework tends to foster an architecture that is developed around the concepts of ''design by contract" and ''design for reuse". This allows to develop a process model that is modular in structure and guarantees the correctness of interactions between the constituent activities. Separation of concerns being the motivation, data-flow within a process is handled at a different abstraction level than the control-flow. Conformance between these levels allows to offer a bi-layered architecture that handles the flow of data through an underlying event management system. An assessment of the capabilities of the proposed approach is provided through a comprehensive patterns-based analysis, which allows a direct comparison of its functionality with other process modeling approaches.

Made available in DSpace on 2016-08-17T14:52:52Z (GMT). No. of bitstreams: 1 GEYSA HELENA GUIMARAES CHAVES.pdf: 3886332 bytes, checksum: 1e032419dfdc24d8a137ce9f3e0c992e (MD5) Previous issue date: 2008-06-26 / This research work presents a proposal for constructing and maintenance of trusting to be perceived by a pretense consumer in a process of making decisions and by means of the involved risks in commercializing in a unsafe environment, the Internet. The dissertation examine the concept of trust as well as the factors and processes that contribute to it in order to elicitate aspects that the consumer consider as relevant to deposit their trusting in an online seller. The aspects that were captured and represented by a metamodel of trusting allows the creation of independent platform models. Thus, the model of trusting can be reused and easily modified for future developments and integrations. An editor of model in the form of trees trusting is provided as plug-in for Eclipse. The mechanisms described as builders of trusting are evidences, information in the form of metrics that enable the reduction of uncertainties in an on-line transactions. Finally, a scenario that allows the description of the results obtained in this research work is presented. / Este trabalho apresenta uma proposta para construção e manutenção de confiança a ser percebida por um pretenso consumidor em um processo de tomada de decisão e mediante aos riscos envolvidos em comercializar em um ambiente inseguro, a Internet. Esta dissertação examina a natureza do conceito de confiança, bem como os fatores e processos que contribuem para a mesma, a fim de elicitar elementos que o consumidor considera como relevantes ao depositar sua crença em um vendedor on-line. Esses elementos foram capturados e representados através de um metamodelo de confiança que permite a criação de modelos independentes de plataformas. Assim, o modelo de confiança pode ser reutilizado e facilmente modificado para futuras evoluções e integrações. Um editor de modelos de confiança em forma de árvore é fornecido como plug-in para Eclipse. Os mecanismos descritos como construtores de confiança são evidências, informações em forma de métricas que possibilitam a diminuição do grau de incerteza em transações on-line. Por fim, um cenário que possibilita a descrição dos resultados obtidos na realização deste trabalho dissertativo é apresentado.