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Avgin, Murat Atacan. "Evolutionary Structural Optimization Of Multiple Load Case Generic Aircraft Components." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614973/index.pdf.
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Structural optimization is achieving the best objective function from a predefined medium, well bounded by constraints. Optimization methods have been utilized on different engineering applications to minimize the conceptual design effort that creates the necessity of new optimization techniques. Evolutionary Structural Optimization (ESO) is a topological optimization algorithm, which is defined as removing of inefficient elements from a design domain. ESO stress based method is applied to linear elastic, isotropic aircraft components for multiple load case. The bulk structure is modeled and discretized into three dimensional solid hexahedron or tetrahedron mesh, afterwards constraints, load and boundary conditions are defined in MSC.PATRAN. MSC.NASTRAN is utilized as finite element solver. The stress results are collected and evaluated by program developed in MICROSOFT VISUAL BASIC. The elements which are below the stress limit are eliminated. The remaining elements are operated after increasing the stress limit. The iteration process continued until prescribed rejection ratio is reached. Well known examples in literature are solved using program code and similar results are obtained which is a check for the code developed. Four generic aircraft components, the clevis, the lug, the main landing fitting and power control unit fitting were structurally optimized. The stress distribution in optimized results and existing aircraft designs are compared.
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Agyei, Eugene Osei. "Groundwater modeling and management using the finite element method and evolutionary optimisation techniques /." Title page, synopsis and contents only, 1997. http://web4.library.adelaide.edu.au/theses/09PH/09pha284.pdf.
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Gao, Huanhuan. "Categorical structural optimization : methods and applications." Thesis, Compiègne, 2019. http://www.theses.fr/2019COMP2471/document.
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La thèse se concentre sur une recherche méthodologique sur l'optimisation structurelle catégorielle au moyen d'un apprentissage multiple. Dans cette thèse, les variables catégorielles non ordinales sont traitées comme des variables discrètes multidimensionnelles. Afin de réduire la dimensionnalité, les nombreuses techniques d'apprentissage sont introduites pour trouver la dimensionnalité intrinsèque et mapper l'espace de conception d'origine sur un espace d'ordre réduit. Les mécanismes des techniques d'apprentissage à la fois linéaires et non linéaires sont d'abord étudiés. Ensuite, des exemples numériques sont testés pour comparer les performances de nombreuses techniques d’apprentissage. Sur la base de la représentation d'ordre réduit obtenue par Isomap, les opérateurs de mutation et de croisement évolutifs basés sur les graphes sont proposés pour traiter des problèmes d'optimisation structurelle catégoriels, notamment la conception du dôme, du cadre rigide de six étages et des structures en forme de dame. Ensuite, la méthode de recherche continue consistant à déplacer des asymptotes est exécutée et fournit une solution compétitive, mais inadmissible, en quelques rares itérations. Ensuite, lors de la deuxième étape, une stratégie de recherche discrète est proposée pour rechercher de meilleures solutions basées sur la recherche de voisins. Afin de traiter le cas dans lequel les instances de conception catégorielles sont réparties sur plusieurs variétés, nous proposons une méthode d'apprentissage des variétés k-variétés basée sur l'analyse en composantes principales pondérées<br>The thesis concentrates on a methodological research on categorical structural optimizationby means of manifold learning. The main difficulty of handling the categorical optimization problems lies in the description of the categorical variables: they are presented in a category and do not have any orders. Thus the treatment of the design space is a key issue. In this thesis, the non-ordinal categorical variables are treated as multi-dimensional discrete variables, thus the dimensionality of corresponding design space becomes high. In order to reduce the dimensionality, the manifold learning techniques are introduced to find the intrinsic dimensionality and map the original design space to a reduced-order space. The mechanisms of both linear and non-linear manifold learning techniques are firstly studied. Then numerical examples are tested to compare the performance of manifold learning techniques mentioned above. It is found that the PCA and MDS can only deal with linear or globally approximately linear cases. Isomap preserves the geodesic distances for non-linear manifold however, its time consuming is the most. LLE preserves the neighbour weights and can yield good results in a short time. KPCA works like a non-linear classifier and we proves why it cannot preserve distances or angles in some cases. Based on the reduced-order representation obtained by Isomap, the graph-based evolutionary crossover and mutation operators are proposed to deal with categorical structural optimization problems, including the design of dome, six-story rigid frame and dame-like structures. The results show that the proposed graph-based evolutionary approach constructed on the reduced-order space performs more efficiently than traditional methods including simplex approach or evolutionary approach without reduced-order space. In chapter 5, the LLE is applied to reduce the data dimensionality and a polynomial interpolation helps to construct the responding surface from lower dimensional representation to original data. Then the continuous search method of moving asymptotes is executed and yields a competitively good but inadmissible solution within only a few of iteration numbers. Then in the second stage, a discrete search strategy is proposed to find out better solutions based on a neighbour search. The ten-bar truss and dome structural design problems are tested to show the validity of the method. In the end, this method is compared to the Simulated Annealing algorithm and Covariance Matrix Adaptation Evolutionary Strategy, showing its better optimization efficiency. In chapter 6, in order to deal with the case in which the categorical design instances are distributed on several manifolds, we propose a k-manifolds learning method based on the Weighted Principal Component Analysis. And the obtained manifolds are integrated in the lower dimensional design space. Then the method introduced in chapter 4 is applied to solve the ten-bar truss, the dome and the dame-like structural design problems
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Hagnell, Christian, and Mosanen Kiavosh Saidi. "Topology optimization : A comparison between the SIMP and BESO methods using open-source software." Thesis, Uppsala universitet, Tillämpad mekanik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447869.
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Structural optimization is a useful tool for engineers and designers in construction technology as well asvehicle and mechanical engineering. With structure optimization, a computer can, with the help of finiteelement analysis, calculate the smallest possible amount of material needed to meet the requirements onthe part to be produced.The purpose of this report is to use two different implementations for finite element calculations fortopology optimization of a beam. Results from the optimizations will then be 3D printed with differentsettings. The beam will be tested for displacement, stress and strain in a universal testing machine. Theresults from the experiment will be compared with computed simulations of the same beam.For the structural optimization, two methods are used and compared: Solid Isotropic Material withPenalization and Bidirectional Evolutionary Structural Optimization. A total of eight beams, four fromeach method, were printed with a 3D printer with two different positions on the printer bed and withdifferent degrees of infill ratios. These were tested with a machine that could register both pressure anddeformation and were filmed to be able to see the strain. The deformation of the beams was alsosimulated in a software computer program to see what deformation difference there was betweenexperiment and reality.It turned out that the beams that were printed behaved anisotropic even though solid plastic should beincluded among isotropic materials. The deformation of the model looked like the finite elementcalculation, but the actual deformation was significantly larger than what was calculated by the computersoftware.
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Giger, Mathias. "Representation concepts in evolutionary algorithm-based structural optimization /." Zürich : ETH, 2006. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17017.
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McMeen, John Norman Jr. "Ranking Methods for Global Optimization of Molecular Structures." Digital Commons @ East Tennessee State University, 2014. https://dc.etsu.edu/etd/2447.
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This work presents heuristics for searching large sets of molecular structures for low-energy, stable systems. The goal is to find the globally optimal structures in less time or by consuming less computational resources. The strategies intermittently evaluate and rank structures during molecular dynamics optimizations, culling possible weaker solutions from evaluations earlier, leaving better solutions to receive more simulation time. Although some imprecision was introduced from not allowing all structures to fully optimize before ranking, the strategies identify metrics that can be used to make these searches more efficient when computational resources are limited.
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Ciftci, Erhan. "Evolutionary Algorithms In Design." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/2/12607983/index.pdf.
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Evolutionary Structural Optimization (ESO) is a relatively new design tool used to improve and optimise the design of structures. In this method, a few elements of an initial design domain of finite elements are iteratively removed. Such a process is carried out repeatedly until an optimum design is achieved, or until a desired given area or volume is reached.
In structural design, there is the demand for the development of design tools and methods that includes optimization. This need is the reason behind the development of methods like Evolutionary Structural Optimization (ESO). It is also this demand that this thesis seeks to satisfy. This thesis develops and examines the program named EVO, with the concept of structural optimization in the ESO process. Taking into account the stiffness and stress constraints, EVO allows a realistic and accurate approach to optimising a model in any given environment.
Finally, in verifying the ESO algorithm&rsquo<br>s and EVO program&rsquo<br>s usefulness to the practical aspect of design, the work presented herein applies the ESO method to case studies. They concern the optimization of 2-D frames, and the optimization of 3-D spatial frames and beams with the prepared program EVO. Comparisons of these optimised models are then made to those that exist in literature.
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Proos, Kaarel. "Evolutionary structural optimisation as a robust and reliable design tool." Connect to full text, 2002. http://hdl.handle.net/2123/519.
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Thesis (Ph. D.)--University of Sydney, 2002.<br>Title from title screen (viewed Apr. 28, 2008). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Aeronautical, Mechatronic and Mechanical Engineering. Includes bibliographical references. Also available in print form.
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Ozsayin, Burcu. "Multi-objective Combinatorial Optimization Using Evolutionary Algorithms." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12610866/index.pdf.
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Due to the complexity of multi-objective combinatorial optimization problems (MOCO), metaheuristics like multi-objective evolutionary algorithms (MOEA) are gaining importance to obtain a well-converged and well-dispersed Pareto-optimal frontier approximation. In this study, of the well-known MOCO problems, single-dimensional multi-objective knapsack problem and multi-objective assignment problem are taken into consideration. We develop a steady-state and elitist MOEA in order to approximate the Pareto-optimal frontiers. We utilize a territory concept in order to provide diversity over the Pareto-optimal frontiers of various problem instances. The motivation behind the territory definition is to attach the algorithm the advantage of fast execution by eliminating the need for an explicit diversity preserving operator. We also develop an interactive preference incorporation mechanism to converge to the regions that are of special interest for the decision maker by interacting with him/her during the optimization process.
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Wong, Kin Ming. "Evolutionary structural form optimisation for lateral stiffness design of tall buildings /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?CIVL%202007%20WONGK.
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Cimtalay, Selçuk. "A method to identify move-limits in structural optimization." Thesis, Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/17930.
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Esteban, Jaime. "A reliability-based method for optimization programming problems." Thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-03302010-020045/.
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TAVARES, VINICIUS GAMA. "EFFICIENT STRUCTURAL TOPOLOGY OPTIMIZATION SYSTEM USING THE GROUND STRUCTURE METHOD." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30728@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Métodos de otimização topológica estrutural visam obter a melhor distribuição de material dentro de um dado domínio, sujeito a carga, condições de contorno e restrições de projeto, de forma a minimizar alguma medida especificada. A otimização topológica estrutural pode ser dividida em dois tipos: contínua e discreta, sendo a forma discreta o foco da pesquisa desta dissertação. O objetivo deste trabalho é a criação de um sistema para realizar todos os passos dessa otimização, visando a resolução de problemas
com grandes dimensões. Para realizar esse tipo de otimização, é necessária a criação de uma malha densa de barras, esta definida como conjunto de nós cobrindo todo o domínio, conectados através de barras, além da especificação dos apoios e das forças aplicadas. Este trabalho propõe um novo método para geração da malha densa de barras, utilizando como entrada somente o contorno do domínio que se deseja otimizar, contrapondo com métodos que necessitam de um domínio já discretizado, como uma malha
de poliedros. Com a malha gerada, este trabalho implementou a otimização topológica, sendo necessário resolver um problema de programação linear. Toda a parte de otimização foi realizada dentro do framework TopSim, tendo implementado o método dos pontos interiores para a resolução da programação
linear. Os resultados apresentados possuem boa qualidade, tanto na geração quanto na otimização, para casos 2D e 3D, tratando casos com mais de 68 milhões de barras.<br>Structural topology optimization methods are used to find the optimal material distribution within a given domain, subject to loading, boundary conditions and design constraints, in order to minimize some specified measure. Structural topology optimization can be divided into two types: continuum and discrete, with the discrete type being the research focus of this dissertation. The goal of this work is the creation of a system to achieve all the steps of this optimization process, aiming problems with large dimensions. In order to perform the optimization, it is necessary create a ground structure, defined as a set of nodes covering the entire domain, connected by bars, with the supports and the applied loads. This work
proposes a new method for the ground structure generation, using as input only the domain boundary, in contrast with methods that require a domain already discretized, such as a polyhedron mesh. With the generated mesh, this work has implemented the topological optimization, needing to solve a linear programming problem. All the optimization part was performed within the TopSim framework, implementing the interior point method for the linear programming resolution. The results presented have good quality, both in generation and optimization, for 2D and 3D cases, considering cases with more than 68 million bars.
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Abdi, Meisam. "Evolutionary topology optimization of continuum structures using X-FEM and isovalues of structural performance." Thesis, University of Nottingham, 2015. http://eprints.nottingham.ac.uk/31226/.
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In the last three decades, advances in modern manufacturing processes, such as additive manufacturing (AM) on one hand and computational power on the other hand, has resulted in a surge of interest in topology optimization as a means of designing high performance components with high degrees of geometrical complexity. Topology optimization seeks to find the best design for a structure by optimally distributing material in a design space. Therefore not only the shape and size of the structure, but also the connectivity of the structure changes during the topology optimization process. As a result, the solution of a topology optimization problem might be represented with a high degree of geometrical complexity as it is not dependent on the initial geometry. The finite element method (FEM) is a powerful numerical analysis technique that was developed to solve complex solid mechanics problems. Many topology optimization approaches use FEM to calculate the response of the structure during the optimization process and some of them, called “element based-methods”, are integrated with FEM to use the properties of finite elements as design variables in the optimization. The solutions of such approaches are usually represented by a uniform finite element mesh that bears no relation to the final geometry and hence they don’t provide an accurate representation of the design boundary. The solution from topology optimization must therefore go through further post processing stages to obtain a manufacturable design. The post processing stages which can include smoothing and shape optimization are costly and time-consuming and may result in the structure becoming less optimal. With traditional manufacturing processes this is acceptable as the manufacturing constraints prevent the optimized design from being manufactured so some re-analysis is necessary. With additive manufacturing, however, this restriction is removed, which means a topology optimization resulting in a manufacturable design is highly desirable. Evolutionary structural optimization (ESO) is an element based topology optimization approach which operates by systematically removing inefficient material from the structure until the optimization objective achieves convergence. Due to the intuitive nature of ESO, this method is simple to be programed and can be easily integrated with FEM or other numerical analysis techniques; thus it is suitable for complex geometries represented with FEM. During the last two decades ESO and its extensions, such as bi-directional ESO (BESO), have been successfully used for many topology optimization problems such as stiffness design, design of compliant mechanisms, heat conduction problems and frequency problems. However, being an element based method, the drawback of poor boundary representation remains. The extended finite element method (X-FEM) is an extension of the classical FEM that was developed to represent discontinuities, such as cracks and material-void interfaces, inside finite elements. X-FEM can be employed in topology optimization problems to handle the material-void discontinuity introduced by the evolving boundary during the optimization process which potentially enables a sub-element boundary representation. This requires an implicit boundary representation, such as level-set method with the benefits of better computational accuracy through the optimization, more optimized solution and smoother boundaries for direct to manufacture. In this work a new method of evolutionary structural optimization is proposed in which X-FEM is employed for the more smooth and accurate representation of the design boundary. Linear finite elements are used to discretize the design space. These include 4-node quadrilateral elements in 2D modelling and 8-node hexahedral elements in 3D modelling. To implement the X-FEM, an implicit boundary representation using isoline and isosurface approaches is used. The proposed method which is called “Iso-XFEM” is implemented for various topology optimization problems, including the stiffness design of 2D and 3D structures, stiffness design with additional displacement constraint and topology optimization of geometrically nonlinear problems. The solutions of the Iso-XFEM method are compared with those obtained using BESO, as a representative FE based method. The results confirm a significant improvement in boundary representation of the solutions when compared against BESO, and also demonstrate the feasibility of the application of the proposed method to complex real-life structures and to different objectives. All the programs used to generate topology optimised solutions using the proposed method and its modifications are developed by the author. These include topology optimization codes, linear and non-linear FEA, and 2D and 3D X-FEM integration schemes.
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Dater, Brian Scott. "Structural acoustic optimization of an aircraft fuselage using the complex method." Thesis, Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/17689.
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Cole, Bjorn Forstrom. "An evolutionary method for synthesizing technological planning and architectural advance." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29758.
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Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Mavris, Dimitri; Committee Member: Costello, Mark; Committee Member: German, Brian. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Aremu, Adedeji. "Topology optimization for additive manufacture." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/12833.
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Additive manufacturing (AM) offers a way to manufacture highly complex designs with potentially enhanced performance as it is free from many of the constraints associated with traditional manufacturing. However, current design and optimisation tools, which were developed much earlier than AM, do not allow efficient exploration of AM's design space. Among these tools are a set of numerical methods/algorithms often used in the field of structural optimisation called topology optimisation (TO). These powerful techniques emerged in the 1980s and have since been used to achieve structural solutions with superior performance to those of other types of structural optimisation. However, such solutions are often constrained during optimisation to minimise structural complexities, thereby, ensuring that solutions can be manufactured via traditional manufacturing methods. With the advent of AM, it is necessary to restructure these techniques to maximise AM's capabilities. Such restructuring should involve identification and relaxation of the optimisation constraints within the TO algorithms that restrict design for AM. These constraints include the initial design, optimisation parameters and mesh characteristics of the optimisation problem being solved. A typical TO with certain mesh characteristics would involve the movement of an assumed initial design to another with improved structural performance. It was anticipated that the complexity and performance of a solution would be affected by the optimisation constraints. This work restructured a TO algorithm called the bidirectional evolutionary structural optimisation (BESO) for AM. MATLAB and MSC Nastran were coupled to study and investigate BESO for both two and three dimensional problems. It was observed that certain parametric values promote the realization of complex structures and this could be further enhanced by including an adaptive meshing strategy (AMS) in the TO. Such a strategy reduced the degrees of freedom initially required for this solution quality without the AMS.
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Hambric, Stephen A. "Structural shape optimization of three dimensional finite element models." Thesis, Virginia Tech, 1987. http://hdl.handle.net/10919/45805.
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<p>The thesis presents a three dimensional shape optimization program which analyzes
models made up of linear isoparametric elements. The goal of the program is to achieve
a near uniform model stress state and thereby to minimize material volume.</p>
<p>
The algorithm is iterative, and performs two analyses per iteration. The first analysis
is a static stress analysis of the model for one or more load cases. Based on results
from the static analysis, an expansion analysis is performed. Model elements are expanded
or contracted based on whether they are stressed higher or lower than a reference
stress. The shape changing is done by creating an expansion load vector using the differences
between the calculated element stresses and the reference stress. Expansion
displacements are solved for, and instead of using them to calculate stresses, the displacements
are added to the nodal coordinates to reshape the structure. This process
continues until a user defined convergence tolerance is met.</p>
<p>
Four programs were used for the analysis process. Models were created using a finite
element modeling program called I-IDEAS or CAIEDS. The I-IDEAS output files
were converted to input files for the optimizer by a conversion program. The model was
optimized using the shape optimization process described above. Post- processing was
done using a program written with a graphical programming language called graPHIGS.</p>
<p>Models used to test the program were: a cylindrical pressure vessel with nonuniform
thickness, a spherical pressure vessel with non-uniform thickness, a torque arm, and a
draft sill casting o a railroad hopper car. Results were compared to similar studies from
selected references.</p>
<p>
Both pressure vessels converged to near uniform thicknesses, which compared ell
with the reference work. In a two dimensional analysis, the torque arm volume decreased
24 percent, which compared well with published results. A three dimensional
analysis showed a volume reduction of l3 percent, but there were convergence problems.
Finally, the draft sill casting was reduced in volume by 9 percent from a manually optimized
design.</p><br>Master of Science
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Korkut, Ahmet Esat. "A Practical Optimum Design Of Steel Structures With Scatter Search Method And Sap2000." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615682/index.pdf.
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In the literature, a large number of metaheuristic search techniques have been proposed up to present time and some of those have been used in structural optimization. Scatter search is one of those techniques which has proved to be effective when solving combinatorial and nonlinear optimization problems such as scheduling, routing, financial product design and other problem areas. Scatter search is an evolutionary method that uses strategies based on a composite decision rules and search diversification and intensification for generating new trial points. Broodly speaking, this thesis is concerned with the use and application of scatter search technique in structural optimization. A newly developed optimization algorithm called modified scatter search is modified which is computerized in a software called SOP2012. The software SOP2012 is integrated with well-known structural analysis software SAP2000 using application programming interface for size optimum design of steel structures. Numerical studies are carried out using a test suite consisting of five real size design examples taken from the literature. In these examples, various steel truss and frame structures are designed for minimum weight according to design limitations imposed by AISC-ASD (Allowable Stress Design Code of American Institute of Steel Construction). The results reveal that the modified scatter search technique is very effective optimization technique for truss structures, yet its performance can be assessed ordinary for frame structures.
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Sedaghati, Ramin. "Investigations in structural optimization of nonlinear problems using the finite element method." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0010/NQ52772.pdf.
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Ekren, Mustafa. "Structural Optimization Strategies Via Different Optimization And Solver Codes And Aerospace Applications." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12610250/index.pdf.
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In this thesis, structural optimization study is performed by using three different methods. In the first method, optimization is performed using MSC.NASTRAN Optimization Module, a commercial structural analysis program. In the second method, optimization is performed using the optimization code prepared in MATLAB and MSC.NASTRAN as the solver. As the third method, optimization is performed by using the optimization code prepared in MATLAB and analytical equations as the solver. All three methods provide certain advantages in the solution of optimization problems. Therefore, within the context of the thesis these methods are demonstrated and the interface codes specific to the programs used in this thesis are explained in detail. In order to compare the results obtained by the methods, the verification study has been performed on a cantilever beam with rectangular cross-section. In the verification study, the height and width of the cross-section of the beam are taken as the two design parameters. This way it has been possible to show the design space on the two dimensional graph, and it becomes easier to trace the progress of the optimization methods during each step. In the last section structural optimization of a multi-element wing torque box has been performed by the MSC.NASTRAN optimization module. In this section geometric property optimization has been performed for constant tip loading and variable loading along the wing span. In addition, within the context of shape optimization optimum rib placement problem has also been solved.
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Stewart, Eric C. "Shape and Structural Optimization of Flapping Wings." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/24808.
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This dissertation presents shape and structural optimization studies on flapping wings for micro air vehicles. The design space of the optimization includes the wing planform and the structural properties that are relevant to the wing model being analyzed. The planform design is parameterized using a novel technique called modified Zimmerman, which extends the concept of Zimmerman planforms to include four ellipses rather than two. Three wing types are considered: rigid, plate-like deformable, and membrane. The rigid wing requires no structural design variables. The structural design variables for the plate-like wing are the thickness distribution polynomial coefficients. The structural variables for the membrane wing control the in-plane distributed forces which modulate the structural deformation of the wing.
The rigid wing optimization is performed using the modified Zimmerman method to describe the wing. A quasi-steady aerodynamics model is used to calculate the thrust and input power required during the flapping cycle. An assumed inflow model is derived based on lifting-line theory and is used to better approximate the effects of the induced drag on the wing. A multi-objective optimization approach is used since more than one aspect is considered in flapping wing design. The the epsilon-constraint approach is used to calculate the Pareto optimal solutions that maximize the cycle-average thrust while minimizing the peak input power and the wing mass.
An aeroelastic model is derived to calculate the aerodynamic performance and the structural response of the deformable wings. A linearized unsteady vortex lattice method is tightly coupled to a linear finite element model. The model is cost effective and the steady-state solution is solved by inverting a matrix. The aeroelastic model is used to maximize the thrust produced over one flapping cycle while minimizing the input power.<br>Ph. D.
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Kim, Yong Yook. "Inverse Problems In Structural Damage Identification, Structural Optimization, And Optical Medical Imaging Using Artificial Neural Networks." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/11111.
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The objective of this work was to employ artificial neural networks (NN) to solve inverse problems in different engineering fields, overcoming various obstacles in applying NN to different problems and benefiting from the experience of solving different types of inverse problems. The inverse problems investigated are: 1) damage detection in structures, 2) detection of an anomaly in a light-diffusive medium, such as human tissue using optical imaging, 3) structural optimization of fiber optic sensor design. All of these problems require solving highly complex inverse problems and the treatments benefit from employing neural networks which have strength in generalization, pattern recognition, and fault tolerance. Moreover, the neural networks for the three problems are similar, and a method found suitable for solving one type of problem can be applied for solving other types of problems.
Solution of inverse problems using neural networks consists of two parts. The first is repeatedly solving the direct problem, obtaining the response of a system for known parameters and constructing the set of the solutions to be used as training sets for NN. The next step is training neural networks so that the trained neural networks can produce a set of parameters of interest for the response of the system. Mainly feed-forward backpropagation NN were used in this work.
One of the obstacles in applying artificial neural networks is the need for solving the direct problem repeatedly and generating a large enough number of training sets. To reduce the time required in solving the direct problems of structural dynamics and photon transport in opaque tissue, the finite element method was used. To solve transient problems, which include some of the problems addressed here, and are computationally intensive, the modal superposition and the modal acceleration methods were employed. The need for generating a large enough number of training sets required by NN was fulfilled by automatically generating the training sets using a script program in the MATLAB environment. This program automatically generated finite element models with different parameters, and the program also included scripts that combined the whole solution processes in different engineering packages for the direct problem and the inverse problem using neural networks.
Another obstacle in applying artificial neural networks in solving inverse problems is that the dimension and the size of the training sets required for the NN can be too large to use NN effectively with the available computational resources. To overcome this obstacle, Principal Component Analysis is used to reduce the dimension of the inputs for the NN without excessively impairing the integrity of the data. Orthogonal Arrays were also used to select a smaller number of training sets that can efficiently represent the given system.<br>Ph. D.
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Moodley, Kamlin. "A Proper Orthogonal Decomposition-based inverse material parameter optimization method with applications to cardiac mechanics." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/22777.
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We are currently witnessing the advent of a revolutionary new tool for biomedical research. Complex mathematical models of "living cells" are being arranged into representative tissue assemblies and utilized to produce models of integrated tissue and organ function. This enables more sophisticated simulation tools that allows for greater insight into disease and guide the development of modern therapies. The development of realistic computer models of mechanical behaviour for soft biological tissues, such as cardiac tissue, is dependent on the formulation of appropriate constitutive laws and accurate identification of their material parameters. The main focus of this contribution is to investigate a Proper Orthogonal Decomposition with Interpolation (PODI) based method for inverse material parameter optimization in the field of cardiac mechanics. Material parameters are calibrated for a left ventricular and bi-ventricular human heart model during the diastolic filling phase. The calibration method combines a MATLAB-based Levenberg Marquardt algorithm with the in-house PODIbased software ORION. The calibration results are then compared against the full-order solution which is obtained using an in-house code based on the element-free Galerkin method, which is assumed to be the exact solution. The results obtained from this novel calibration method demonstrate that PODI provides the means to drastically reduce computation time but at the same time maintain a similar level of accuracy as provided by the conventional approach.
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Bryson, Dean Edward. "A Unified, Multifidelity Quasi-Newton Optimization Method with Application to Aero-Structural Design." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1510146591195367.
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Jackson, Timothy W. "Design-oriented aeroservoelastic optimization of strain-actuated aircraft /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/9979.
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Kotani, Takayo. "Structural optimization of actuators and mechanisms considering electrostatic-structural coupling effects and geometric nonlinearity." 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/192185.
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Wei, Xiaofan. "Stochastic Analysis and Optimization of Structures." University of Akron / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=akron1163789451.
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Wei, Dong. "A univariate decomposition method for higher-order reliability analysis and design optimization." Diss., University of Iowa, 2006. http://ir.uiowa.edu/etd/55.
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Khoza, Dineo. "Topology optimization of plate-like structures." Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-04102007-185634.
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Mansour, Rami. "Reliability Assessment and Probabilistic Optimization in Structural Design." Doctoral thesis, KTH, Hållfasthetslära (Avd.), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-183572.
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Research in the field of reliability based design is mainly focused on two sub-areas: The computation of the probability of failure and its integration in the reliability based design optimization (RBDO) loop. Four papers are presented in this work, representing a contribution to both sub-areas. In the first paper, a new Second Order Reliability Method (SORM) is presented. As opposed to the most commonly used SORMs, the presented approach is not limited to hyper-parabolic approximation of the performance function at the Most Probable Point (MPP) of failure. Instead, a full quadratic fit is used leading to a better approximation of the real performance function and therefore more accurate values of the probability of failure. The second paper focuses on the integration of the expression for the probability of failure for general quadratic function, presented in the first paper, in RBDO. One important feature of the proposed approach is that it does not involve locating the MPP. In the third paper, the expressions for the probability of failure based on general quadratic limit-state functions presented in the first paper are applied for the special case of a hyper-parabola. The expression is reformulated and simplified so that the probability of failure is only a function of three statistical measures: the Cornell reliability index, the skewness and the kurtosis of the hyper-parabola. These statistical measures are functions of the First-Order Reliability Index and the curvatures at the MPP. In the last paper, an approximate and efficient reliability method is proposed. Focus is on computational efficiency as well as intuitiveness for practicing engineers, especially regarding probabilistic fatigue problems where volume methods are used. The number of function evaluations to compute the probability of failure of the design under different types of uncertainties is a priori known to be 3n+2 in the proposed method, where n is the number of stochastic design variables.<br><p>QC 20160317</p>
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Good, Matthew G. "Development of a Variable Camber Compliant Aircraft Tail using Structural Optimization." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/33976.
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The objectives of the research presented in this thesis are the development of a seven degree-of-freedom morphing airplane and the design and integration of a variable camber compliant tail. The morphing airplane was designed and manufactured to study the benefits of large planform changes and flight control morphing. Morphing capabilities of each wing consist of 8 in. wing extension and contraction, 40° of wing sweep and ±20.25° of outboard wing twist in addition to 6 in. of tail extension and contraction. Initial wind-tunnel tests proved that for a large range of lift coefficients, the optimal airplane configuration changes to minimize the drag.
Another portion of this research deals with the development of a structural optimization program to design a variable camber compliant tail. The program integrates ANSYS, aerodynamic thin airfoil theory and the Method of Moving Asymptotes to optimize the shape of an airfoil tail for maximum trailing edge deflection. An objective function is formulated to maximize the trailing edge tip deflection subject to stress constraints. The optimal structure needs to be flexible to maximize the tip deflection, but stiff enough to minimize the deflection of the tip due to aerodynamic loading. The results of the structural optimization program created a compliant tail mechanism that can deflect the trailing edge tip with a single actuator ±4.27°.<br>Master of Science
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King, Jacob Michael B. "A Method for Visualizing the Structural Complexity of Organizational Architectures." DigitalCommons@CalPoly, 2021. https://digitalcommons.calpoly.edu/theses/2266.
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To achieve a high level of performance and efficiency, contemporary aerospace systems must become increasingly complex. While complexity management traditionally focuses on a product’s components and their interconnectedness, organizational representation in complexity analysis is just as essential. This thesis addresses this organizational aspect of complexity through an Organizational Complexity Metric (OCM) to aid complexity management. The OCM augments Sinha’s structural complexity metric for product architectures into a metric that can be applied to organizations. Utilizing nested numerical design structure matrices (DSMs), a compact visual representation of organizational complexity was developed. Within the nested numerical DSM are existing organizational datasets used to quantify the complexity of both organizational system components and their interfaces. The OCM was applied to a hypothetical system example, as well as an existing aerospace organizational architecture. Through the development of the OCM, this thesis assumed that each dataset was collected in a statistically sufficient manner and has a reasonable correlation to system complexity. This thesis recognizes the lack of complete human representation and aims to provide a platform for expansion. Before a true organizational complexity metric can be applied to real systems, additional human considerations should be considered. These limitations differ from organization to organization and should be taken into consideration before implementation into a working system. The visualization of organizational complexity uses a color gradient to show the relative complexity density of different parts of the organization.
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Smith, Richard A. "Structural analysis and optimization of the support device used for a proximal fracture of the femur." Thesis, Monterey, Calif. : Naval Postgraduate School, 2008. http://edocs.nps.edu/npspubs/scholarly/theses/2008/Dec/08Dec%5FSmithR.pdf.
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Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, December 2008.<br>Thesis Advisor(s): Kwon, Young W. "December 2008." Description based on title screen as viewed on January 30, 2009. Includes bibliographical references (p. 67-68). Also available in print.
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Noguchi, Yuki. "An optimum structural design methodology for acoustic metamaterials using topology optimization." Kyoto University, 2019. http://hdl.handle.net/2433/242492.
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Long, Craig Stephen. "Finite element developments and applications in structural topology optimization." Thesis, University of Pretoria, 2007. http://upetd.up.ac.za/thesis/available/etd-05062008-123415/.
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Neogi, Sudipto. "Design of large composite structures using global optimization and finite element analysis /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/7082.
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Dasari, Saaranya Kumar. "Computational morphogenesis of spatial structures by structural optimization using finite element method and a genetic algorithm." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
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This thesis focuses on computational design techniques that incorporate structural considerations in the early stages of the architectural design process. Since structural behavior is most affected by geometric form and problems are mainly associated with the complexity of their design process in the early conceptual design.
This research conceptual structure is based on complex interactions between architectural forms and the functionality of the design. Starting from the complex problems that arise from non-standard architecture, free form, and other specific constructive aspects. This highlights the most important consequences of free form and the complexity of design evolution and uses them to develop a typology of design complexity and explores the contribution of how computational technologies and design strategies enable us to address complexity with the help of advancements.
For a better understanding of computational complexity and mechanisms that take part in conceptual design processing, and a thorough search for structural efficiency to solve a more complex issue than reality and achieve an original solution through direct search method of optimization using mathematic–mechanical modeling operations with the aid of computer models/simulations. These models address how complex systems are formed, how they evolve, and how they can break down. The interdisciplinary scientific approach is concerned with theoretical studies of real-world engineering design to understand the relationship between architectures (topologies) and dynamics and to evaluate structural systems with physical and geometrical nonlinearities with which to explain how the concept of architectonic is continuously transformed within contingent, complex, and dynamic structural design practices as buildings materialize.
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Schön, Sofia. "Design Space Exploration for Structural Aircraft Components : A method for using topology optimization in concept development." Thesis, Linköpings universitet, Maskinkonstruktion, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-159955.
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When building aircrafts, structural components must be designed for high strength, low cost, and easy assembly.To meet these conditions structural components are often based upon previous designs, even if a new component is developed.Refining previous designs can be a good way of preserving knowledge but can also limit the exploration of new design concepts. Currently the design process for structural aircraft components at SAAB is managed by design engineers. The design engineer is responsible for ensuring the design meets requirements from several different disciplines such as structural analysis, manufacturing, tool design, and assembly.Therefore, the design engineer needs to have good communication with all disciplines and an effective flow of information. The previous design is refined, it is then reviewed and approved by adjacent disciplines.Reviewing designs is an iterative process, and when several disciplines are involved it quickly becomes time consuming.Any time the design is altered it has to be reviewed once more by all disciplines to ensure the change is acceptable.So there is a need for further customizing the design concept to decrease the number of iterations when reviewing. Design Space Exploration DSE is a well known method to explore design alternatives before implementation and is used to find new concepts.This thesis investigates if DSE can be used to facilitate the design process of structural aircraft components and if it can support the flow of information between different disciplines.To find a suitable discipline to connect with design a prestudy is conducted, investigating what information affect structural design and how it is managed.The information flow is concluded in a schematic diagram where structural analysis is chosen as additional discipline. By using topology optimization in a DSE, design and structural analysis are connected.The design space can be explored with regards to structural constraints.The thesis highlights the possibilities of using DSE with topology optimization for developing structural components and proposes a method for including it in the design process.
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Long, Craig Stephen. "Optimal structural design for a planar parallel platform for machining." Diss., Pretoria : [S.n], 2002. http://upetd.up.ac.za/thesis/available/etd-11302005-093541/.
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Solat, Yavari Majid. "Slab Frame Bridges : Structural Optimization Considering Investment Cost and Environmental Impacts." Licentiate thesis, KTH, Bro- och stålbyggnad, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-202948.
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This research encompasses the automated design and structural optimization of reinforced concrete slab frame bridges, considering investment costs and environmental impacts. The most important feature of this work is that it focusses on realistic and complete models of slab frame bridges rather than on optimization of only individual members or sections of a bridge. The thesis consists of an extended summary of publications and three appended papers. In the first paper, using simple assumptions, the possibility of applying cost-optimization to the structural design of slab frame bridges was investigated. The results of the optimization of an existing constructed bridge showed the potential to reduce the investment cost of slab frame bridges. The procedure was further developed in the second paper. In this paper, automated design was integrated to a more refined cost-optimization methodology based on more detailed assumptions and including extra constructability factors. This procedure was then applied to a bridge under design, before its construction. From the point of view of sustainability, bridge design should not only consider criteria such as cost but also environmental performance. The third paper thus integrated life cycle assessment (LCA) with the design optimization procedure to perform environmental impact optimization of the same case study bridge as in the second paper. The results of investment cost and environmental impact optimization were then compared. The obtained results presented in the appended papers highlight the successful application of optimization techniques to the structural design of reinforced concrete slab frame bridges. Moreover, the results indicate that a multi-objective optimization that simultaneously considers both environmental impacts and investment cost is necessary in order to generate more sustainable designs. The presented methodology has been applied to the design process for a time-effective, sustainable, and optimal design of concrete slab frame bridges.<br><p>QC 20170316</p>
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Zuo, Zihao, and Zhihao zuo@rmit edu au. "Topology optimization of periodic structures." RMIT University. Civil, Environmental and Chemical Engineering, 2009. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20091217.151415.
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This thesis investigates topology optimization techniques for periodic continuum structures at the macroscopic level. Periodic structures are increasingly used in the design of structural systems and sub-systems of buildings, vehicles, aircrafts, etc. The duplication of identical or similar modules significantly reduces the manufacturing cost and greatly simplifies the assembly process. Optimization of periodic structures in the micro level has been extensively researched in the context of material design, while research on topology optimization for macrostructures is very limited and has great potential both economically and intellectually. In the present thesis, numerical algorithms based on the bi-directional evolutionary structural optimization method (BESO) are developed for topology optimization for various objectives and constraints. Soft-kill (replacing void elements with soft elements) formulations of topology optimization problems for solid-void solutions are developed through appropriate material interpolation schemes. Incorporating the optimality criteria and algorithms for mesh-independence and solution-convergence, the present BESO becomes a reliable gradient based technique for topology optimization. Additionally, a new combination of genetic algorithms (GAs) with BESO is developed in order to stochastically search for the global optima. These enhanced BESO algorithms are applied to various optimization problems with the periodicity requirement as an extra constraint aiming at producing periodicity in the layout. For structures under static loading, the present thesis addresses minimization of the mean compliance and explores the applications of conventional stiffness optimization for periodic structures. Furthermore, this thesis develops a volume minimization formulation where the maximum deflection is constrained. For the design of structures subject to dynamic loading, this thesis develops two different approaches (hard-kill and soft-kill) to resolving the problem of localized or artificial modes. In the hard-kill (completely removing void elements) approach, extra control measures are taken in order to eliminate the localized modes in an explicit manner. In the soft-kill approach, a modified power low material model is presented to prevent the occurrence of artificial and localized modes. Periodic stress and strain fields cannot be assumed in structures under arbitrary loadings and boundaries at the macroscopic level. Therefore being different from material design, no natural base cell can be directly extracted from macrostructures. In this thesis, the concept of an imaginary representative unit cell (RUC) is presented. For situations when the structure cannot be discretized into equally-sized elements, the concept of sensitivity density is developed in order for mesh-independent robust solutions to be produced. The RUC and sensitivity density based approach is incorporated into various topology optimization problems to obtain absolute or scaled periodicities in structure layouts. The influence of this extra constraint on the final optima is investigated based on a large number of numerical experiments. The findings shown in this thesis have established appropriate techniques for designing and optimizing periodic structures. The work has provided a solid foundation for creating a practical design tool in the form of a user-friendly computer program suitable for the conceptual design of a wide range of structures.
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Wang, Jia-Pei, and 王嘉霈. "Bi-Directional Evolutionary Structural Optimization Method with Manufacturing Constraints." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/03878699735264560871.
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碩士<br>國立臺灣大學<br>機械工程學研究所<br>101<br>This thesis proposes a modified bi-directional evolutionary structural optimization (BESO) method which combines a modified filter scheme and a modified element removal/addition criterion for evolution ratio dependence problem and manufacturing constraints. Instead of selecting a fixed length of filter radius, the modified filter scheme decreases the length of filter radius through the evolution process. Such modification contributes to the suppression of evolution ratio dependence problem, and therefore enhances the stability of BESO method. On the other hand, draw direction constraints, defined by required manufacturing process, are achieved by modifying the element removal/addition criterion. Modified element removal/addition criterion gradually removes elements from top surface of the draw direction to the inner design domain. The optimal designs with draw direction constraints are free from hollow or closed cavity geometries which are infeasible for manufacturing, and therefore the practicability of BESO method is enhanced. A structural topology optimization program which combines the proposed modified BESO method and ANSYS is developed. The results prove the validity and practicability of the proposed modifications in structural topology optimization.
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Nguyen, Dang Quang. "Extended evolutionary structural optimization method for multi-storey buildings." Thesis, 2001. https://vuir.vu.edu.au/18198/.
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This study extends the Evolutionary Structural Optimization (ESO) method for
application to multi-storey buildings. The objective is to find the optimal
topologies of multi-storey buildings subject to overall stiffness or displacement
constraints. It emphasizes the derivation of a methodology to help the structural
designers to choose the optimal topology among many topologies that are
generated during the evolutionary optimization process. Other problems of the
ESO method such as the termination condition, sharp change in structural mean
compliance or constrained displacements are also investigated.
The new added features provide the ESO method with the capability of dealing
with structures containing different types of finite elements. For the structure
being considered, only continuum elements are allowed to be removed during
the optimization process while beam elements are assumed to be fixed and are
referred to as a non-design domain. By having all the topologies with the same
weight as the initial structure, the performance of these topologies can be
evaluated by comparing the mean compliance or constrained displacements.
The results of this study show the extended ESO method can effectively find
efficient bracing systems for multi-storey buildings.
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Chu, Duc Nha. "Evolutionary structural optimization method for systems with stiffness and displacement constraints." Thesis, 1997. https://vuir.vu.edu.au/15282/.
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This thesis presents the development of an evolutionary method for optimization of stmctures subject to displacement and stiffness constraints. Using an optimality
criteria approach, the study provides a rigorous mathematical basis to the recently proposed evolutionary stmctural optimization (ESO) method. New types of
sensitivity numbers for element removal have been formulated from the optimality conditions of the general weight minimization problem. The optimal shape and
topology of a structure is obtained by repeated finite element analysis and element removal until the sensitivity numbers become uniform by which the optimality
conditions are satisfied, or no further improvement in the objective can be achieved. It is shown that the method can be applied to other constraints on generalized
displacements, stiffness, stress and frequency. Investigations on various aspects of the proposed method have been carried out to show its validity and efficiency for shape and topology optimization.
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Manickarajah, Dhayanthi. "Optimum design of structures with stability constraints using the evolutionary optimisation method." Thesis, 1998. https://vuir.vu.edu.au/15258/.
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In the past most of the works on structural optimisation have been based on either mathematical programming or optimality criteria methods and have mainly concentrated on static responses of structures. These optimisation methods are mathematically complex and have limited applications. A novel approach to structural optimisation is being developed for practical applications based on the concept of
slowly removing the inefficient material or gradually shifting the material from the strongest part of the structure to the weakest part until the structure evolves towards the desired optimum. From the results of finite element analysis, the contribution of each element to the required structural response may be assessed. Based on this assessment, material is gradually shifted or removed in the design domain. In doing so optimum designs can be easily achieved without resorting to any complex mathematics. This
optimisation procedure is called Evolutionary Structural Optimisation (ESO). This project examines the suitability of the ESO for the design of structures with buckling constraints.
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Gonçalves, Filipe Assis. "Introduction to Structural Optimization using the ESO and BESO Evolutionary Methods." Master's thesis, 2018. https://repositorio-aberto.up.pt/handle/10216/116442.
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Gonçalves, Filipe Assis. "Introduction to Structural Optimization using the ESO and BESO Evolutionary Methods." Dissertação, 2018. https://repositorio-aberto.up.pt/handle/10216/116442.
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Yang, Xiaoying. "Bi-directional evolutionary method for stiffness and displacement optimisation." Thesis, 1999. https://vuir.vu.edu.au/18230/.
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This thesis presents a method for structural optimisation called bi-directional
evolutionary structural optimisation (BESO). It is an extension of the systematic
research on the evolutionary method. The basic concept of evolutionary structural
optimisation (ESO) is that by slowly removing the inefficient material, the structure
evolves towards an optimum. BESO extends the concept by allowing for the efficient
material to be added while the inefficient material is removed. The formulation of
BESO is motivated to improve the reliability and efficiency of the ESO method.
The BESO method for topological optimisation of 2D continua subject to stiffness and
displacement constraints is the major task of this thesis. The theoretical aspects are
explored by following the optimality criteria algorithm for problems of discrete design
variables. These aspects include the optimality criteria, sensitivity analysis,
displacement extrapolation and evolutionary procedure. The bi-directional evolutionary
procedure is incorporated with the finite element analysis to realise an automatic
optimisation process.
A wide range of examples are tested by using the proposed BESO procedure. Different
design conditions are considered including stiffness optimisation and single or multiple
displacement optimisation under single and multiple loading conditions. The solution
reliability and parametric effect are further studied to improve the BESO performance.
The comparison of results by BESO and ESO are attempted and the satisfactory
agreement demonstrates the validity of the proposed procedure. Two major conclusions
are derived from the work in this thesis. The first one is that BESO is as effective as
ESO, and the second one is that BESO can be computationally more efficient in most
cases.
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HUANG, PIN-JUI, and 黃品睿. "The Preliminary Study on Three-dimensional Isothermal Forging Preform Design by using Bi-directional Evolutionary Structural Optimization Method." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/29172400858836011758.
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碩士<br>國立高雄應用科技大學<br>機械工程系<br>105<br>Preform is an intermediate shape between blanking and the final product. Preform design and optimization would affect the forming loads, material flow, tool wear and dimensional accuracy. Thus, the investigations of design and optimization of the preforming stage plays an important role in the metal forming process. The traditional topology optimization method is used in the field of structure design, in which little deformation is involved. However, the metal forming process behaves a large amount of plastic deformation, in which the mesh distortion occurs in the simulation process. Therefore, introducing the topology optimization into the metal forming process is a big challenge.
In this study, the analysis and simulation software are carried out by using the DEFORM-3D finite element software as well as CAD software and MATLAB software as auxiliary tools. The research procedures are separated into three steps. First, using the point tracking to design the preform, and check the volume loss and flow line after the simulation. The second part, type 1 (initial design) preform design is used to simulate the isothermal hot forging process for producing a disk with concentric shaft and eccentric shaft, and design the type 2 preform which is based on material filling condition and then conduct forging process simulation again. Finally, conduct the type 3 preform design which is based on material flow condition.
The simulation results show that the volume loss of the first simulation is 0.3904%, and the volume loss of the second simulation is 0.6433%, through the flow line and forging products are found surface defects on the eccentric shaft and concentric shaft. The simulation result of type 1 preform design depicts under filled condition at bottom of concentric shaft. The material volume is increased as preform design of type 2 to fix the under filled problem. In order to improve the condition of material flow distribution by increasing the material volume at eccentric shaft, as shown in the preform design type 3. The simulation result of the type 3 and the forged product are quite similar. In this research, the establishment of three dimensional background mesh and the points tracking data analysis are carried out by MATLAB software in order to perform the automatic preform design.