To decrease the computational cost of genetic algorithm optimizations, surrogate models are used during optimization. Online update of surrogate models and repeated exchange of surrogate models with exact model during genetic optimization converts static optimization problems to dynamic ones. However, genetic algorithms fail to converge to the global optimum in dynamic optimization problems. To address these problems, a multiploid genetic algorithm optimization method is proposed. Multi-fidelity surrogate models are assigned to corresponding levels of fitness values to sustain the static optimization problem. Low fidelity fitness values are used to decrease the computational cost. The exact/highest-fidelity model fitness value is used for converging to the global optimum. The algorithm is applied to single and multi-objective turbine blade aerodynamic optimization problems. The design objectives are selected as maximizing the adiabatic efficiency and torque so as to reduce the weight, size and the cost of the gas turbine engine. A 3-D steady Reynolds-Averaged Navier-Stokes solver is coupled with an automated unstructured grid generation tool. The solver is validated by using two well known test cases. Blade geometry is modelled by 37 design variables. Fine and coarse grid solutions are respected as high and low fidelity surrogate models, respectively. One of the test cases is selected as the baseline and is modified in the design process. The effects of input parameters on the performance of the multiploid genetic algorithm are studied. It is demonstrated that the proposed algorithm accelerates the optimization cycle while providing convergence to the global optimum for single and multi-objective problems.

In industrial quality improvement and design studies, an important aim is to improve the product or process quality by determining factor levels that would result in satisfactory quality results. In these studies, quality characteristics that are qualitative are often encountered. Although there are many effective methods proposed for parameter optimization (robust design) with continuous responses, the methods available for qualitative responses are limited. In this study, a parameter optimization method for solving binary response robust design problems is proposed. The proposed method uses Mahalanobis Taguchi System to form a classification model that provides a distance function to separate the two response classes. Then, it finds the product/process variable settings that minimize the distance from the desired response class using quadratic programming. The proposed method is applied on two cases previously studied using Logistic Regression. The classification models are formed and the parameter optimization is conducted using the formed MTS models. The results are compared with those of the Logistic Regression. Conclusions and suggestions for future work are given.

This thesis gives a comprehensive study on the effect of using different structural idealizations on the design, analysis and optimization of thin walled semi-monocoque wing structures in the preliminary design phase. In the design part, wing structures are designed by employing two different structural idealizations that are typically used in the preliminary design phase. In the structural analysis part, finite element analysis of one of the designed wing configurations is performed using six different one and two dimensional element pairs which are typically used to model the sub-elements of semi-monocoque wing structures. The effect of using different finite element types on the analysis results of the wing structure is investigated. During the analysis study, depending on the mesh size used, conclusions are also inferred with regard to the deficiency of certain element types in handling the true external load acting on the wing structure. Finally in the optimization part, wing structure is optimized for minimum weight by using finite element models which have the same six different element pairs used in the analysis phase. The effect of using different one and two dimensional element pairs on the final optimized configurations of the wing structure is investigated, and conclusions are inferred with regard to the sensitivity of the optimized wing configurations with respect to the choice of different element types in the finite element model. Final optimized wing structure configurations are also compared with the simplified method based designs which are also optimized iteratively. Based on the results presented in the thesis, it is concluded that with the simplified methods, preliminary sizing of the wing structures can be performed with enough confidence, as long as the simplified method based designs are also optimized. Results of the simplified method of analysis showed that simplified method is applicable to be used as an analysis tool in performing the preliminary sizing of the wing structure before moving on to more refined finite element based analysis.

Rapid urbanization and population growth have represented a great challenge to water resources management, since wastewater generated in urban areas forms a non-conventional source, wastewater reuse is being recognized as a sustainable water management approach. This study focuses on with the potential and practibility of implementing wastewater reuse techniques in Izmir region, especially with the aim to use treated wastewater and nutrient for agriculture. To this end, qualititative and quantitative agricultural water demand were considered. This thesis introduces a wastewater reuse planning model and optimization method with an emphasis on the wastewater treatment technology used as well as the agricultural demand in the area of the study. The model was developed with considerations over water quality, wastewater treatment and discharge. The objective of the model is to upgrade existing wastewater treatment plants or to design new treatment plants in regard to reuse wastewater in agriculture. The model is also capable of comparing treatment technologies from the point of design and cost. Three case studies were represented so as to demonstrate the modeling process and optimization studies for agricultural irrigation.

The law of bone remodeling, commonly referred to as Wolff's Law, asserts that the internal trabecular bone adapts to external loadings, reorienting with the principal stress trajectories to maximize mechanical efficiency, thereby creating a naturally optimum structure. The primary objective of the research was to utilize an advanced structural optimization algorithm, called design space optimization (DSO), to create a numerical framework to perform a micro-level three-dimensional finite element bone remodeling simulation on the human proximal femur and analyze the results to determine the validity of Wolff's hypothesis. DSO optimizes the layout of material by iteratively distributing it into the areas of highest loading, while simultaneously changing the design domain to increase computational efficiency. The result is a "fully stressed" structure with minimized compliance and increased stiffness. The large-scale computational simulation utilized a 175µm mesh resolution and the routine daily loading activities of walking and stair climbing. The resulting anisotropic human trabecular architecture was compared to both Wolff's trajectory hypothesis and natural femur data from the literature using a variety of visualization techniques, including radiography and computed tomography (CT). The remodeling predictions qualitatively revealed several anisotropic trabecular regions comparable to the natural human femurs. Quantitatively, the various regional bone volume fractions from the computational results were consistent with CT analyses. The strain energy proceeded to become more uniform during optimization; implying increased mechanical efficiency was achieved. The realistic simulated trabecular geometry suggests that the DSO method can accurately predict three-dimensional bone adaptation due to mechanical loading and that the proximal femur is an optimum structure as Wolff hypothesized. The secondary objective was to revise this computational framework to perform the first in-silico hip replacement considering micro-level bone remodeling. Two different commercially available hip prostheses were quantitatively analyzed using stress, strain energy, and bone mineral density as performance criteria and qualitatively visualized using the techniques above. Several important factors for stable fixation, determined from clinical evaluations, were evident: high levels of proximal bone loss, distal bone growth, and medial densification. The results suggest the DSO method can be utilized for comparative prosthetic implant stem design, uniquely considering post-operation bone remodeling as a design criterion. / Thesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2010-08-16 15:30:55.144

The main goal of this thesis is the development of a novel methodology to generate creative solutions at functional level for design tasks without binding solution spaces with designers&rsquo / individual experiences and prejudices. For this purpose, an evolutionary methodology for the conceptual design of engineering products has been proposed. This methodology performs evaluation, combination and modification of the existing solutions repetitively to generate new solution alternatives. Therefore, initially a representation scheme, which is generic enough to cover all alternatives in solution domain, has been defined. Following that, the evolutionary operations have been defined and two evaluation metrics have been proposed. Finally, the computer implementation of the developed theory has been performed. The test-runs of developed software resulted in creative alternatives for the design task. Consequently, the evolutionary design methodology presents a systematic design approach for less experienced or inexperienced designers and establishes a base for experienced designers to conceive many other solution alternatives beyond their experiences.

Optimization theory is a key technology for inverse problems of reconstruction in science, engineering and economy. Discrete tomography is a modern research field dealing with the reconstruction of finite objects in, e.g., VLSI chip design, where this thesis will focus on. In this work, a framework with its supplementary algorithms and a new problem reformulation are introduced to approximately resolve this NP-hard problem. The framework is modular, so that other reconstruction methods, optimization techniques, optimal experimental design methods can be incorporated within. The problem is being revisited with a new optimization formulation, and interpretations of known methods in accordance with the framework are also given. Supplementary algorithms are combined or incorporated to improve the solution or to reduce the cost in terms of time and space from the computational point of view.

Absorvedores de vibração são comumente usados em aplicações com intuito de reduzir indesejadas amplitudes de vibração de estruturas e maquinas vibrantes. O conceito de um absorvedor de vibração linear consiste na ideia de projetar um subsistema com frequência de ressonância coincidente com uma dada frequência de interesse, tal que a amplitude de vibração do sistema primário e significativamente reduzida quando comparada a situação original, sem o absorvedor de vibração. Porem, uma deficiência dos absorvedores de vibração lineares típicos e sua estreita faixa de frequência de operação. Para superar essa deficiência, muitas tentativas de solução usando subsistemas não lineares tem sido propostas na literatura, ja que se apropriadamente projetados, eles podem aumentar a faixa de frequência de absorção de vibração e/ou melhorar a redução das amplitudes de vibração do sistema primário. Contudo, a síntese e o projeto de tais absorvedores não lineares não e tão simples e direta como no caso linear. Baseado na geometria de uma topologia proposta e encontrada na literatura, que compreende a inclusão de uma montagem do tipo snap through truss no lugar da mola linear do absorvedor de vibração, este trabalho tem intenção de apresentar um estudo sobre o projeto e otimização de um absorvedor dinâmico de vibrações não linear. Portanto, o efeito dos parâmetros do absorvedor e analisado quanto as perspectivas de redução das amplitudes de vibração do sistema principal como também de aumento da faixa de frequência de operação. A analise paramétrica do absorvedor foi promovida para responder questões sobre as variáveis de projeto, tanto físicas como geométricas. Realizou-se otimização do absorvedor com objetivo de sintoniza-lo a frequência de trabalho desejada, através de busca extensiva e algoritmos genéticos. Os resultados mostram que o absorvedor não linear proposto pode ser mais efetivo que seu correspondente linear em ambos os aspectos, na redução da máxima amplitude de vibração e no aumento da faixa de frequência de absorção. Portanto, apesar da dificuldade inicial de projeto, esse tipo de absorvedor representa uma alternativa interessante na atenuação das amplitudes de vibração ao longo de uma extensa faixa de frequência. / Dynamic vibration absorbers are commonly used in several applications in order to reduce undesired vibration amplitudes of vibrating machinery and structures. The concept of a linear vibration absorber is based on the idea of designing a subsystem with a resonance frequency coincident with a given frequency of interest such that the vibration amplitude of the primary system is significantly reduced when compared to the original situation (without the vibration absorber). But one of the known handicaps of typical linear vibration absorbers is their narrow frequency range of operation. To overcome this handicap, a number of tentative solutions have been proposed in the literature using nonlinear subsystems. If properly designed, they could enlarge the frequency range of vibration absorption and/or improve vibration reduction of the primary system. However, the synthesis and design of such nonlinear absorbers are not as straightforward as for their linear counterpart. A proposed design found in the open literature consists of replacing the linear spring of the vibration absorber by a nonlinear snap-through truss. This work aims to present a study on the design and optimization of a nonlinear dynamic vibration absorber based on snap-through absorber geometry. The effect of the absorber parameters was analyzed on both, the primary system vibration amplitude reduction and the frequency range of operation. Parametric analyses of the absorber were carried out to answer questions about the physical and geometric design variables. The absorber optimization was performed in two different ways, by extensive search and genetic algorithms, in order to tune it in the desired working frequency. The results show that the proposed nonlinear vibration absorber may be more effective than its linear counterpart both in terms of maximum vibration amplitude reduction and absorption frequency-range. Therefore, despite the increased design complexities such an absorber is an interesting alterna- tive in attenuating vibration amplitudes over a wide frequency range.

The dissertation focuses on one of the major research needs in the area of adaptive /intelligent/smart structures, the development and application of finite element analysis and genetic algorithms for optimal design of large-scale adaptive structures. We first review some basic concepts in finite element method and genetic algorithms, along with the research on smart structures. Then we propose a solution methodology for solving a critical problem in the design of a next generation of large-scale adaptive structures -- optimal placements of a large number of actuators to control thermal deformations. After briefly reviewing the three most frequently used general approaches to derive a finite element formulation, the dissertation presents techniques associated with general shell finite element analysis using flat triangular laminated composite elements. The element used here has three nodes and eighteen degrees of freedom and is obtained by combining a triangular membrane element and a triangular plate bending element. The element includes the coupling effect between membrane deformation and bending deformation. The membrane element is derived from the linear strain triangular element using Cook's transformation. The discrete Kirchhoff triangular (DKT) element is used as the plate bending element. For completeness, a complete derivation of the DKT is presented. Geometrically nonlinear finite element formulation is derived for the analysis of adaptive structures under the combined thermal and electrical loads. Next, we solve the optimization problems of placing a large number of piezoelectric actuators to control thermal distortions in a large mirror in the presence of four different thermal loads. We then extend this to a multi-objective optimization problem of determining only one set of piezoelectric actuator locations that can be used to control the deformation in the same mirror under the action of any one of the four thermal loads. A series of genetic algorithms, GA Version 1, 2 and 3, were developed to find the optimal locations of piezoelectric actuators from the order of 10<SUP>21</SUP> ~ 10<SUP>56</SUP> candidate placements. Introducing a variable population approach, we improve the flexibility of selection operation in genetic algorithms. Incorporating mutation and hill climbing into micro-genetic algorithms, we are able to develop a more efficient genetic algorithm. Through extensive numerical experiments, we find that the design search space for the optimal placements of a large number of actuators is highly multi-modal and that the most distinct nature of genetic algorithms is their robustness. They give results that are random but with only a slight variability. The genetic algorithms can be used to get adequate solution using a limited number of evaluations. To get the highest quality solution, multiple runs including different random seed generators are necessary. The investigation time can be significantly reduced using a very coarse grain parallel computing. Overall, the methodology of using finite element analysis and genetic algorithm optimization provides a robust solution approach for the challenging problem of optimal placements of a large number of actuators in the design of next generation of adaptive structures. / Ph. D.

Approved for public release, distribution is unlimited / Numerous optimization problems involve systems with multiple and often contradictory criteria. Such contradictory criteria have been an issue for marine/naval engineering design studies for many years. This problem becomes more important when one considers novel ship types with very limited or no operational record. A number of approaches have been proposed to overcome these multiple criteria design optimization problems. This Thesis follows the Parameter Space Investigation (PSI) technique to address these problems. The PSI method is implemented with a software package called MOVI (Multi-criteria Optimization and Vector Identification). Two marine/naval engineering design optimization models were investigated using the PSI technique along with the MOVI software. The first example was a bulk carrier design model which was previously studied with other optimization methods. This model, which was selected due to its relatively small dimensionality and the availability of existing studies, was utilized in order to demonstrate and validate the features of the proposed approach. A more realistic example was based on the "MIT Functional Ship Design Synthesis Model" with a greater number of parameters, criteria, and functional constraints. A series of optimization studies conducted for this model demonstrated that the proposed approach can be implemented in a naval ship design environment and can lead to a large design parameter space exploration with minimum computational effort. / Lieutenant Junior Grade, Turkish Navy