Bone is a living material. It adapts, in an optimal sense, to loading by changing its density and trabeculae architecture - a process termed remodelling. Implanted orthopaedic devices can significantly alter the loading on the surrounding bone. In addition, these devices rely on bone ingrowth to ensure secure implant fixation. In this project, a computational model that accounts for bone remodelling is developed and used to elucidate the response of bone following a reverse shoulder procedure. The reverse shoulder procedure investigated here is for rotary cuff deficient patients. In this procedure up to 75 % complications are reported in some clinical series. It is therefore necessary, for the design of successful implants, to understand the loading environment to promote bone growth in the correct areas. The physical process of remodelling is modelled using continuum scale, open system thermodynamics whereby the density of bone evolves isotropically in response to the loading it experiences. The fully-nonlinear continuum theory is solved approximately using the finite element method. The finite element library AceGEN forms the basis for the implementation. Several benchmark problems were implemented to validate the code and demonstrate features of the theory. These include several one-dimensional problems, the classical two-dimensional femur benchmark, and a series of three-dimensional examples. The three-dimensional examples include different loading scenarios on a rectangular block, as well as the investigation of the ASTM testing procedure of the glenoid side prosthesis implanted in a polyurethane foam block. The results clearly demonstrate the adaptive behaviour of the bone density in response to the magnitude and duration of the loading. The numerical implementation is also shown to be robust. The remodelling of the scapula post reverse shoulder arthroplasty is then investigated. A statistical shape model of the scapula was obtained from collaborators in the Division of Biomedical Engineering at the University of Cape Town. The finite element model was used to determine the density distribution in the scapula prior to surgery. A virtual surgery was then performed. The resulting geometry provides the input for the pre-processing phase of the post reverse shoulder arthroplasty model. The loading conditions for the reverse shoulder were provided by collaborators in the Division of Biomedical Engineering and the Leon Root Motion Analysis Laboratory at the Hospital for Special Surgery in New York City. The maximal loading condition at 90° abduction is used as the input for the simulation. It was found that the density increases in the vicinity of the screws, where the maximum stresses are concentrated, however, bone resorption is observed directly below and adjacent to the implant. No conclusive statement can be made, however, as only one loading scenario is considered and calibration of the model against experimental results is still outstanding. A unique feature of the code is that the upper and lower bounds of the density do not have to be enforced directly, as done in most bone remodelling theories in the literature. Rather, the bounds of the density are naturally enforced by calibrating the mass flux for the problem at hand. This project lays out the groundwork for a sound remodelling code, which can serve as a predictive tool in the field of orthopaedics.

Chalcogen bonding (ChB) is a particular case of secondary bonding centred on heavy group-16 elements. It is almost exclusively identified through crystallography by measuring interatomic distances intermediate between single-bond averages and the sum of van der Waals radii. However, there is significant recent progress in discerning its signatures using spectroscopic techniques such as multinuclear NMR. This M.Sc. thesis describes progress in two research projects on chalcogen bonding. The first examined the effect of halogenation on the aggregation of 3-methyl-5-phenyl 1-2-tellurazole 2-oxide. The second examined the strengthening of ChB interaction between molecules of benzo-1,2-chalcogenazole 2-oxides by chlorination. The bromination of 3-methyl-5-phenyl 1-2-tellurazole 2-oxide yielded 3,3,3-tri-bromo-3-methyl-5-phenyl-1,2-tellurazole-2-anole. Four unique crystal structures were obtained with the most promising being the dimeric structure. Deprotonation was unsuccessfully attempted although yielded 2 unique crystal structures co-crystallized with proton-sponge. Iodination of 3-methyl-5-phenyl 1-2-tellurazole 2-oxide was also performed, resulting in a mixed tetrameric aggregate containing two molecules of 3-methyl-5-phenyl 1-2-tellurazole 2-oxide and two 1,1-di-iodo-3-methyl-5-phenyl 1-2-tellurazole 2-oxide molecules. DFT investigations into the electronic properties, thermodynamics of aggregation, and basicity were performed. Similar to the chlorinated derivative, the most favourable aggregate to form is the hetero-tetramer with two brominated or iodinated molecules and 2 non-halogenated molecules. The reaction of benzo 1,2-sellenazole 2-oxide with SO2Cl2 and benzo 1,2-tellurazole 2-oxide with HCl followed by SO2Cl2 yielded halogenated derivatives of each molecule in which the chalcogen was oxidized from Ch(II) to Ch(IV). In the selenium derivative, an unexpected chlorination occurred on the heterocycle of the molecule. Crystal structures were obtained for each chlorinated product where dimeric interactions were observed. DFT calculations show how the electronic and orbital mixing contributions to the ChB interactions are enhanced upon halogenation. Gibbs free energy of aggregation is most negative for a mixed structure in which two chlorinated molecules and two unchlorinated molecules are linked. / Thesis / Master of Science (MSc)

No description available.

Estruturas do tipo linha/curva (line-like, curve-like), alongadas e ramificadas são comumente encontradas nos ecossistemas que conhecemos. Na biomedicina e na biociências, por exemplo, diversas aplicações podem ser observadas. Justamente por este motivo, extrair este tipo de estrutura em imagens é um constante desafio em problemas de análise de imagens. Porém, diversas dificuldades estão envolvidas neste processo. Normalmente as características espectrais e espaciais destas estruturas podem ser muito complexas e variáveis. Especificamente as mais \"finas\" são muito frágeis a qualquer tipo de processamento realizado na imagem e torna-se muito fácil a perda de informações importantes. Outro problema bastante comum é a ausência de parte das estruturas, seja por motivo de pouca resolução, ou por problemas de aquisição, ou por casos de oclusão. Este trabalho tem por objetivo explorar, descrever e desenvolver técnicas de detecção/segmentação de estruturas finas e ramificadas. Diferentes métodos são utilizados de forma combinada, buscando uma melhor representação topológica e perceptual das estruturas e, assim, melhores resultados. Grafos são usados para a representação das estruturas. Esta estrutura de dados vem sendo utilizada com sucesso na literatura na resolução de diversos problemas em processamento e análise de imagens. Devido à fragilidade do tipo de estrutura explorado, além das técnicas de processamento de imagens, princípios de visão computacional são usados. Busca-se, desta forma, obter um melhor \"entendimento perceptual\" destas estruturas na imagem. Esta informação perceptual e informações contextuais das estruturas são utilizadas em um modelo de campos aleatórios de Markov, buscando o resultado final da detecção através de um processo de otimização. Finalmente, também propomos o uso combinado de diferentes modalidades de imagens simultaneamente. Um software é resultado da implementação do arcabouço desenvolvido e o mesmo é utilizado em duas aplicações para avaliar a abordagem proposta: extração de estradas em imagens de satélite e extração de raízes em imagens de perfis de solo. Resultados do uso da abordagem proposta na extração de estradas em imagens de satélite mostram um melhor desempenho em comparação com método existente na literatura. Além disso, a técnica de fusão proposta apresenta melhora significativa de acordo com os resultados apresentados. Resultados inéditos e promissores são apresentados na extração de raízes de plantas. / Line- curve-like, elongated and ramified structures are commonly found inside many known ecosystems. In biomedicine and biosciences, for instance, different applications can be observed. Therefore, the process to extract this kind of structure is a constant challenge in image analysus problems. However, various difficulties are involved in this process. Their spectral and spatial characteristics are usually very complex and variable. Considering specifically the thinner ones, they are very \"fragile\" to any kind of process applied to the image, and then, it becomes easy the loss of crucial data. Another very common problem is the absence of part of the structures, either because of low image resolution and image acquisition problems or because of occlusion problems. This work aims to explore, describe and develop techniques for detection/segmentation of thin and ramified structures. Different methods are used in a combined way, aiming to reach a better topological and perceptual representation of the structures and, therefore, better results. Graphs are used to represent the structures. This data structure has been successfully used in the literature for the development of solutions for many image processing and analysis problems. Because of the fragility of the kind of structures we are dealing with, some computer vision principles are used besides usual image processing techniques. In doing so, we search for a better \"perceptual understanding\" of these structures in the image. This perceptual information along with contextual information about the structures are used in a Markov random field, searching for a final detection through an optimization process. Lastly, we propose the combined use of different image modalities simultaneously. A software is produced from the implementation of the developed framework and it is used in two application in order to evaluate the proposed approach: extraction of road networks from satellite images and extraction of plant roots from soil profile images. Results using the proposed approach for the extraction of road networks show a better performance if compared with an existent method from the literature. Besides that, the proposed fusion technique presents a meaningful improvement according to the presented results. Original and promising results are presented for the extraction of plant roots from soil profile images.

Estruturas do tipo linha/curva (line-like, curve-like), alongadas e ramificadas são comumente encontradas nos ecossistemas que conhecemos. Na biomedicina e na biociências, por exemplo, diversas aplicações podem ser observadas. Justamente por este motivo, extrair este tipo de estrutura em imagens é um constante desafio em problemas de análise de imagens. Porém, diversas dificuldades estão envolvidas neste processo. Normalmente as características espectrais e espaciais destas estruturas podem ser muito complexas e variáveis. Especificamente as mais \"finas\" são muito frágeis a qualquer tipo de processamento realizado na imagem e torna-se muito fácil a perda de informações importantes. Outro problema bastante comum é a ausência de parte das estruturas, seja por motivo de pouca resolução, ou por problemas de aquisição, ou por casos de oclusão. Este trabalho tem por objetivo explorar, descrever e desenvolver técnicas de detecção/segmentação de estruturas finas e ramificadas. Diferentes métodos são utilizados de forma combinada, buscando uma melhor representação topológica e perceptual das estruturas e, assim, melhores resultados. Grafos são usados para a representação das estruturas. Esta estrutura de dados vem sendo utilizada com sucesso na literatura na resolução de diversos problemas em processamento e análise de imagens. Devido à fragilidade do tipo de estrutura explorado, além das técnicas de processamento de imagens, princípios de visão computacional são usados. Busca-se, desta forma, obter um melhor \"entendimento perceptual\" destas estruturas na imagem. Esta informação perceptual e informações contextuais das estruturas são utilizadas em um modelo de campos aleatórios de Markov, buscando o resultado final da detecção através de um processo de otimização. Finalmente, também propomos o uso combinado de diferentes modalidades de imagens simultaneamente. Um software é resultado da implementação do arcabouço desenvolvido e o mesmo é utilizado em duas aplicações para avaliar a abordagem proposta: extração de estradas em imagens de satélite e extração de raízes em imagens de perfis de solo. Resultados do uso da abordagem proposta na extração de estradas em imagens de satélite mostram um melhor desempenho em comparação com método existente na literatura. Além disso, a técnica de fusão proposta apresenta melhora significativa de acordo com os resultados apresentados. Resultados inéditos e promissores são apresentados na extração de raízes de plantas. / Line- curve-like, elongated and ramified structures are commonly found inside many known ecosystems. In biomedicine and biosciences, for instance, different applications can be observed. Therefore, the process to extract this kind of structure is a constant challenge in image analysus problems. However, various difficulties are involved in this process. Their spectral and spatial characteristics are usually very complex and variable. Considering specifically the thinner ones, they are very \"fragile\" to any kind of process applied to the image, and then, it becomes easy the loss of crucial data. Another very common problem is the absence of part of the structures, either because of low image resolution and image acquisition problems or because of occlusion problems. This work aims to explore, describe and develop techniques for detection/segmentation of thin and ramified structures. Different methods are used in a combined way, aiming to reach a better topological and perceptual representation of the structures and, therefore, better results. Graphs are used to represent the structures. This data structure has been successfully used in the literature for the development of solutions for many image processing and analysis problems. Because of the fragility of the kind of structures we are dealing with, some computer vision principles are used besides usual image processing techniques. In doing so, we search for a better \"perceptual understanding\" of these structures in the image. This perceptual information along with contextual information about the structures are used in a Markov random field, searching for a final detection through an optimization process. Lastly, we propose the combined use of different image modalities simultaneously. A software is produced from the implementation of the developed framework and it is used in two application in order to evaluate the proposed approach: extraction of road networks from satellite images and extraction of plant roots from soil profile images. Results using the proposed approach for the extraction of road networks show a better performance if compared with an existent method from the literature. Besides that, the proposed fusion technique presents a meaningful improvement according to the presented results. Original and promising results are presented for the extraction of plant roots from soil profile images.

World resources are becoming more and more scarce due to the increasing demand. Hence, the industry is moving towards sustainable development in order to suffice the needs of the future generations. Electricity is one such resources that account for 90% of the daily utility. In Sweden alone 378 TWh of electricity is consumed over a year. The major source of production of electricity is the fossil fuels, but due to development in the renewable resource's the electricity is also produced using solar, wind and geothermal energy. However, no production process is 100% efficient and hence, there is loss of energy in the form of waste. Organic Rankine Cycle Turbine (ORC) is a technology which is under the focus of the researcher and the industry to convert this wasteful energy into useful energy. Designing of these machines is a challenging task which requires careful consideration of every design parameter, i.e. with the change in every parameter the losses in the turbine either increase or decrease. In this study, effect of the parameters such as inlet mach number, stagger angle, inlet angle and pitch to chord is studied to see the effect on the profile loss. Since ANSYS Fluent works with 2D unlike ANSYS CFX which work with pseudo 2D geometry, ANSYS Fluent was used for investigating profile loss. Furthermore, a methodology is defined to investigate the tip leakage loss based on the geometry provided by the Againity AB for future studies. Tip leakage loss simulations were carried out in ANSYS CFX turbo mode due to its user friendly interface for simulating turbo machinery flows. The results of the profile loss investigation suggested a range for parameters where the profile loss is observed to be comparatively lower than elsewhere. The methodology proposed for tip leakage loss investigation paved a pathway for the further improvement with respect to the future studies.