Na presente tese é resolvida a equação de difusão de nêutrons estacionária, bem como problemas de cinética, em geometria unidimensional cartesiana multi-região considerando o modelo de multigrupos de energia. Um dos objetivos e inovação neste trabalho é a obtenção de uma solução aproximada com estimativa de erro, controle de precisão e na forma de uma expressão analítica. Com esse tipo de solução não há a necessidade de recorrer a esquemas de interpolação, geralmente necessários em caso de discretizações do domínio. O fluxo de nêutrons é expandido em uma série de Taylor cujos coeficientes são encontrados utilizando a equação diferencial e as condições de contorno e interface. O domínio é dividido em várias células, cujo tamanho e o grau do polinômio são ajustáveis de acordo com a precisão requerida. Para resolver o problema de autovalor é utilizado o método da potência. A metodologia é aplicada em um benchmark que consiste na solução da equação de difusão como condição inicial e na solução de problemas de cinética para diferentes transientes. Os resultados são comparados com sucesso com resultados da literatura. A convergência da série é garantida pela aplicação de um raciocínio baseado no critério de Lipschitz para funções contínuas. Cabe ressaltar que a solução obtida, em conjunto com a análise da convergência, mostra a solidez e a precisão dessa metodologia. / In the present dissertation the one-dimensional neutron diffusion equation for stationary and kinetic problems in a multi-layer slab has been solved considering the multi-group energy model. One of the objectives and innovation in this work is to obtain an approximate solution with error estimation, accuracy control and in the form of an analytical expression. With this solution there is no need for interpolation schemes, which are usually needed in case of discretization of the domain. The neutron flux is expanded in a Taylor series whose coefficients are found using the differential equation and the boundary and interface conditions. The domain is divided into several layers, whose size and the polynomial order can be adjusted according to the required accuracy. To solve the eigenvalue problem the conventional power method has been used. The methodology is applied in a benchmark problem consisting of the solution of the diffusion equation as an initial condition and solving kinetic problems for different transients. The results are compared successfully with the ones in the literature. The convergence of the series is guaranteed by applying a criterion based on the Lipschitz criterion for continuous functions. Note that the solution obtained, together with the convergence analysis, shows the robustness and accuracy of this methodology.

Orientador: Renato Pavanello / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-28T11:58:24Z (GMT). No. of bitstreams: 1 Calixto_TainanKhalilLeite_M.pdf: 15775150 bytes, checksum: e5e4d45becc32f922a1fd31b8f9bd3ab (MD5) Previous issue date: 2015 / Resumo: A utilização de materiais de alta performance se tornou uma realidade em diversos campos da engenharia, como na indústria automotiva e aeroespacial, devido aos avanços nas técnicas de manufatura aditiva. Por outro lado, sabe-se que a otimização topológica estrutural é uma ferramenta de desenvolvimento de estruturas com ampla aplicação industrial. Dentre os vários métodos de otimização topológica existentes, a otimização estrutural evolucionária tem se destacado pela sua versatilidade, podendo ser utilizada em diversos tipos de problemas de engenharia. Na tentativa de combinar esses campos, este trabalho consiste no estudo do método de otimização evolucionária BESO (Bi-directional Evolutionary Structural Optimization) aplicado a sistemas bidimensionais multiescala a fim de se projetar as topologias ótimas, em ambas as escalas, de uma estrutura. A análise do modelo multiescala é feita através do método da homogeneização, onde o padrão do material microestrutural é considerado periódico. O algoritmo implementado pode buscar dois objetivos distintos: a minimização da flexibilidade média, que resulta na maximização da rigidez global; ou a maximização da frequência fundamental. Resultados numéricos do algoritmo são apresentados para o projeto de materiais, onde apenas a microestrutura é otimizada, e de estruturas, na qual otimiza-se as topologias nas duas escalas. Para a análise do desempenho do método de otimização multiescala, são propostos um índice de eficiência estrutural e uma metodologia de fabricação de estruturas periódicas / Abstract: High-performance materials utilization became a reality in many fields of actual engineering, such as in automotive and aerospace industries, due to advances in additive manufacturing techniques. In the other hand, structural topology optimization is a powerful tool for the structure development with wide industrial application. Among the various optimization methods, evolutionary structural optimization stands out for its versatility and it can be used in many engineering problems. As an attempt to combine these fields, this work intends to study the Bi-directional evolutionary Structural Optimization method applied to two-dimensional multi-scale systems in order to design the optimal topologies of structures in both scales. The analysis of multi-scale model is made using the homogenization method, where the pattern of the micro-structural material is considered periodic. The implemented algorithm can use two different objective function: mean compliance minimization, which results in maximizing the global stiffness; or fundamental frequency maximization. Numerical results are presented for material design, where only the micro structure is optimized, and for structural design, in which the topologies in both scales are optimized. Deepening the study in multiscale optimization, it is proposed an index to analyse the structural efficiency and also a manufacturing methodology of periodic structures / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23153号 / 工博第4797号 / 新制||工||1750(附属図書館) / 京都大学大学院工学研究科建築学専攻 / (主査)教授 大崎 純, 教授 竹脇 出, 准教授 倉田 真宏 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Les travaux présentés dans ce mémoire proposent une nouvelle méthode d'optimisation globale dénommée MPSO-SA. Cette méthode hybride est le résultat d'un couplage d'une variante d'algorithme par Essaim de particules nommé MPSO (Particle Swarm Optimization) avec la méthode du recuit simulé nommé SA (Simulted Annealing). Les méthodes stochastiques ont connu une progression considérable pour la résolution de problèmes d'optimisation. Parmi ces méthodes, il y a la méthode Essaim de particules (PSO° qui est développée par [Eberhart et Kennedy (1995)]. Quant à la méthode recuit simulé (SA), elle provient du processus physique qui consiste à ordonner les atomes d'un cristal afin de former une structure cristalline parfaite. Pour illustrer les performances de la méthode MPSO-SA proposée, une comparaison avec MPSO et SA est effectuée sur des fonctions tests connues dans la littérature. La métode MPSO-SA est utilisée pour la résolution des problèmes réels interopérabilité des systèmes d'information, ainsi qu'aux problèmes d'optimisation et de fiabilité des structures mécaniques. / The work presented in this PhD thesis contibutes to a new method for a modified particle swarm optimization algorith (MPSO) combined with a simulating annealing algorithm (SA). MPSO is known as an efficient approach with a high performance of solving optimization problems in many research fields. It is a population intelligence algorithm [Eberhart et Kennedy (1995)] inspired by social behavior simulations of bird flocking. Considerable research work on classical method PSO (Particle Swarm Optimization) has been done to improve the performance of this method. Therefore, the propose hybrid optimization algorithms MPSOSA use the combination of MPSO and simulating annealing SA. This method has the avantage to provide best results comparing with all heuristics methods PSO and SA. In this matter, a benchmark of eighteen well-known functions is given. These functions present different situations of finding the global minimum with gradual difficulties. Numerical results presented, in this paper, show the robustness of the MPSOSA algorithm. Numerical comparisons with three algorithms namely, Simulating Annealing, Modified Particle swarm optimization and MPSO-SA show that hybrid algorithm offers better results. This method (MPSO-SA) treats a wide range of optimization problems, in information systems interoperability and in structural optimization field.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18585号 / 工博第3946号 / 新制||工||1606(附属図書館) / 31485 / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 西脇 眞二, 教授 田畑 修, 教授 松原 厚 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The intention of this thesis is to develop, evaluate new concepts and look over the current design for a container sized barge module. By request of Group Ocean, a cost and weight reduction is the main improvement criteria along with keeping the strength of the module.Five concepts are developed, analyzed and discussed with the supervisor at Group Ocean, where three are decided to be presented here. The other two are left out, since they are considered way too expensive without giving a satisfying result. The three concepts that are developed throughout this thesis are; changing to high strength steel, changing to sandwich panels and increasing stiffeners with smaller dimensions.A structural optimization is made in the software MATLAB to find out the best dimension to use for the sandwich panels. To determine the local stresses, the finite element method is used in Inventor Professional. It is also where the design and CAD modules are built in, so for simplifications it is used for FEA (Finite Element Analysis) as well. To reduce the amount of elements and nodes, shell elements and other structural constraints are used in the FEA. All the concepts are modelled with the same structural constraints so a practical comparison study can be made.The final designs resulted in a total weight reduction up to 40% with a material cost reduction of 12%. Based on what type of material is chosen, the material cost reduction range is between 3-12% and the weight reduction range is between 13-40%.

Civil engineering projects involve great investments and great impacts. For that reason,engineers have a commitment with an efficient and optimal use of resources. Researchers inuniversities claim that a lot could be achieved by applying structural optimization into realprojects, even though this approach has not gained the same popularity in the industry over thelast decades.The purpose of the present thesis is to explore the possibilities offered by structural optimizationand to verify its applicability in realistic and complex structural engineering problems. Amongthe questions regarding design optimization, it was emphasized feasibility, efficiency and userfriendliness. The chosen structural system was a bridge cantilever deck. The analysis was limitedto the transversal design of the structure and the goal of the optimization was to reduce investmentcosts. In order to guarantee efficiency of the simulations, a "longitudinal length convergence"analysis was performed. It consisted of determining the minimum required longitudinal length(perpendicular to the cantilever length) that ensured reasonable accuracy. The purpose of thisanalysis was to reduce the computational time during the optimization process. In order toautomate the analysis, MATLAB was used in connection to Abaqus (to perform the FE Analysis).There were three different sets of results presented: the length convergence, application toreal projects and parametric study. In the first application, it was shown that the requiredlongitudinal length (lx) proportionally decreased as the cantilever length (lc) increased. It wasalso observed the presence of the edge beam implied in consistently larger longitudinal lengthsfor the same accuracy tolerance. With respect to the second application, two projects wereconsidered and the structural optimization presented alternatives with significant investment costreduction in a reasonable time. Furthermore, it was observed that a design solution without theedge beam reduced the costs even more. Finally, the parametric study confirmed that the costreduction obtained by eliminating the edge beam was not restricted to only certain cantileverlengths. Furthermore, it was possible to obtain the pattern of thickness variation as function ofthe cantilever length.The results of this research suggest that structural optimization could be an alternative totraditional design methods used today in consulting offices and its possibilities transcend puredesign achievements.

A procedure for generating a customized weight function for wing bending material weight of a High Speed Civil Transport (HSCT) is described. The weight function is based on HSCT configuration parameters. A response surface methodology is used to fit a quadratic polynomial to data gathered from a large number of structural optimizations. To reduce the time of performing a large number of structural optimizations, coarse-grained parallelization with a master-slave processor assignment on an Intel Paragon computer is used. The results of the structural optimization are noisy. Noise reduction in the structural optimization results is discussed. It is shown that the response surface filters out this noise. A statistical design of experiments technique is used to minimize the number of required structural optimizations and to maintain accuracy. Simple analysis techniques are used to find regions of the design space where reasonable HSCT designs could occur, thus customizing the weight function to the design requirements of the HSCT, while the response surface itself is created employing detailed analysis methods. Analysis of variance is used to reduce the number of polynomial terms in the response surface model function. Linear and constant corrections based on a small number of high fidelity results are employed to improve the accuracy of the response surface model. Configuration optimization of the HSCT employing a customized weight function is compared to the configuration optimization of the HSCT with a general weight function. / Ph. D.

Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2009. / Although mass minimisation is an important application within structural optimisation, other applications include: (1) concept generation, (2) concept evaluation, (3) design for structural feasibility and (4) data matching. These applications, except data matching, are discussed and illustrated on a prototype design of the Karoo Array Telescope (KAT) antenna. The KAT passed through the design process and a full scale prototype was built, but was found to be too expensive. A detailed finite element model of the finalised design was considered as a test bed for reducing costs. Size-, shape- and topology optimisation are applied to three KAT components, while considering wind, temperature and gravity loads. Structural- and nonstructural constraints are introduced. Coupling of the structural optimisation code with an external analysis program to include non-structural responses and the parallelisation of the sensitivity calculations are presented. It is shown that if a finite element model is available, it is generally possible to apply structural optimisation to improve an existing design. A reduction of 2673 kg steel was accomplished for the existing KAT components. The total cost saving for the project will be significant, when considering that a large amount of antennas will be manufactured.

L’objectif de cette thèse est le développement de méthodes d’optimisation multi-objectif pour la résolution de problèmes de conception des structures mécaniques. En effet, la plupart des problèmes réels dans le domaine de la mécanique des structures ont plusieurs objectifs qui sont souvent antagonistes. Il s’agit, par exemple, de concevoir des structures en optimisant leurs poids, leurs tailles, et leurs coûts de production. Le but des méthodes d’optimisation multi-objectif est la recherche des solutions de compromis entre les objectifs étant donné l’impossibilité de satisfaire tout simultanément. Les métaheuristiques sont des méthodes d’optimisation capables de résoudre les problèmes d’optimisation multi-objective en un temps de calcul raisonnable sans garantie de l’optimalité de (s) solution (s). Au cours des dernières années, ces algorithmes ont été appliqués avec succès pour résoudre le problème des mécaniques des structures. Dans cette thèse deux métaheuristiques ont été développées pour la résolution des problèmes d’optimisation multi-objectif en général et de conception de structures mécaniques en particulier. Le premier algorithme baptisé MOBSA utilise les opérateurs de croisement et de mutation de l’algorithme BSA. Le deuxième algorithme nommé NNIA+X est une hybridation d’un algorithme immunitaire et de trois croisements inspirés de l’opérateur de croisement original de l’algorithme BSA. Pour évaluer l’efficacité et l’efficience de ces deux algorithmes, des tests sur quelques problèmes dans littérature ont été réalisés avec une comparaison avec des algorithmes bien connus dans le domaine de l’optimisation multi-objectif. Les résultats de comparaison en utilisant des métriques très utilisées dans la littérature ont démontré que ces deux algorithmes peuvent concurrencer leurs prédécesseurs. / The objective of this thesis is the development of multi-objective optimization methods for solving mechanical design problems. Indeed, most of the real problems in the field of mechanical structures have several objectives that are often antagonistic. For example, it is about designing structures by optimizing their weight, their size, and their production costs. The goal of multi-objective optimization methods is the search for compromise solutions between objectives given the impossibility to satisfy all simultaneously. Metaheuristics are optimization methods capable of solving multi-objective optimization problems in a reasonable calculation time without guaranteeing the optimality of the solution (s). In recent years, these algorithms have been successfully applied to solve the problem of structural mechanics. In this thesis, two metaheuristics have been developed for the resolution of multi-objective optimization problems in general and of mechanical structures design in particular. The first algorithm called MOBSA used the crossover and mutation operators of the BSA algorithm. The second one named NNIA+X is a hybridization of an immune algorithm and three crossover inspired by the original crossover operator of the BSA algorithm. To evaluate the effectiveness and efficiency of these two algorithms, tests on some problems in literature have been made with a comparison with algorithms well known in the field of multi-objective optimization. The comparison results using metrics widely used in the literature have shown that our two algorithms can compete with their predecessors.