This thesis investigates the relations between (1) free stream velocity, blade radius as well as the number of blades, and (2) generated torque, power and efficiency in the design of a water turbine. In the study, blade element momentum theory (BEMT) is exploited to devise the shape of the horizontal water turbine. Further, a CFD package is in used to simulate the flow and pressure fields. The result shows that torque and power generated by turbine vary with such parameters as inlet velocity and blade radii. As the number of blade increases, the generated power is also on the rise but to a lessened degree.It is due to the fact that fluid can hardly flow into the cross section as the blade number increases, which brings about lower cross-section velocity. So the rotational speed should decline as a consequence to obtain the angle of attack satisfying the greatest lift-drag ratio. The largest power efficiency is thus gained.

Four different non-orthogonal basis sets are studied and compared in order to obtain the resonance properties of a model scattering problem. In particular, two types of Gaussian basis sets, one B-spline basis set and one hybrid Gaussian - B-spline basis set. Their ability to represent the scattering continuum is investigated along with their numerical properties. Particular attention is paid to the energy range within which each basis set gives reasonably accurate values of the phase shift and the decay width. The radial Schrödinger equation is solved by the Löwdin's symmetric orthogonalization method and the decay width is extracted by the Stieltjes imaging procedure. The R-matrix method within the framework of Feshbach-Fano projection operator formalism with polynomial basis set is utilized as a numerically exact reference method.

This thesis aims to investigate the performance of a horizontal water turbine in ocean current. The design of the water turbine is based on the Blade Element Momentum theory to begin with. As the water current flows past a single turbine, the water inflow velocity and the rotational speed are the parameters to be investigated. Furthermore, the interaction of more than two turbines due to the relative distance is also discussed. The relative distance encompasses both the front and the back. The results show that the water inflow velocity and the turbine rotational speed influence the performance of the turbine. When two turbines function simultaneously, the flow field is different from the one of a single turbine and thus influences the performance of the other turbines in the vicinity. Lastly, the site arrangement of three turbines is discussed, and it is revealed that a proper arrangement can enhance the performance of the turbines.

En vue de contrôler les émissions de gaz à effet de serre, il est envisagé d’injecter du CO2 dans des réservoirs géologiques. Or le CO2 n'est pas un gaz inerte. En modifiant la composition chimique de l'eau in situ, il est à l'origine d'interactions roche/fluide. Ces réactions géochimiques impactent les propriétés d'écoulement. Aussi, pour s'assurer de la viabilité et de la pérennité du stockage, les opérateurs ont besoin de simulations tenant compte de ces écoulements réactifs. Cependant les paramètres de l'équation macroscopique de transport utilisée sont affectés par les réactions surfaciques. Or, ces spécificités dues au transfert de masse ne sont pas prises en compte actuellement. De même, la loi perméabilité-porosité (K-F) n’est estimée que semi-empiriquement. Le but de cette thèse a été de développer une méthode pour obtenir les coefficients macroscopiques précédents et les relations K-F, en résolvant les équations gouvernant les phénomènes à l'échelle du pore. Pour ce faire, nous avons utilisé l'approche réseau de pores. L'avantage du modèle réseau est qu'il prend en compte explicitement la structure tout en conceptualisant cette dernière à un ensemble de pores et de canaux à la morphologie simplifiée (sphères, cylindres). L'étude est basée sur deux changements d'échelles successifs : du local au pore, puis du pore à la carotte. Le problème de transport réactif est résolu pour des éléments basiques, analytiquement ou numériquement. Puis, en faisant appel aux solutions précédemment trouvées, le transport réactif est traité sur l'ensemble du réseau. Notre model fut validé par des observations sur micromodèles, puis à l'aide d'une expérience d'altération acide / The geological storage of CO2 is considered as an attractive option to reduce the greenhouse gas emissions in the atmosphere. CO2 is not an inert gas, however. Its dissolution in brine forms a weak acid that has the potential to react with the host rock formation. The induced pores structure modification impacts the flow properties. Thus, to ensure the viability and sustainability of CO2 storage, operators need simulations that take into account the specificities of reactive transport. However, the macroscopic coefficients of the reactive transport equation are modified from the values of an inert tracer by surface reactions. These specificities due to mass transfer are currently not considered. Similarly, the permeability-porosity (K-F) relationship is only estimated semi-empirically. The aim of this thesis was to develop a method to obtain the macroscopic coefficients and the K-F laws, by solving the equations governing the pore-scale phenomena. To do this, we used the Pore Network Modelling approach (PNM). The advantage of the PNM is that it explicitly takes into account the pore structure, while conceptualizing the latter to a set of pores and throats whose morphology is simplified into spheres or cylinders for instance. The study is based into two successive upscalings: from local-scale to pore-scale, then from pore-scale to core-scale. The reactive transport problem is solved for basic elements, analytically or numerically. Then, using the solutions previously found at the pore scale, the reactive transport phenomena are treated throughout the network. Our model was validated by observations on micromodels and by a comparison with an acid-induced alteration experiment

Uma das tarefas básicas dos mecanismos atencionais é decidir qual a localização dentro do campo visual, em que devemos prestar atenção primeiro. Um objeto que contenha características distintas, tais como orientação, forma, cor, tamanho, brilho, textura, etc. diferentes, pode atrair a atenção de uma maneira \"bottom-up\". A informação \"top-down\" baseia-se no conhecimento prévio e tem uma grande influência nas localizações atendidas. Inspirado nos mecanismos da Atenção Visual Humana, embora sem a pretensão de simulá-la, este trabalho prevê o desenvolvimento de uma nova metodologia que integra os dois tipos de informações: \"bottom-up\" e \"top-down\". Características \"bottom-up\" são geradas a partir de Momentos e essas informações são utilizadas em mapas de saliência, enquanto que um conhecimento prévio é utilizado para gerar pistas \"top-down\". Neste trabalho, desenvolveu-se uma metodologia específica para a busca e o reconhecimento visual em cenas com múltiplos objetos, utilizando para isso uma rede \"fuzzy\" contendo três subsistemas \"fuzzy\". Dada uma imagem de entrada, o objetivo consiste em se detectar regiões que possam conter informações mais significativas, a fim de que se possa guiar e restringir processamentos mais complexos. A inclusão de mecanismos de atenção (seleção de uma região de interesse dentro da imagem) é de fundamental importância pois os resultados obtidos pelo método podem ser usados para controlar a aquisição da imagem de uma maneira dinâmica. O modelo proposto está estruturado em três estágios principais: O primeiro estágio consiste em se segmentar os objetos e extrair características globais dos mesmos baseadas principalmente na teoria dos momentos, tais como tamanho, orientação, formato e distância e também média de nível de cinza. Por intermédio da comparação de um objeto com os outros presentes na cena, características \"bottom-up\" de conspicuidade são usadas para guiar a atenção ao objeto mais diferente. Por intermédio do uso da lógica \"fuzzy\" é possível inferir com grande flexibilidade algumas regras de decisão baseadas nos princípios de percepção visual tais como as leis Gestalt. O segundo estágio consiste de um subsistema \"fuzzy top-down\" que combina diferentes características de acordo com a relevância das mesmas em diferentes tarefas. Finalmente, o terceiro estágio consiste de um subsistema \"fuzzy\" que integra as informações obtidas dos subsistemas anteriores e fornece um índice geral de saliência, e indica a provável localização do objeto a ser reconhecido. A nova abordagem foi testada com objetos geométricos levando-se em consideração as características que atraem a atenção dos serem humanos / One of the basic tasks assigned to the human attentional mechanisms is to decide which location in the visual field we must pay attention first. An object containing distinctive features (such as different orientation, shape, color, size, shine, texture, etc.) can attract attention in a bottom-up way. Top-down information is based on the previous knowledge and has a large influence on the attended locations. Inspired on human visual attention mechanisms, although it doesn\'t want simulate it, this work presents a new methodology to integrate two different kind of information: bottom-up and top-down. Bottom-up features are obtained from Moment Theory and this information is used in salience maps, while a previous knowledge is used to create top-down hints. In this work, an specific methodology to visual search and recognition was developed to be applied to scenes containing multiple objects by a fuzzy net with three fuzzy subsystems. The aim of this methodology is to detect regions that may contain the most significant information, in order to guide and to restrict most complex processing. The inclusion of attentional mechanisms (the selection of a region of interest in the image) is fundamental and can be used to control the image acquisition in a dynamic way. The proposed model is structured in three main stages. The first stage segments the objects and extracts global features of them, based on the Moment Theory such as size, orientation, shape and distance and gray level average. By comparing one object with the other ones present in the scene, bottom-up features of conspicuity are used to guide the attention to the most different object. The Fuzzy Logic allows us to infer with great flexibility some of decision rules based on the visual perception principles such as the Gestalt Laws. The second stage is a top-down fuzzy subsystem that combines different features according to the relevance of them in different tasks. Finally, the third stage is a fuzzy subsystem that integrates the information obtained from the previous sub-systems and gives us a general salience index. The new methodology was tested in geometrical objects considering the feature that attracts attention to human beings

Uma das tarefas básicas dos mecanismos atencionais é decidir qual a localização dentro do campo visual, em que devemos prestar atenção primeiro. Um objeto que contenha características distintas, tais como orientação, forma, cor, tamanho, brilho, textura, etc. diferentes, pode atrair a atenção de uma maneira \"bottom-up\". A informação \"top-down\" baseia-se no conhecimento prévio e tem uma grande influência nas localizações atendidas. Inspirado nos mecanismos da Atenção Visual Humana, embora sem a pretensão de simulá-la, este trabalho prevê o desenvolvimento de uma nova metodologia que integra os dois tipos de informações: \"bottom-up\" e \"top-down\". Características \"bottom-up\" são geradas a partir de Momentos e essas informações são utilizadas em mapas de saliência, enquanto que um conhecimento prévio é utilizado para gerar pistas \"top-down\". Neste trabalho, desenvolveu-se uma metodologia específica para a busca e o reconhecimento visual em cenas com múltiplos objetos, utilizando para isso uma rede \"fuzzy\" contendo três subsistemas \"fuzzy\". Dada uma imagem de entrada, o objetivo consiste em se detectar regiões que possam conter informações mais significativas, a fim de que se possa guiar e restringir processamentos mais complexos. A inclusão de mecanismos de atenção (seleção de uma região de interesse dentro da imagem) é de fundamental importância pois os resultados obtidos pelo método podem ser usados para controlar a aquisição da imagem de uma maneira dinâmica. O modelo proposto está estruturado em três estágios principais: O primeiro estágio consiste em se segmentar os objetos e extrair características globais dos mesmos baseadas principalmente na teoria dos momentos, tais como tamanho, orientação, formato e distância e também média de nível de cinza. Por intermédio da comparação de um objeto com os outros presentes na cena, características \"bottom-up\" de conspicuidade são usadas para guiar a atenção ao objeto mais diferente. Por intermédio do uso da lógica \"fuzzy\" é possível inferir com grande flexibilidade algumas regras de decisão baseadas nos princípios de percepção visual tais como as leis Gestalt. O segundo estágio consiste de um subsistema \"fuzzy top-down\" que combina diferentes características de acordo com a relevância das mesmas em diferentes tarefas. Finalmente, o terceiro estágio consiste de um subsistema \"fuzzy\" que integra as informações obtidas dos subsistemas anteriores e fornece um índice geral de saliência, e indica a provável localização do objeto a ser reconhecido. A nova abordagem foi testada com objetos geométricos levando-se em consideração as características que atraem a atenção dos serem humanos / One of the basic tasks assigned to the human attentional mechanisms is to decide which location in the visual field we must pay attention first. An object containing distinctive features (such as different orientation, shape, color, size, shine, texture, etc.) can attract attention in a bottom-up way. Top-down information is based on the previous knowledge and has a large influence on the attended locations. Inspired on human visual attention mechanisms, although it doesn\'t want simulate it, this work presents a new methodology to integrate two different kind of information: bottom-up and top-down. Bottom-up features are obtained from Moment Theory and this information is used in salience maps, while a previous knowledge is used to create top-down hints. In this work, an specific methodology to visual search and recognition was developed to be applied to scenes containing multiple objects by a fuzzy net with three fuzzy subsystems. The aim of this methodology is to detect regions that may contain the most significant information, in order to guide and to restrict most complex processing. The inclusion of attentional mechanisms (the selection of a region of interest in the image) is fundamental and can be used to control the image acquisition in a dynamic way. The proposed model is structured in three main stages. The first stage segments the objects and extracts global features of them, based on the Moment Theory such as size, orientation, shape and distance and gray level average. By comparing one object with the other ones present in the scene, bottom-up features of conspicuity are used to guide the attention to the most different object. The Fuzzy Logic allows us to infer with great flexibility some of decision rules based on the visual perception principles such as the Gestalt Laws. The second stage is a top-down fuzzy subsystem that combines different features according to the relevance of them in different tasks. Finally, the third stage is a fuzzy subsystem that integrates the information obtained from the previous sub-systems and gives us a general salience index. The new methodology was tested in geometrical objects considering the feature that attracts attention to human beings