Les métaheuristiques sont une famille d'algorithmes stochastiques destinés à résoudre des problèmes d 'optimisation difficile . Utilisées dans de nombreux domaines, ces méthodes présentent l'avantage d'être généralement efficaces, sans pour autant que l'utilisateur ait à modifier la structure de base de l'algorithme qu'il utilise. Parmi celles-ci, l'Optimisation par Essaim Particulaire (OEP) est une nouvelle classe d'algorithmes proposée pour résoudre les problèmes à variables continues. Les algorithmes d'OEP s'inspirent du comportement social des animaux évoluant en essaim, tels que les oiseaux migrateurs ou les poissons. Les particules d'un même essaim communiquent de manière directe entre elles tout au long de la recherche pour construire une solution au problème posé, en s'appuyant sur leur expérience collective. Reconnues depuis de nombreuses années pour leur efficacité, les métaheuristiques présentent des défauts qui rebutent encore certains utilisateurs. Le réglage des paramètres des algorithmes est un de ceux-ci. Il est important, pour chaque probléme posé, de trouver le jeu de paramètres qui conduise à des performances optimales de l'algorithme. Cependant, cette tâche est fastidieuse et coûteuse en temps, surtout pour les utilisateurs novices. Pour s'affranchir de ce type de réglage, des recherches ont été menées pour proposer des algorithmes dits adaptatifs . Avec ces algorithmes, les valeurs des paramètres ne sont plus figées, mais sont modifiées, en fonction des résultats collectés durant le processus de recherche. Dans cette optique-là, Maurice Clerc a proposé TRIBES, qui est un algorithme d'OEP mono-objectif sans aucun paramètre de contrôle. Cet algorithme fonctionne comme une boite noire , pour laquelle l'utilisateur n'a qu'à définir le problème à traiter et le critàre d'arrêt de l'algorithme. Nous proposons dans cette thèse une étude comportementale de TRIBES, qui permet d'en dégager les principales qualités et les principaux défauts. Afin de corriger certains de ces défauts, deux modules ont été ajoutés à TRIBES. Une phase d'initialisation régulière est insérée, afin d'assurer, dès le départ de l'algorithme, une bonne couverture de l'espace de recherche par les particules. Une nouvelle stratégie de déplacement, basée sur une hybridation avec un algorithme à estimation de distribution, est aussi définie, afin de maintenir la diversité au sein de l'essaim, tout au long du traitement. Le besoin croissant de méthodes de résolution de problèmes multiobjectifs a conduit les concepteurs à adapter leurs méthodes pour résoudre ce type de problème. La complexité de cette opération provient du fait que les objectifs à optimiser sont souvent contradictoires. Nous avons élaboré une version multiobjectif de TRIBES, dénommée MO-TRIBES. Nos algorithmes ont été enfin appliqués à la résolution de problèmes de seuillage d'images médicales et au problème de dimensionnement de composants de circuits analogiques / Metaheuristics are a new family of stochastic algorithms which aim at solving difficult optimization problems. Used to solve various applicative problems, these methods have the advantage to be generally efficient on a large amount of problems. Among the metaheuristics, Particle Swarm Optimization (PSO) is a new class of algorithms proposed to solve continuous optimization problems. PSO algorithms are inspired from the social behavior of animals living in swarm, such as bird flocks or fish schools. The particles of the swarm use a direct way of communication in order to build a solution to the considered problem, based on their collective experience. Known for their e ciency, metaheuristics show the drawback of comprising too many parameters to be tuned. Such a drawback may rebu some users. Indeed, according to the values given to the parameters of the algorithm, its performance uctuates. So, it is important, for each problem, to nd the parameter set which gives the best performance of the algorithm. However, such a problem is complex and time consuming, especially for novice users. To avoid the user to tune the parameters, numerous researches have been done to propose adaptive algorithms. For such algorithms, the values of the parameters are changed according to the results previously found during the optimization process. TRIBES is an adaptive mono-objective parameter-free PSO algorithm, which was proposed by Maurice Clerc. TRIBES acts as a black box , for which the user has only the problem and the stopping criterion to de ne. The rst objective of this PhD is to make a global study of the behavior of TRIBES under several conditions, in order to determine the strengths and drawbacks of this adaptive algorithm. In order to improve TRIBES, two new strategies are added. First, a regular initialization process is defined in order to insure an exploration as wide as possible of the search space, since the beginning of the optimization process. A new strategy of displacement, based on an hybridation with an estimation of distribution algorithm, is also introduced to maintain the diversity in the swarm all along the process. The increasing need for multiobjective methods leads the researchers to adapt their methods to the multiobjective case. The di culty of such an operation is that, in most cases, the objectives are con icting. We designed MO-TRIBES, which is a multiobjective version of TRIBES. Finally, our algorithms are applied to thresholding segmentation of medical images and to the design of electronic components

A proteção de sistemas de energia elétrica possui papel extremamente importante no aspecto de garantir o fornecimento de energia de maneira segura e confiável. Assim, a ação indevida ou a não atuação deste sistema de proteção pode causar danos materiais ou econômicos tanto para as concessionárias quanto para os consumidores de energia elétrica. Dessa forma, o sistema de proteção deve estar bem ajustado para que possa garantir suas funções, sendo sensível, seletivo, confiável e rápido. Para tanto, uma boa coordenação entre os relés de proteção deve ser estabelecida. No caso de um sistema de transmissão, o qual costuma ser um sistema malhado, a proteção é comumente realizada por relés de distância aliados a relés de sobrecorrente com unidade direcional, sendo que estes funcionam como elemento de retaguarda daqueles. O processo de ajuste desses relés é um trabalho muito difícil e demorado, que pode ainda estar sujeito a erros do engenheiro de proteção responsável pelo estudo. Neste contexto, este trabalho tem como objetivo desenvolver uma metodologia baseada na otimização por enxame de partículas que obtenha automaticamente os ajustes desses relés de forma a garantir a coordenação e seletividade entre eles, tornando assim o processo de ajuste mais rápido e preciso. Dessa forma, essa metodologia pode constituir uma ferramenta de auxílio muito favorável ao engenheiro de proteção. Além disso, como em todo problema de otimização, a função objetivo e as restrições foram definidas de maneira a retratar o problema de coordenação envolvendo tanto os relés de distância quanto os direcionais de sobrecorrente. A metodologia foi aplicada a dois sistemas, um fictício com 16 relés e um sistema de transmissão real com 44 relés, sendo que em ambos os casos ela apresentou resultados bastante satisfatórios proporcionando ajustes bem coordenados. / Electrical power systems protection has a very important role in the aspect of ensuring energy supply with safety and reliability. Thus, improper action or non-actuation of this protection system can cause materials and/or economics damages to electricity utilities as well as ordinary energy consumers. Therefore the protection system must be well adjusted so it can ensure its functions and thus being sensible, selective, reliable and fast. In order to achieve these characteristics, the protective relays must be well coordinated. In the case of meshed transmission systems, the protection is generally performed by distance relays as primary protection associated with directional overcurrent relays as backup protection. The process of adjusting these relays is very tough, slow and it can even be subject to the protection engineer mistakes. In this context, this work aims to develop a particle swarm optimization based methodology that can automatically obtain these relays adjusts so they can ensure relays coordination and selectivity, and then make this setting process faster and more precise. Thus, this methodology may provide a very favorable tool to aid the protection engineer. Moreover, as in any optimization problem, the objective function and the constraints were defined to represent the coordination problem involving both distance and directional overcurrent relays. The methodology was applied to two systems, a fictitious with 16 relays and a real transmission system with 44 relays, and in both cases it showed satisfactory results providing well-coordinated settings.

Le travail présenté dans ce mémoire porte sur l'étude, l'optimisation et la réalisation d'une transmission planétaire magnétique. Dans notre thèse nous essayons de répondre à quelques questions intéressantes sur la possibilité de remplacer un train planétaire mécanique par un train planétaire magnétique, est-ce que la formule de Willis reste valable pour le train planétaire magnétique et est-ce que les trains magnétiques ont des performances similaires à celles des trains mécaniques ? Donc nous étudions, le remplacement du train mécanique par une transmission magnétique. Nous montrons que le train magnétique a un volume moindre, des pertes inférieures et plusieurs autres avantages. Notre but dans cette thèse est d'obtenir un "design" optimal d'un train magnétique. Nous utilisons un logiciel de calcul par éléments finis pour l'étude électromagnétique et nous cherchons également à optimiser les dimensions de ce train. Pour cela nous utilisons la méthode d'optimisation par essaim de particules (OEP). Un prototype a été réalisé ce qui permet de confronter les résultats de simulation et expérimentaux. / The work presented in this thesis deals with the study, the optimisation and the realisation of a magnetic planetary transmission. We try to answer some questions about the possibility of replacing the mechanical planetary gear used in industrial machines by a magnetic planetary gear; is the formula of Willis still valid for the magnetic planetary gear and are the magnetic planetary gear performances at least similar to ones of the mechanical gears? We study the replacement of the mechanical planetary gear by a magnetic one. We show that the magnetic one has a smaller volume, lower losses and many other benefits. The objective of this work is to obtain an optimum design of a magnetic planetary gear. We use a finite element software to study the magnetic behaviour of the device and we also perform the optimization of the dimensions of the magnetic planetary gear. The particle swarm optimization method (PSO) has been used. A prototype has been built so the computation results has been compared to the experimental ones.

Made available in DSpace on 2014-06-12T17:36:41Z (GMT). No. of bitstreams: 2 arquivo9409_1.pdf: 2593707 bytes, checksum: c82123beb5138e539b7e5a7a30279094 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2012 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Nesta Tese são propostas diversas estratégias para projetar redes ópticas WDM de forma otimizada. As redes são consideradas com tráfego dinâmico e penalizadas pelas penalidades da camada física. As estratégias propostas lidam com os principais elementos que afetam a relação custo desempenho em uma rede óptica: o algoritmo de roteamento e atribuição de comprimentos de onda (RWA), a colocação de regeneradores (RP), a atribuição de regeneradores (RA), o projeto da topologia física da rede (PTD) e o dimensionamento dos dispositivos ópticos (DDO) que serão instalados na rede. Esses problemas são tratados tanto de forma separada quanto de forma integrada na Tese. Para o RWA, é proposta uma metodologia para se projetar algoritmos heurísticos de roteamento que têm como objetivo o aumento no desempenho da rede e que levam em conta as penalidades da camada física. Para a solução do RP são propostos algoritmos heurísticos e metaheurísticos para o projeto de redes ópticas translúcidas, considerando simultaneamente a otimização dos custos de capital (CapEx) e operacional (OpEx) e do desempenho da rede. O problema de PTD é tratado em conjunto com o DDO também de forma mutiobjetiva, considerando a otimização simultânea do CapEx e do desempenho (probabilidade de bloqueio). Um algoritmo multiobjetivo para realização da expansão de topologia (i.e. adição de novos enlaces a uma rede já existente) também é proposto. Além disso, são resolvidos conjuntamente os problemas de PTD, RP e RWA de forma mutiobjetiva considerando a otimização simultânea de CapEx e desempenho da rede. As otimizações das soluções são feitas utilizando as seguintes estratégias metaheuristicas propostas na área de inteligência computacional: Particle Swarm Optimization (PSO) e Non-dominated Sorting Genetic Algorithm II (NSGA-II)

A proteção de sistemas de energia elétrica possui papel extremamente importante no aspecto de garantir o fornecimento de energia de maneira segura e confiável. Assim, a ação indevida ou a não atuação deste sistema de proteção pode causar danos materiais ou econômicos tanto para as concessionárias quanto para os consumidores de energia elétrica. Dessa forma, o sistema de proteção deve estar bem ajustado para que possa garantir suas funções, sendo sensível, seletivo, confiável e rápido. Para tanto, uma boa coordenação entre os relés de proteção deve ser estabelecida. No caso de um sistema de transmissão, o qual costuma ser um sistema malhado, a proteção é comumente realizada por relés de distância aliados a relés de sobrecorrente com unidade direcional, sendo que estes funcionam como elemento de retaguarda daqueles. O processo de ajuste desses relés é um trabalho muito difícil e demorado, que pode ainda estar sujeito a erros do engenheiro de proteção responsável pelo estudo. Neste contexto, este trabalho tem como objetivo desenvolver uma metodologia baseada na otimização por enxame de partículas que obtenha automaticamente os ajustes desses relés de forma a garantir a coordenação e seletividade entre eles, tornando assim o processo de ajuste mais rápido e preciso. Dessa forma, essa metodologia pode constituir uma ferramenta de auxílio muito favorável ao engenheiro de proteção. Além disso, como em todo problema de otimização, a função objetivo e as restrições foram definidas de maneira a retratar o problema de coordenação envolvendo tanto os relés de distância quanto os direcionais de sobrecorrente. A metodologia foi aplicada a dois sistemas, um fictício com 16 relés e um sistema de transmissão real com 44 relés, sendo que em ambos os casos ela apresentou resultados bastante satisfatórios proporcionando ajustes bem coordenados. / Electrical power systems protection has a very important role in the aspect of ensuring energy supply with safety and reliability. Thus, improper action or non-actuation of this protection system can cause materials and/or economics damages to electricity utilities as well as ordinary energy consumers. Therefore the protection system must be well adjusted so it can ensure its functions and thus being sensible, selective, reliable and fast. In order to achieve these characteristics, the protective relays must be well coordinated. In the case of meshed transmission systems, the protection is generally performed by distance relays as primary protection associated with directional overcurrent relays as backup protection. The process of adjusting these relays is very tough, slow and it can even be subject to the protection engineer mistakes. In this context, this work aims to develop a particle swarm optimization based methodology that can automatically obtain these relays adjusts so they can ensure relays coordination and selectivity, and then make this setting process faster and more precise. Thus, this methodology may provide a very favorable tool to aid the protection engineer. Moreover, as in any optimization problem, the objective function and the constraints were defined to represent the coordination problem involving both distance and directional overcurrent relays. The methodology was applied to two systems, a fictitious with 16 relays and a real transmission system with 44 relays, and in both cases it showed satisfactory results providing well-coordinated settings.

Artificial intelligence tools, which are fast, robust and adaptive can overcome the drawbacks of traditional solutions for several power systems problems. In this work, applications of AI techniques have been studied for solving two important problems in power systems. The first problem is static security evaluation (SSE). The objective of SSE is to identify the contingencies in planning and operations of power systems. Numerical conventional solutions are time-consuming, computationally expensive, and are not suitable for online applications. SSE may be considered as a binary-classification, multi-classification or regression problem. In this work, multi-support vector machine is combined with several evolutionary computation algorithms, including particle swarm optimization (PSO), differential evolution, Ant colony optimization for the continuous domain, and harmony search techniques to solve the SSE. Moreover, support vector regression is combined with modified PSO with a proposed modification on the inertia weight in order to solve the SSE. Also, the correct accuracy of classification, the speed of training, and the final cost of using power equipment heavily depend on the selected input features. In this dissertation, multi-object PSO has been used to solve this problem. Furthermore, a multi-classifier voting scheme is proposed to get the final test output. The classifiers participating in the voting scheme include multi-SVM with different types of kernels and random forests with an adaptive number of trees. In short, the development and performance of different machine learning tools combined with evolutionary computation techniques have been studied to solve the online SSE. The performance of the proposed techniques is tested on several benchmark systems, namely the IEEE 9-bus, 14-bus, 39-bus, 57-bus, 118-bus, and 300-bus power systems. The second problem is the non-convex, nonlinear, and non-differentiable economic dispatch (ED) problem. The purpose of solving the ED is to improve the cost-effectiveness of power generation. To solve ED with multi-fuel options, prohibited operating zones, valve point effect, and transmission line losses, genetic algorithm (GA) variant-based methods, such as breeder GA, fast navigating GA, twin removal GA, kite GA, and United GA are used. The IEEE systems with 6-units, 10-units, and 15-units are used to study the efficiency of the algorithms.

Dans cette thèse, nous nous intéressons à la gestion des flux de marchandises en zone urbaine aussi appelée logistique du dernier kilomètre, et associée à divers enjeux d’actualité : économique, environnemental, et sociétal. Quatre principaux acteurs sont concernés par ces enjeux : chargeurs, clients, transporteurs et collectivités, ayant chacun des priorités différentes (amélioration de la qualité de service, minimisation de la distance parcourue, réduction des émissions de gaz à effet de serre, …). Face à ces défis dans la ville, un levier d’action possible consiste à optimiser les tournées effectuées pour la livraison et/ou la collecte des marchandises. Trois types de flux urbains sont considérés : en provenance ou à destination de la ville, et intra-urbains. Pour les flux sortants et entrants dans la ville, les marchandises sont d’abord regroupées dans un entrepôt situé en périphérie urbaine. S’il existe plusieurs entrepôts, le problème de planification associé est de type Location Routing Problem (LRP). Nous en étudions une de ses variantes appelée Capacitated Location Routing Problem (CLRP). Dans cette dernière, en respectant la contrainte de capacité imposée sur les véhicules et les dépôts, la localisation des dépôts et la planification des tournées sont considérées en même temps. L’objectif est de minimiser le coût total qui est constitué du coût d’ouverture des dépôts, du coût d’utilisation des véhicules, et du coût de la distance parcourue. Pour tous les flux, nous cherchons également à résoudre un problème de tournées de type Pickup and Delivery Problem (PDP), dans lequel une flotte de véhicules effectue simultanément des opérations de collecte et de livraison. Nous nous sommes focalisés sur deux de ses variantes : la variante sélective où toutes les demandes ne sont pas toujours satisfaites, dans un contexte de demandes appairées et de sites contraints par des horaires d’ouverture et fermeture (Selective Pickup and Delivery Problem with Time Windows and Paired Demands, ou SPDPTWPD). La seconde variante étudiée est l’extension de la première en ajoutant la possibilité d’effectuer les transports en plusieurs étapes par l’introduction d’opérations d’échanges des marchandises entre véhicules en des sites de transfert (Selective Pickup and Delivery with Transfers ou SPDPT). Les objectifs considérés pour ces deux variantes de PDP sont de maximiser le profit et de minimiser la distance. Chaque problème étudié fait l’objet d’une description formelle, d’une modélisation mathématique sous forme de programme linéaire, puis d’une résolution par des méthodes exactes, heuristiques et/ou métaheuristiques. En particulier nous avons développé des algorithmes basés sur une métaheuristique appelée Particle Swarm Optimization, que nous avons hybridée avec de la recherche locale. Les approches sont validées sur des instances de différentes tailles issues de la littérature et/ou que nous avons générées. Les résultats sont analysés de façon critique pour mettre en évidence les avantages et inconvénients de chaque méthode. / In this thesis, we are interested in the management of goods flows in urban areas, also called last mile logistics, and associated with various current issues: economic, environmental, and societal. Four main stakeholders are involved by these challenges: shippers, customers, carriers and local authorities, each with different priorities (improving service quality, minimizing the travelling distance, reducing greenhouse gas emissions, etc.). Faced with these challenges in the city, one possible action lever is to optimize the routes for the pickup and/or delivery of goods. Three types of urban flows are considered: from or to the city, and intra-urban. For outgoing and incoming flows into the city, the goods are first grouped in a warehouse located on the suburban area of the city. If there are several warehouses, the associated planning problem is the Location Routing Problem (LRP). We are studying one of its variants called the Capacitated Location Routing Problem (CLRP). In this problem, by respecting the capacity constraint on vehicles and depots, the location of depots and route planning are considered at the same time. The objective is to minimize the total cost, which consists of the cost of opening depots, the cost of using vehicles, and the cost of the travelling distance. For all flows, we are also looking to solve a Pickup and Delivery Problem (PDP), in which a fleet of vehicles simultaneously carries out pickup and delivery operations. We focus on two of its variants: the selective variant where not all requests are satisfied, in a context of paired demands and time windows on sites (Selective Pickup and Delivery Problem with Time Windows and Paired Demands, or SPDPTWPD). The second studied variant is the extension of the first one by adding the possibility of carrying out transport in several stages by introducing operations for the exchange of goods between vehicles at transfer sites (Selective Pickup and Delivery with Transfers or SPDPT). The considered objectives for these two variants of PDP are to maximize profit and to minimize distance. Each studied problem is formally described, mathematically modelled as a linear program and then solved by exact, heuristic and/or metaheuristic methods. In particular, we have developed algorithms based on a metaheuristic called Particle Swarm Optimization, which we have hybridized with local search operators. The approaches are validated on instances of different sizes from the literature and/or on instances that we have generated. The results are critically analyzed to highlight the advantages and drawbacks of each method.

La conception de systèmes complexes, et plus particulièrement de micro-systèmes complexes embarqués, posent des problèmes tels que l'intégration des composants, la consommation d'énergie, la fiabilité, les délais de mise sur marché, ...La conception mécatronique apparait comme étant particulièrement adaptée à ces systèmes car elle intègre intimement simulations, expérimentations, interactions entre sous-systèmes et cycles de reconception à tous les niveaux. Le produit obtenu est plus optimisé, plus performant et les délais de mise sur le marché sont réduits.Cette thèse a permis de trouver des méthodes de caractérisation, d'identification de paramètres ainsi que d'optimisation de systèmes mécatroniques actifs par la constitution de modèles numériques, de bancs d'expériences numériques, physiques et hybrides. Le cadre est bien précis : c'est celui d'un actionneur piézoélectrique amplifié, de sa commande ainsi que de la constitution générale de la boucle fermée d'un système mécatronique l'intégrant, les conclusions étant généralisables.Au cours de cette thèse, ont été introduits, avec succès, différents concepts :– Le « Signal Libre ». Un nouveau signal de commande des actionneurs piézoélectriques, basé sur les splines, maximise la vitesse de déplacement de l'actionneur et minimise sa consommation énergétique.– Deux améliorations de l'algorithme d'optimisation par essais de particules. La première introduit un arrêt de l'algorithme par la mesure du rayon de l'essaim ; le rayon limite est défini par la limite de mesurabilité des paramètres à optimiser ("Radius") ; la seconde ajoute la possibilité pour l'essaim de se transférer à une meilleure position tout en gardant sa géométrie. Ceci permet d' accélérer la convergence ("BSG-Starcraft")– L'optimisation expérimentale. Le modèle numérique étant très incertain, il est remplacé directement par le système réel dans le processus d'optimisation. Les résultats sont de qualité supérieure à ceux obtenus à partir de la simulation numérique. / The design of complex systems, especially of embedded complex micro systems, causes problems such as component integration, power consumption, reliability, time-to-market ....Mechatronics design appears to be particularly suitable for these systems because it integrates closely simulations, experiments, interactions between subsystems and redesign cycles at all levels. The resulting product is more optimized, more efficient and time-to-market is reduced.This thesis led to methods of characterization and parameter identification but also to methods for optimizing active mechatronic systems through numerical model building and different bench types, i.e. digital, physical, and hybrid. The framework is specifically that of an amplified piezoelectric actuator, its control as well as the general constitution of the closed loop of the related mechatronic system. The conclusions are generalizable.In this thesis, different concepts have been successfully introduced: - The "Free Signal". A new control signal of the piezoelectric actuator, based on splines, maximizes the speed of the actuator movement and minimizes the energy consumption. - Two improvements of the particle swarm optimization algorithm. The first one introduces a stopping criteria by measuring the swarm radius; the limit radius is defined by the measurability limit of the parameters to be optimized (“Radius”). The second one adds a swarm ability: it can jump to a better location keeping its geometry. This allows a faster convergence rate (“BSG-Starcraft”). - The experimental optimization. The numerical model being very uncertain, it is directly replaced by the real system in the optimization process. This leads to better results than those obtained using numerical simulation.

Les matériaux composites à matrice de carbure de silicium renforcée par des fibres decarbone (C/SiC) sont des composites à matrice céramique (CMC), très prometteurs pour desapplications à haute température, comme le secteur aéronautique. Dans cette thèse, sontmenées des études particulières concernant les propriétés de ces matériaux : prédiction despropriétés mécanique (élastiques), analyses thermiques (optimisation des contraintesthermiques), simulation de l’oxydation à haute température.Une méthode basée sur l’énergie de déformation est proposée pour la prédiction desconstantes élastiques et des coefficients de dilatation thermiques de matériaux compositesorthotropes 3D. Dans cette méthode, les constantes élastiques et les coefficients de dilatationthermique sont obtenus en analysant la relation entre l'énergie de déformation de lamicrostructure et celle du modèle homogénéisé équivalent sous certaines conditions auxlimites thermiques et élastiques. Différents types de matériaux composites sont testés pourvalider le modèle.Différentes configurations géométriques du volume élémentaire représentatif des compositesC/SiC (2D tissés et 3D tressés) sont analysées en détail. Pour ce faire, la méthode énergétiquea été couplée à une analyse éléments finis. Des modèles EF des composites C/SiC ont étédéveloppés et liés à cette méthode énergétique pour évaluer les constantes élastiques et lescoefficients de dilatation thermique. Pour valider la modélisation proposée, les résultatsnumériques sont ensuite comparés à des résultats expérimentaux.Pour poursuivre cette analyse, une nouvelle stratégie d'analyse « globale/locale »(multi-échelle) est développée pour la détermination détaillée des contraintes dans lesstructures composites 2D tissés C/SiC. Sur la base de l'analyse par éléments finis, laprocédure effectue un passage de la structure composite homogénéisée (Echelle macro :modèle global) au modèle détaillé de la fibre (Echelle micro : modèle local). Ce passage entreles deux échelles est réalisé à partir des résultats de l'analyse globale et des conditions auxlimites du modèle local. Les contraintes obtenues via cette approche sont ensuite comparées àcelles obtenues à l’aide d’une analyse EF classique.IVLa prise des contraintes résiduelles thermiques (contraintes d’origine thermique dans lesfibres et la matrice) joue un rôle majeur dans le comportement des composites à matricescéramiques. Leurs valeurs influencent fortement la contrainte de microfissuration de lamatrice. Dans cette thèse, on cherche donc à minimiser cette contrainte résiduelle thermique(TRS) par une méthode d’optimisation de type métaheuristique: Particle Swarm Optimization(PSO), Optimisation par essaims particulaires.Des modèles éléments finis du volume élémentaire représentatif de composites 1-Dunidirectionnels C/SiC avec des interfaces multi-couches sont générés et une analyse paréléments finis est réalisée afin de déterminer les contraintes résiduelles thermiques. Unschéma d'optimisation couple l'algorithme PSO avec la MEF pour réduire les contraintesrésiduelles thermiques dans les composites C/SiC en optimisant les épaisseurs des interfacesmulti-couches.Un modèle numérique est développé pour étudier le processus d'oxydation de microstructureet la dégradation des propriétés élastiques de composites 2-D tissés C/SiC oxydant àtempérature intermédiaire (T<900°C). La microstructure du volume élémentaire représentatifde composite oxydé est modélisée sur la base de la cinétique d'oxydation. La méthode del'énergie de déformation est ensuite appliquée au modèle éléments finis de la microstructureoxydé pour prédire les propriétés élastiques des composites. Les paramètres d'environnement,à savoir, la température et la pression, sont étudiées pour voir leurs influences sur lecomportement d'oxydation de composites C/SiC. / Carbon fiber-reinforced silicon carbide matrix (C/SiC) composite is a ceramic matrixcomposite (CMC) that has considerable promise for use in high-temperature structuralapplications. In this thesis, systematic numerical studies including the prediction of elasticand thermal properties, analysis and optimization of stresses and simulation ofhigh-temperature oxidations are presented for the investigation of C/SiC composites.A strain energy method is firstly proposed for the prediction of the effective elastic constantsand coefficients of thermal expansion (CTEs) of 3D orthotropic composite materials. Thismethod derives the effective elastic tensors and CTEs by analyzing the relationship betweenthe strain energy of the microstructure and that of the homogenized equivalent model underspecific thermo-elastic boundary conditions. Different kinds of composites are tested tovalidate the model.Geometrical configurations of the representative volume cell (RVC) of 2-D woven and 3-Dbraided C/SiC composites are analyzed in details. The finite element models of 2-D wovenand 3-D braided C/SiC composites are then established and combined with the stain energymethod to evaluate the effective elastic constants and CTEs of these composites. Numericalresults obtained by the proposed model are then compared with the results measuredexperimentally.A global/local analysis strategy is developed for the determination of the detailed stresses inthe 2-D woven C/SiC composite structures. On the basis of the finite element analysis, theprocedure is carried out sequentially from the homogenized composite structure of themacro-scale (global model) to the parameterized detailed fiber tow model of the micro-scale(local model). The bridge between two scales is realized by mapping the global analysisresult as the boundary conditions of the local tow model. The stress results by global/localmethod are finally compared to those by conventional finite element analyses.Optimal design for minimizing thermal residual stress (TRS) in 1-D unidirectional C/SiCcomposites is studied. The finite element models of RVC of 1-D unidirectional C/SiCIIcomposites with multi-layer interfaces are generated and finite element analysis is realized todetermine the TRS distributions. An optimization scheme which combines a modifiedParticle Swarm Optimization (PSO) algorithm and the finite element analysis is used toreduce the TRS in the C/SiC composites by controlling the multi-layer interfaces thicknesses.A numerical model is finally developed to study the microstructure oxidation process and thedegradation of elastic properties of 2-D woven C/SiC composites exposed to air oxidizingenvironments at intermediate temperature (T<900°C). The oxidized RVC microstructure ismodeled based on the oxidation kinetics analysis. The strain energy method is then combinedwith the finite element model of oxidized RVC to predict the elastic properties of composites.The environmental parameters, i.e., temperature and pressure are studied to show theirinfluences upon the oxidation behavior of C/SiC composites.

Maximum asset performance is one of the major goals for electric power distribution system operators (DSOs). To reach this goal minimal life cycle cost and maintenance optimization become crucial while meeting demands from customers and regulators. One of the fundamental objectives is therefore to relate maintenance and reliability in an efficient and effective way. Furthermore, this necessitates the determination of the optimal balance between pre¬ventive and corrective maintenance, which is the main problem addressed in the thesis. The balance between preventive and corrective maintenance is approached as a multiobjective optimization problem, with the customer interruption costs on one hand and the maintenance budget of the DSO on the other. Solutions are obtained with meta-heuristics, developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The methods deliver a Pareto border, a set of several solutions, which the operator can choose between, depending on preferences. The optimization is built on component reliability importance indices, developed specifically for power systems. One vital aspect of the indices is that they work with several supply and load points simultaneously, addressing the multistate-reliability of power systems. For the computation of the indices both analytical and simulation based techniques are used. The indices constitute the connection between component reliability performance and system performance and so enable the maintenance optimization. The developed methods have been tested and improved in two case studies, based on real systems and data, proving the methods’ usefulness and showing that they are ready to be applied to power distribution systems. It is in addition noted that the methods could, with some modifications, be applied to other types of infrastructures. However, in order to perform the optimization, a reliability model of the studied power system is required, as well as estimates on effects of maintenance actions (changes in failure rate) and their related costs. Given this, a generally decreased level of total maintenance cost and a better system reliability performance can be given to the DSO and customers respectively. This is achieved by focusing the preventive maintenance to components with a high potential for improvement from system perspective. / QC 20100810