Thematische Bibliographien / Multi-objective topology optimization

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Auswahl der wissenschaftlichen Literatur zum Thema „Multi-objective topology optimization“

Autor: Grafiati
Veröffentlicht am 30. Juni 2021
Zuletzt aktualisiert am 7. Februar 2022

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Zeitschriftenartikel zum Thema "Multi-objective topology optimization"

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Lee, Chen Jian Ken, and Hirohisa Noguchi. "515 Multi-objective topology optimization involving 3D surfaces." Proceedings of The Computational Mechanics Conference 2008.21 (2008): 233–34. http://dx.doi.org/10.1299/jsmecmd.2008.21.233.

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Kunakote, Tawatchai, and Sujin Bureerat. "Multi-objective topology optimization using evolutionary algorithms." Engineering Optimization 43, no. 5 (2011): 541–57. http://dx.doi.org/10.1080/0305215x.2010.502935.

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Gong, Yunyi, Yoshitsugu Otomo, and Hajime Igarashi. "Multi-objective topology optimization of magnetic couplers for wireless power transfer." International Journal of Applied Electromagnetics and Mechanics 64, no. 1-4 (2020): 325–33. http://dx.doi.org/10.3233/jae-209337.

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In this paper, the multi-objective topology optimizations of wireless power transfer (WPT) devices with two different coil geometries are proposed for obtaining the designs with good balance between transfer efficiency and safety. For this purpose, the proposed method adopts the normalized Gaussian network (NGnet) and Non-dominated Sorting Genetic Algorithm II (NSGA-II). In addition, the optimization under the different constraint on ferrite volume is carried out to verify its influence on optimization results. It has been shown that the proposed method successfully provides the Pareto solution to the design problem of the WPT device.
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Guo, Weian, Ming Chen, Lei Wang, and Qidi Wu. "Hyper multi-objective evolutionary algorithm for multi-objective optimization problems." Soft Computing 21, no. 20 (2016): 5883–91. http://dx.doi.org/10.1007/s00500-016-2163-5.

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Bian, Xiang, Zong De Fang, Kun Qin, Lifei Lian, and Bao Yu Zhang. "Multi-Objective Topology Optimization for Bevel Gear and Geometrical Reconstruction." Applied Mechanics and Materials 278-280 (January 2013): 139–42. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.139.

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Usually the gear modification is a main measure to reduce the vibration and noise of the gears, but in view of the complexity of the gear modification, topology optimization method was used to optimize the structure of the gear. The minimum volume was set as the direct optimization goal. To achieve the target of reducing contact stress, tooth root bending stress and improving flexibility, the upper bound of the stress and lower bound of the flexibility were set appropriately, thus realizing multi-objective optimization indirectly. A method for converting topology result into parametric CAD model which can be modified was presented, by fitting the topology result with simple straight lines and arcs, the model can be smoothed automatically, after further regulating, the geometry reconstruction was finished. After topology optimization, the resulting structure and properties of the gear are consistent with cavity gear. While reducing the weight of the gear, the noise can be reduced and its life would be extended through increasing flexibility and reducing tooth root stress.
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Zuliani, João Batista Queiroz, Miri Weiss Cohen, Lucas de Souza Batista, and Frederico Gadelha Guimarães. "Multi-objective Topology Optimization with Ant Colony Optimization and Genetic Algorithms." Computer-Aided Design and Applications 12, no. 6 (2015): 674–82. http://dx.doi.org/10.1080/16864360.2015.1033328.

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Queiroz Zuliani, João Batista, Miri Weiss Cohen, Frederico Gadelha Guimarães, and Carlos Alberto Severiano Junior. "A multi-objective approach for multi-material topology and shape optimization." Engineering Optimization 51, no. 6 (2018): 915–40. http://dx.doi.org/10.1080/0305215x.2018.1514501.

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LI, Dongmei. "Multi-objective Topology Optimization of Thermo-mechanical Compliant Mechanisms." Chinese Journal of Mechanical Engineering 24, no. 06 (2011): 1123. http://dx.doi.org/10.3901/cjme.2011.06.1123.

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Borovinšek, Matej, Nejc Novak, Matej Vesenjak, Zoran Ren, and Miran Ulbin. "Designing 2D auxetic structures using multi-objective topology optimization." Materials Science and Engineering: A 795 (September 2020): 139914. http://dx.doi.org/10.1016/j.msea.2020.139914.

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Aguilar Madeira, J. F., H. Rodrigues, and Heitor Pina. "Multi-objective optimization of structures topology by genetic algorithms." Advances in Engineering Software 36, no. 1 (2005): 21–28. http://dx.doi.org/10.1016/j.advengsoft.2003.07.001.

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Dissertationen zum Thema "Multi-objective topology optimization"

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Haidine, Abdelfatteh. "Multi-objective combinatorial optimization in topology planning of wireline broadband access networks." Köln WiKu-Verl, 2008. http://d-nb.info/99229200X/04.

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Curwen, Vincent, and Alexander Saxin. "Analysis and optimal design of a titanium aircraft bracket using topology optimization." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-20004.

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Sustainable engineering within product development is becoming increasingly important with the ever-growing amounts of resources used to sustain the human way of life in modern times. An effective way of helping to deal with this problem is to reduce the resources used in products and components across the world. This thesis explores the effectiveness of the topology optimization method in achieving significant material reductions whilst maintaining structural strength and integrity when designing an aircraft component. The part is an engine handling mounting bracket which will be optimized to be produced by additive manufacturing, and so restrictions imposed by traditional manufacturing methods are not considered, allowing for larger material reductions to be achieved. The original bracket part was provided by GE Electric, and the computer software Abaqus computer aided engineering with integrated TOSCA was used to solve the problem. Two trials were conducted, with the first being used to gain knowledge and understanding of the optimization features of the software. The basic requirements for the optimized design were that it should be able to withstand four given static load cases without undergoing plastic deformation, and these load cases were applied separately in trial 1 for simplicity. The second trial was conducted with a higher complexity, utilising multi-objective topology optimization which allowed the load cases to be weighted individually whilst being applied simultaneously during optimization. The resulting bracket part that was created with the help of the optimized topology from trial 2 reduced the volume of the original part by over 75%. This also left potential for further material reductions as the optimized part did not undergo plastic deformation when subject to any of the four load cases of the study. In conclusion, topology optimization seems to be extremely helpful when designing components that have clearly defined load cases, producing results that designers and engineers can have confidence in. The method does however have its flaws, such as difficulties in utilising the optimized topology directly to create a computer aided design part file. The post-processing process needed to achieve such a part is also time-consuming although it must be implemented to create a digital part that can be analysed and verified by FEA.
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Pardo, María Alejandra Guzmán. "Técnicas de otimização baseadas em quimiotaxia de bactérias." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/18/18146/tde-19012011-120319/.

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Em sentido geral, a quimiotaxia é o movimento dirigido que desenvolvem alguns seres vivos em resposta aos gradientes químicos presentes no seu ambiente. Uma bactéria é um organismo unicelular que usa a quimiotaxia como mecanismo de mobilização para encontrar os nutrientes de que precisa para sobreviver e para escapar de ambientes nocivos. Evoluída durante milhões de anos pela natureza, a quimiotaxia de bactérias é um processo altamente otimizado de busca e exploração em espaços desconhecidos. Graças aos avanços no campo da computação, as estratégias quimiotácticas das bactérias e sua excelente capacidade de busca podem ser modeladas, simuladas e emuladas para desenvolver métodos de otimização inspirados na natureza que sejam uma alternativa aos métodos já existentes. Neste trabalho, desenvolvem-se dois algoritmos baseados em estratégias quimiotácticas de bactérias: o BCBTOA (Bacterial Chemotaxis Based Topology Optimization Algorithm) e o BCMOA (Bacterial Chemotaxis Multiobjective Optimization Algorithm) os quais são um algoritmo de otimização topológica e um algoritmo de otimização multi-objetivo, respectivamente. O desempenho dos algoritmos é avaliado mediante a sua aplicação à solução de diversos problemas de prova e os resultados são comparados com os de outros algoritmos atualmente relevantes. O algoritmo de otimização multi-objetivo desenvolvido, também foi aplicado na solução de três problemas de otimização de projeto mecânico de eixos. Os resultados obtidos e os analise comparativos feitos, permitem concluir que os algoritmos desenvolvidos são altamente competitivos e demonstram o potencial do processo de quimiotaxia de bactérias como fonte de inspiração de algoritmos de otimização distribuída, contribuindo assim, a dar resposta à constante demanda por técnicas de otimização mais eficazes e robustas.<br>In general, chemotaxis is the biased movement developed by certain living organisms as a response to chemical gradients present in their environment. A bacterium is a unicellular organism that uses chemotaxis as a mechanism for mobilization that allows it to find nutrients needed to survive and to escape from harmful environments. Millions of years of natural evolution became bacterial chemotaxis a highly optimized process in searching and exploration of unknown spaces. Thanks to advances in the computing field, bacterial chemotactical strategies and its excellent ability in searching can be modeled, simulated and emulated developing bio-inspired optimization methods as alternatives to classical methods. Two algorithms based on bacterial chemotactical strategies were designed, developed and implemented in this work: i) the topology optimization algorithm, BCBTOA (Bacterial Chemotaxis Based Topology Optimization Algorithm) and ii) the multi-objective optimization algorithm, BCMOA (Bacterial Chemotaxis Multiobjective Optimization Algorithm). Algorithms performances were evaluated by their applications in the solution of benchmark problems and the results obtained were compared with other algorithms also relevant today. The BCMOA developed here was also applied in the solution of three mechanical design problems. The results obtained as well as the comparative analysis conducted lead to conclude that the algorithms developed were competitive. This also demonstrates the potential of bacterial chemotaxis as a process in which distributed optimization techniques can be inspired.
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Li, Yilun. "Numerical methodologies for topology optimization of electromagnetic devices." Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS228.

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L'optimisation de la topologie est la conception conceptuelle d'un produit. En comparaison avec les approches de conception conventionnelles, il peut créer une nouvelle topologie, qui ne pouvait être imaginée à l’avance, en particulier pour la conception d’un produit sans expérience préalable ni connaissance. En effet, la technique de la topologie consistant à rechercher des topologies efficaces à partir de brouillon devient un sérieux atout pour les concepteurs. Bien qu’elle provienne de l'optimisation de la structure, l'optimisation de la topologie en champ électromagnétique a prospéré au cours des deux dernières décennies. De nos jours, l'optimisation de la topologie est devenue le paradigme des techniques d'ingénierie prédominantes pour fournir une méthode de conception quantitative pour la conception technique moderne. Cependant, en raison de sa nature complexe, le développement de méthodes et de stratégies applicables pour l’optimisation de la topologie est toujours en cours. Pour traiter les problèmes et défis typiques rencontrés dans le processus d'optimisation de l'ingénierie, en considérant les méthodes existantes dans la littérature, cette thèse se concentre sur les méthodes d'optimisation de la topologie basées sur des algorithmes déterministes et stochastiques. Les travaile principal et la réalisation peuvent être résumés comme suit: Premièrement, pour résoudre la convergence prématurée vers un point optimal local de la méthode ON/OFF existante, un Tabu-ON/OFF, un Quantum-inspiré Evolutif Algorithme (QEA) amélioré et une Génétique Algorithme (GA) amélioré sont proposés successivement. Les caractéristiques de chaque algorithme sont élaborées et ses performances sont comparées de manière exhaustive. Deuxièmement, pour résoudre le problème de densité intermédiaire rencontré dans les méthodes basées sur la densité et le problème que la topologie optimisée est peu utilisée directement pour la production réelle, deux méthodes d'optimisation de la topologie, à savoir Matérial Isotrope solide avec pénalisation (SIMP)-Fonction de Base Radiale (RBF) et Méthode du Level Set (LSM)-Fonction de Base Radiale (RBF). Les deux méthodes calculent les informations de sensibilité de la fonction objectif et utilisent des optimiseurs déterministes pour guider le processus d'optimisation. Pour le problème posé par un grand nombre de variables de conception, le coût de calcul des méthodes proposées est considérablement réduit par rapport à celui des méthodes de comptabilisation sur des algorithmes stochastiques. Dans le même temps, en raison de l'introduction de la technique de lissage par interpolation de données RBF, la topologie optimisée est plus adaptée aux productions réelles. Troisièmement, afin de réduire les coût informatiques excessifs lorsqu’un algorithme de recherche stochastique est utilisé dans l’optimisation de la topologie, une stratégie de redistribution des variables de conception est proposée. Dans la stratégie proposée, l’ensemble du processus de recherche d’une optimisation de la topologie est divisé en structures en couches. La solution de la couche précédente est défini comme topologie initiale pour la couche d'optimisation suivante, et seuls les éléments adjacents à la limite sont choisis comme variables de conception. Par conséquent, le nombre de variables de conception est réduit dans une certaine mesure; le temps de calcul du processus est ainsi raccourci. Enfin, une méthodologie d’optimisation de topologie multi-objectif basée sur l’algorithme d’optimisation hybride multi-objectif combinant l’Algorithme Génétique de Tri Non dominé II (NSGAII) et l’algorithme d’Evolution Différentielle (DE) est proposée<br>Topology optimization is the conceptual design of a product. Comparing with conventional design approaches, it can create a novel topology, which could not be imagined beforehand, especially for the design of a product without prior-experiences or knowledge. Indeed, the topology optimization technique with the ability of finding efficient topologies starting from scratch has become a serious asset for the designers. Although originated from structure optimization, topology optimization in electromagnetic field has flourished in the past two decades. Nowadays, topology optimization has become the paradigm of the predominant engineering techniques to provide a quantitative design method for modern engineering design. However, due to its inherent complex nature, the development of applicable methods and strategies for topology optimization is still in progress. To address the typical problems and challenges encountered in an engineering optimization process, considering the existing methods in the literature, this thesis focuses on topology optimization methods based on deterministic and stochastic algorithms. The main work and achievement can be summarized as: Firstly, to solve the premature convergence to a local optimal point of existing ON/OFF method, a Tabu-ON/OFF, an improved Quantum-inspired Evolutionary Algorithm (QEA) and an improved Genetic Algorithm (GA) are proposed successively. The characteristics of each algorithm are elaborated, and its performance is compared comprehensively. Secondly, to solve the intermediate density problem encountered in density-based methods and the engineering infeasibility of the finally optimized topology, two topology optimization methods, namely Solid Isotropic Material with Penalization-Radial Basis Function (SIMP-RBF) and Level Set Method-Radial Basis Function (LSM-RBF) are proposed. Both methods calculate the sensitivity information of the objective function, and use deterministic optimizers to guide the optimizing process. For the problem with a large number of design variables, the computational cost of the proposed methods is greatly reduced compared with those of the methods accounting on stochastic algorithms. At the same time, due to the introduction of RBF data interpolation smoothing technique, the optimized topology is more conducive in actual productions. Thirdly, to reduce the excessive computing costs when a stochastic searching algorithm is used in topology optimization, a design variable redistribution strategy is proposed. In the proposed strategy, the whole searching process of a topology optimization is divided into layered structures. The solution of the previous layer is set as the initial topology for the next optimization layer, and only elements adjacent to the boundary are chosen as design variables. Consequently, the number of design variables is reduced to some extent; and the computation time is thereby shortened. Finally, a multi-objective topology optimization methodology based on the hybrid multi-objective optimization algorithm combining Non-dominated Sorting Genetic Algorithm II (NSGAII) and Differential Evolution (DE) algorithm is proposed. The comparison results on test functions indicate that the performance of the proposed hybrid algorithm is better than those of the traditional NSGAII and Strength Pareto Evolutionary Algorithm 2 (SPEA2), which guarantee the good global optimal ability of the proposed methodology, and enables a designer to handle constraint conditions in a direct way. To validate the proposed topology optimization methodologies, two study cases are optimized and analyzed
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Akteke-ozturk, Basak. "New Approaches To Desirability Functions By Nonsmooth And Nonlinear Optimization." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612649/index.pdf.

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Desirability Functions continue to attract attention of scientists and researchers working in the area of multi-response optimization. There are many versions of such functions, differing mainly in formulations of individual and overall desirability functions. Derringer and Suich&rsquo<br>s desirability functions being used throughout this thesis are still the most preferred ones in practice and many other versions are derived from these. On the other hand, they have a drawback of containing nondifferentiable points and, hence, being nonsmooth. Current approaches to their optimization, which are based on derivative-free search techniques and modification of the functions by higher-degree polynomials, need to be diversified considering opportunities offered by modern nonlinear (global) optimization techniques and related softwares. A first motivation of this work is to develop a new efficient solution strategy for the maximization of overall desirability functions which comes out to be a nonsmooth composite constrained optimization problem by nonsmooth optimization methods. We observe that individual desirability functions used in practical computations are of mintype, a subclass of continuous selection functions. To reveal the mechanism that gives rise to a variation in the piecewise structure of desirability functions used in practice, we concentrate on a component-wise and generically piecewise min-type functions and, later on, max-type functions. It is our second motivation to analyze the structural and topological properties of desirability functions via piecewise max-type functions. In this thesis, we introduce adjusted desirability functions based on a reformulation of the individual desirability functions by a binary integer variable in order to deal with their piecewise definition. We define a constraint on the binary variable to obtain a continuous optimization problem of a nonlinear objective function including nondifferentiable points with the constraints of bounds for factors and responses. After describing the adjusted desirability functions on two well-known problems from the literature, we implement modified subgradient algorithm (MSG) in GAMS incorporating to CONOPT solver of GAMS software for solving the corresponding optimization problems. Moreover, BARON solver of GAMS is used to solve these optimization problems including adjusted desirability functions. Numerical applications with BARON show that this is a more efficient alternative solution strategy than the current desirability maximization approaches. We apply negative logarithm to the desirability functions and consider the properties of the resulting functions when they include more than one nondifferentiable point. With this approach we reveal the structure of the functions and employ the piecewise max-type functions as generalized desirability functions (GDFs). We introduce a suitable finite partitioning procedure of the individual functions over their compact and connected interval that yield our so-called GDFs. Hence, we construct GDFs with piecewise max-type functions which have efficient structural and topological properties. We present the structural stability, optimality and constraint qualification properties of GDFs using that of max-type functions. As a by-product of our GDF study, we develop a new method called two-stage (bilevel) approach for multi-objective optimization problems, based on a separation of the parameters: in y-space (optimization) and in x-space (representation). This approach is about calculating the factor variables corresponding to the ideal solutions of each individual functions in y, and then finding a set of compromised solutions in x by considering the convex hull of the ideal factors. This is an early attempt of a new multi-objective optimization method. Our first results show that global optimum of the overall problem may not be an element of the set of compromised solution. The overall problem in both x and y is extended to a new refined (disjunctive) generalized semi-infinite problem, herewith analyzing the stability and robustness properties of the objective function. In this course, we introduce the so-called robust optimization of desirability functions for the cases when response models contain uncertainty. Throughout this thesis, we give several modifications and extensions of the optimization problem of overall desirability functions.
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Pinho, Flávio Augusto Xavier Carneiro. "Métodos de densidade em otimização de topologia aplicados a subsistemas de edifícios." Universidade Federal de Goiás, 2015. http://repositorio.bc.ufg.br/tede/handle/tede/5187.

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Submitted by Cláudia Bueno (claudiamoura18@gmail.com) on 2016-01-29T14:45:57Z No. of bitstreams: 2 Dissertação - Flávio Augusto Xavier Carneiro Pinho - 2015.pdf: 5478560 bytes, checksum: 3507be4593cbd586348d2f5a2bfe2f9f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)<br>Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-02-01T11:53:05Z (GMT) No. of bitstreams: 2 Dissertação - Flávio Augusto Xavier Carneiro Pinho - 2015.pdf: 5478560 bytes, checksum: 3507be4593cbd586348d2f5a2bfe2f9f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)<br>Made available in DSpace on 2016-02-01T11:53:05Z (GMT). No. of bitstreams: 2 Dissertação - Flávio Augusto Xavier Carneiro Pinho - 2015.pdf: 5478560 bytes, checksum: 3507be4593cbd586348d2f5a2bfe2f9f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-04-10<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>Optimization techniques have been widely used in different engineering applications. In the case of structural conception, these techniques can be applied from the architectural concept, determining, for example, bracing structures to setting the best topology for concrete structures, as those compared to strut and tie models. In this context, this thesis presents techniques applied to topology optimization in subsystems of buildings. It is also presented a new software tool, modelled in object-oriented programming, seeking the solution for topology optimization problems assembling various technical problems unified in a single approach. The software tool was used to determine the best shape to bracing frames on a building submited to different loading combinations as well to compare the strut and tie models to foundation blocks. Results were compared to literature review, validating the unified computational procedure. Strut and tie models found in literature were compared to piled foundation blocks varying the number of piles, and whose geometry for larger number of piles are still not clearly defined.<br>Técnicas de otimização têm sido especialmente utilizadas em diversos problemas de engenharia. No caso da concepção estrutural de grandes edifícios, essas técnicas podem ser utilizadas desde o partido arquitetônico. Neste caso, podem ser determinadas, por exemplo, estruturas de contraventamento. Outro exemplo é a aplicação da otimização de topologia para determinação do modelo de bielas e tirantes de estruturas de concreto armado. Neste trabalho, são utilizadas técnicas de otimização de topologia aplicadas em subsistemas de edifícios. Apresenta-se um software em linguagem de programação orientada a objeto para a solução de problemas de otimização de topologia em que são reunidas diferentes técnicas características do problema as quais são unificadas em uma única abordagem. Esse software é aplicado para determinar a melhor forma da estrutura de contraventamento de edifícios altos submetidos a diversas combinações de carregamentos e para determinação do modelo de bielas e tirantes de blocos de fundações. Os resultados encontrados validam a utilização da uma abordagem unificada já que são condizentes com a literatura. Os modelos de bielas e tirantes encontrados para os blocos de fundações são iguais aos modelos clássicos encontrados na literatura. Também foram estudados blocos de fundações com uma maior quantidade de estacas cujos modelos ainda não possuem geometria bem definida na literatura.
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Oliveira, Giovana Trindade da Silva. "Projeto ótimo de robôs manipuladores 3r considerando a topologia do espaço de trabalho." Universidade Federal de Uberlândia, 2012. https://repositorio.ufu.br/handle/123456789/14706.

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Fundação de Amparo a Pesquisa do Estado de Minas Gerais<br>Several studies have investigated the properties of the workspace of opened robotic chains (or serial) with the purpose of emphasizing its geometric and kinematic characteristics, to devise analytical algorithms and procedures for its design. The workspace of a robot manipulator is considered of great interest from theoretical and practical viewpoint. In classical applications in industry, manipulators need to pass through singularities in the joint space to change their posture. A 3-DOF manipulator can execute a non-singular change of posture if and only if there is at least one point in its workspace which has exactly three coincident solutions of the Inverse Kinematic Model (IKM). It is very difficult to express this condition directly from the kinematic model. Thus, in this work, the algebraic tool Gröbner basis is used to obtain an equation for splitting the regions with different types of 3R orthogonal manipulators. The determinant of Jacobian matrix of the direct kinematic model is considered equal to zero to obtain the other surfaces of separation. In addition, is presented a classification of 3R orthogonal manipulators related to the number of solutions in IKM, the number of cusp points and nodes. Some problems of multi-objective optimization are proposed to obtain the optimal design of robots. First considering a general case where the aim is to maximize the volume of the workspace, maximize the stiffness of the joint system and optimize the dexterity of the manipulator without the imposition of restrictions. Next, the optimization problem is subject to penalties that control the topology, making it possible to obtain solutions which satisfy the predetermined topologies. Solutions are presented for the case r3 null and r3 not null. The optimization problem is investigated by using a deterministic technique and two evolutionary algorithms. Some numerical applications are presented to show the efficiency of the proposed methodology.<br>Diversos estudos têm investigado as propriedades do espaço de trabalho de cadeias robóticas abertas com o objetivo de enfatizar suas características geométricas e cinemáticas, criar algoritmos analíticos e procedimentos para o seu projeto. O espaço de trabalho de um robô manipulador é considerado de grande interesse do ponto de vista teórico e prático. Em aplicações clássicas na indústria, manipuladores precisam passar por singularidades no espaço das juntas para mudar sua postura. Um manipulador com três graus de liberdade pode executar uma mudança de postura não singular se, e somente se, existe pelo menos um ponto em seu espaço de trabalho que tem exatamente três soluções coincidentes do Modelo Geométrico Inverso (MGI). É muito difícil expressar esta condição a partir do modelo cinemático. Assim, neste trabalho, a ferramenta algébrica base de Groebner é utilizada para obter uma das equações que separam as regiões que possuem diferentes tipos de manipuladores 3R ortogonais. O determinante da matriz Jacobiana do Modelo Geométrico Direto é considerado nulo para obter as demais superfícies de separação. Além disso, apresenta-se uma classificação dos manipuladores 3R ortogonais em relação ao número de soluções no MGI, o número de pontos de cúspides e o número de nós. Alguns problemas de otimização multi-objetivo são propostos visando obter o projeto ótimo de robôs. Primeiramente, considera-se o caso geral, cujo objetivo é maximizar o volume do espaço de trabalho, maximizar a rigidez do sistema de juntas e otimizar a destreza do manipulador sem a imposição de restrições. Em seguida, o problema de otimização é sujeito a penalidades que controlam a topologia, tornando possível a obtenção de soluções que obedeçam as topologias pré-estabelecidas. São apresentadas as soluções para o caso r3 nulo e para r3 não nulo. O problema de otimização é investigado aplicando uma técnica determinística e dois algoritmos evolutivos. Algumas aplicações numéricas são apresentadas para mostrar a eficiência da metodologia proposta.<br>Doutor em Engenharia Mecânica
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Jiang, Yi-Syuan, and 江倚瑄. "Topology Optimization of a Load Cell via a Multi-objective Genetic Algorithm." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/37469397528422536759.

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碩士<br>國立臺灣大學<br>機械工程學研究所<br>104<br>A load cell for measuring the lift force generated by flapping wings of an insect must have a high fundamental frequency and low stiffness to meet the stringent precision requirements. This thesis aims to design a load cell that can record the waveform of the lift of an insect accurately. Starting from a rectangular shape with specified material properties, a multi-objective genetic algorithm, called NSGA-II, is employed to find the optimal shape of the load cell. A finite element analysis program is developed to determine the values of the objective functions. In NSGA-II, the non-dominated sorting method and crowded-comparison approach are used to increase the genetic diversity as well as keep the elite genes. Because the boundary conditions and applied force are symmetric with respect to the central line of the load cell, we restrict the outcomes of the optimization program to symmetrical structures. The restriction is then removed. The performance of the asymmetrical optimal results thus generated is compared with that of the performance of the symmetrical ones. In order to reduce the computation time, the optimization is first performed on a coarse mesh for the generation of primitive structures. Then the meshes of some specified areas of a primitive optimal structure are refined. Optimization is performed on the refined meshes to determine the final topology of the load cell. In this way, the computational burden can be largely reduced. Prototypes of several optimal designs are manufactured by 3D printing. Experimental test results for the fundamental frequency and flexibility of these prototypes are compared with those of the numerical simulation.
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Tsai, Chih-Chieh, and 蔡至捷. "Topology Optimization of a Load Cell via a Multi-objective Particle Swarm Algorithm." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/9uup2e.

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碩士<br>國立臺灣大學<br>機械工程學研究所<br>106<br>A good load cell should have a wide band-width and large flexibility to meet the demand of high resolution. It’s very difficult to satisfy these two conflicting demands. This research aims to find a proper design, thorough topology optimization, of a load cell possessing both proper band-width and flexibility. The load cell studied in this thesis is a planar frame. The position of every joint and cross-section area of each rod are used as design variables. The objective functions are the fundamental frequency and the static deflection at the free end of the structure. The Pareto solutions in the design space are located by a multi-objective particle swarm optimization (MOPSO) algorithm. The values of the objective functions are determined using an in-house finite element method code. The MOPSO algorithm proposed by Coello [1], which introduces a mutation operator and a roulette-wheel selection scheme for maintaining the diversity of the particles, is employed to find the optimal designs. In this thesis, several schemes for constructing the frame of the load cell are tested. The symmetrical structures with angle braces have the best performance. In order to find proper designs in a feasible time, we first determine the primary frames under the restriction that the every rod has the same cross-sectional area. Then a primary design in the Pareto set is chosen and further optimized. In the final optimization process, the cross-sectional dimensions of each rod as well as the coordinates of each joint are used as design variables. The final optimal designs are compared with previous designs obtained using different topological optimization algorithms.
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Kang, Yu-Chia, and 康祐嘉. "An Integrated Method of Moving Asymptotes and Fuzzy Theory for Multi-objective Topology Optimization." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/71101397953729470644.

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碩士<br>淡江大學<br>航空太空工程學系碩士班<br>100<br>An integrated method of moving asymptotes and fuzzy theory for multi-objective topology optimization is developed in this study. The finite element analysis software ANSYS is used for structural analysis. By using the method of material distribution with method of moving asymptotes, the optimum topology design of structure is obtained. In this paper, the multi-objective optimization problem transfer to single optimization problem by utilizing the concept of the fuzzy theory, which is using membership function and intersection set of decision-making. After implementing the concept above, the Pareto solution of the multi-objective topology optimization problem can be obtained. Three stages of topology design were employed in this study. In first stage, a dual method is used to obtain the initial topology design. To eliminate unnecessary element and retain necessary element by element growth-removal combined method (EGRCM) in second stage. The B-Spline curve is used to smooth the design shape in the final stage. Four different multi-objective problems are demonstrated in this paper. The topology optimization result will be discussed in each stage. After using three stages topology design, the results shows that the optimum shapes of structures are more clear and smooth.
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Buchteile zum Thema "Multi-objective topology optimization"

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Giusti, Sebastián Miguel, and Antonio André Novotny. "Multi-objective Topology Optimization Design of Micro-structures." In Computational Modeling, Optimization and Manufacturing Simulation of Advanced Engineering Materials. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-04265-7_2.

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Najafabadi, Hossein R., Tiago G. Goto, Thiago C. Martins, Ahmad Barari, and Marcos S. G. Tsuzuki. "Multi-objective Topology Optimization Using Simulated Annealing Method." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63403-2_31.

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Munk, David J., Gareth A. Vio, Grant P. Steven, and Timoleon Kipouros. "Producing Smart Pareto Sets for Multi-objective Topology Optimisation Problems." In Advances in Structural and Multidisciplinary Optimization. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67988-4_10.

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Munk, David J., Timoleon Kipouros, and Gareth A. Vio. "A Generalized SNC-BESO Method for Multi-objective Topology Optimization." In EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97773-7_1.

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Xu, Jianan, Xin Gao, and Dongyue Qu. "Multi-objective Topology Optimization for Supporting Plate of Winch Drum Spindle." In Advances in Mechanical Design. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6553-8_27.

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Zăvoianu, Alexandru-Ciprian, Gerd Bramerdorfer, Edwin Lughofer, and Susanne Saminger-Platz. "Multi-objective Topology Optimization of Electrical Machine Designs Using Evolutionary Algorithms with Discrete and Real Encodings." In Computer Aided Systems Theory – EUROCAST 2017. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74718-7_40.

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Aulig, N., S. Menzel, E. Nutwell, and D. Detwiler. "Towards multi-objective topology optimization of structures subject to crash and static load cases." In Engineering Optimization 2014. CRC Press, 2014. http://dx.doi.org/10.1201/b17488-151.

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Sahini, Deepak Kumar, Joyjeet Ghose, Sanjay Kumar Jha, Ajit Behera, and Animesh Mandal. "Optimization and Simulation of Additive Manufacturing Processes." In Advances in Civil and Industrial Engineering. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-4054-1.ch010.

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Additive manufacturing (AM) has developed and gained popularity across the globe into a multi-billion-dollar industry that involves many materials and techniques. AM has created itself as a technology for the manufacturing of metallic parts with enhanced mechanical characteristics that are scientifically sound and commercially feasible. However, there are various challenges, from business point of view, like high machine and material costs. Considering the complexities involved, sustainable manufacturing, optimization tools, and simulation models are necessary in order to save time and costly trial and errors. Topology optimization and simulation of AM processes are commercially available and are receiving attention from scientists and industry. Thus, this chapter is designed to provide readers with a brief introduction to AM technologies with typical applications. The main objective of this chapter is to provide the current trends and innovations in the field of design for additive manufacturing (DFAM), topology optimization, and simulation technologies.
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Konferenzberichte zum Thema "Multi-objective topology optimization"

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Olympio, Kingnide, and Farhan Gandhi. "Skin Designs Using Multi-Objective Topology Optimization." In 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
16th AIAA/ASME/AHS Adaptive Structures Conference
10t. American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-1793.

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Chu, Xu-yang, Hui-huang Xu, Gui-fang Shao, and Wei-feng Zheng. "Multi-objective topology optimization for industrial robot." In 2016 IEEE International Conference on Information and Automation (ICIA). IEEE, 2016. http://dx.doi.org/10.1109/icinfa.2016.7832132.

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Streichert, Thilo, Christian Haubelt, and Jurgen Teich. "Multi-Objective Topology Optimization for Networked Embedded Systems." In 2006 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation. IEEE, 2006. http://dx.doi.org/10.1109/icsamos.2006.300814.

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Turevsky, Inna, and Krishnan Suresh. "Tracing the Envelope of the Objective-Space in Multi-Objective Topology Optimization." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47329.

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In multi-objective problems, one is often interested in generating the envelope of the objective-space, where the envelope is, in general, a superset of pareto-optimal solutions. In this paper, we propose a method for tracing the envelope of multi-objective topology optimization problems, and generating the corresponding topologies. The proposed method exploits the concept of topological sensitivity, and is applied to bi-objective optimization, namely eigenvalue-volume, eigenvalue-eigenvalue and compliance-eigenvalue problems. The robustness and efficiency of the method is illustrated through numerical examples.
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Hatzakis, Iason, and David Wallace. "Topology of Anticipatory Populations for Evolutionary Dynamic Multi-Objective Optimization." In 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. American Institute of Aeronautics and Astronautics, 2006. http://dx.doi.org/10.2514/6.2006-7071.

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Nathan, Nathan, Pramudita S. Palar, and Lavi Rizki Zuhal. "A Multi-objective Approach for Robust Structural Topology Optimization." In AIAA Scitech 2021 Forum. American Institute of Aeronautics and Astronautics, 2021. http://dx.doi.org/10.2514/6.2021-1777.

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Liang Liang, Jie Zhang, Li-Ping Chen, and Xiao-hong Zhang. "FVM-based multi-objective topology optimization and Matlab implementation." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5619042.

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Jiang, Chuan, HongYi Hu, ZhiZhou Xu, and RuZhen Liu. "The U-type Platform Multi-objective Topology Optimization Research." In 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering. Atlantis Press, 2015. http://dx.doi.org/10.2991/iccmcee-15.2015.242.

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Padhye, Nikhil. "Topology optimization of compliant mechanism using multi-objective particle swarm optimization." In the 2008 GECCO conference companion. ACM Press, 2008. http://dx.doi.org/10.1145/1388969.1388983.

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Zuliani, João Batista, Miri Cohen, Lucas de Souza Batista, and Frederico Gadelha Guimarães. "Multi-objective Topology Optimization with Ant Colony Optimization and Genetic Algorithms." In CAD'14. CAD Solutions LLC, 2014. http://dx.doi.org/10.14733/cadconfp.2014.170-172.

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