Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-04-28T17:57:49Z No. of bitstreams: 1 erasmotalesfonseca.pdf: 866120 bytes, checksum: 042a0c3210df8046171b1593162cde44 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-05-02T01:13:24Z (GMT) No. of bitstreams: 1 erasmotalesfonseca.pdf: 866120 bytes, checksum: 042a0c3210df8046171b1593162cde44 (MD5) / Made available in DSpace on 2016-05-02T01:13:24Z (GMT). No. of bitstreams: 1 erasmotalesfonseca.pdf: 866120 bytes, checksum: 042a0c3210df8046171b1593162cde44 (MD5) Previous issue date: 2015-11-06 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Neste trabalho apresentamos um estudo da influência dos parâmetros de um algoritmo de pontos interiores e direções viáveis para solução de problemas de otimização não linear. Esse algoritmo, denominado FDIPA, tem por objetivo encontrar dentre os pontos de um conjunto definido por restrições de igualdade e/ou desigualdade, aqueles que minimizam uma função diferenciável. O FDIPA baseia-se na resolução de dois sistemas de equações lineares com a mesma matriz de coeficientes, obtidos das condições necessárias de primeira ordem de Karush-Kuhn-Tucker. A partir de um ponto inicial no interior do conjunto viável, o FDIPA gera uma sequência de pontos também interiores ao conjunto. Em cada iteração, uma nova direção de descida é obtida e, em seguida, produz-se uma deflexão da direção de descida no sentido do interior do conjunto viável, de modo a se obter uma nova direção que seja de descida e viável. Realiza-se então uma busca linear para obter um novo ponto interior e garantir a convergência global do método. Uma família de algoritmos pode ser obtida variando-se as regras de atualização dos parâmetros do FDIPA. O estudo apresentado neste trabalho foi feito considerando-se um único algoritmo e com restrições de desigualdade somente. Testes numéricos apontaram para uma escolha de parâmetros que levou a um número menor de iterações na resolução dos problemas teste. / This work presents a study on the influence of the parameters of an interior point and feasible directions algorithm for solving non-linear problems. The algorithm, named FDIPA, aims to find among the points of a set defined by equality and/or inequality constraints, those which minimize a differentiable function. The FDIPA is based on two linear systems with the same coefficient matrix, obtained from the Karush-Kuhn-Tucker first order necessary conditions. From a initial point in the interior of the feasible set, FDIPA generates a sequence of points which are also interior to the set. At each iteration, FDIPA produces a descent direction which is deflected towards the interior of the feasible set in order to create a new descent and feasible direction. Then, a linear search is performed to get a new interior point and assure the global convergence of the method. A family of algorithms can be obtained varying the rules used to update the parameters of the FDIPA. The study presented here has been done considering just one particular algorithm and inequality constraints only. Numerical tests pointed to a certain choice of parameters which led to a fewer number of iterations when solving some test problems.

Despite many advances in the design methods for compliant mechanisms, it is still not possible to know if a set of user-specifications has a solution. Furthermore, practical considerations such as failure limits and manufacturing limitations cannot be easily incorporated into existing methods. To address these issues, we have recently developed the concept of feasible stiffness and inertia maps. This thesis extends the concept of feasible maps and proposes another kind of maps that comprehensively depict the nonlinear kinetoelastostatic behaviour of compliant mechanisms. Feasible maps drawn as per user-specifications, with compliant mechanisms of the database overlaid on it, instantly inform the reader whether the specifications are feasible; whether the specifications are stringent; whether any mechanisms in the database meet the specifications, and whether any mechanism can be interactively modified to meet the specifications including size, strength and manufacturability. This thesis extends the earlier work on feasible maps by relaxing one condition that all beam segments in a compliant mechanism must retain their relative proportions. This is achieved by using size optimization. Thus, a certain degree of automation is brought into the procedure, which enhances the ease of use of the feasible maps. Illustrative examples are presented and implementation into a software is demonstrated. A major contribution of this work is the development of the concept of kinetoelastostatic maps of compliant mechanisms with fixed topology, shape, and relative proportions of beam segments in them. The map is drawn on a 2D plot using two non-dimensional quantities, one that captures the response of the mechanism and the other that combines the force, geometry, and material parameters. The map encloses a region that indicates the kinetoelastostatic capability of the mechanism. Another contribution of this work is the observation that the enclosed region can be parameterized using average slenderness ratio of the beam segments. The resulting curves help designers in assessing the capability and limits of a mechanism in terms of geometric advantage, mechanical advantage, normalized output displacement, inherent stiffness, etc. Numerous examples are presented to explain various uses of the non-dimensional maps.

This thesis presents cutter swept volume generation, in-process workpiece modeling and Cutter Workpiece Engagement (CWE) algorithms for finding the instantaneous intersections between cutter and workpiece in milling. One of the steps in simulating machining operations is the accurate extraction of the intersection geometry between cutter and workpiece. This geometry is a key input to force calculations and feed rate scheduling in milling. Given that industrial machined components can have highly complex geometries, extracting intersections accurately and efficiently is challenging. Three main steps are needed to obtain the intersection geometry between cutter and workpiece. These are the Swept volume generation, in-process workpiece modeling and CWE extraction respectively. In this thesis an analytical methodology for determining the shapes of the cutter swept envelopes is developed. In this methodology, cutter surfaces performing 5-axis tool motions are decomposed into a set of characteristic circles. For obtaining these circles a concept of two-parameter-family of spheres is introduced. Considering relationships among the circles the swept envelopes are defined analytically. The implementation of methodology is simple, especially when the cutter geometries are represented by pipe surfaces. During the machining simulation the workpiece update is required to keep track of the material removal process. Several choices for workpiece updates exist. These are the solid, facetted and vector model based methodologies. For updating the workpiece surfaces represented by the solid or faceted models third party software can be used. In this thesis multi-axis milling update methodologies are developed for workpieces defined by discrete vectors with different orientations. For simplifying the intersection calculations between discrete vectors and the tool envelope the properties of canal surfaces are utilized. A typical NC cutter has different surfaces with varying geometries and during the material removal process restricted regions of these surfaces are eligible to contact the in-process workpiece. In this thesis these regions are analyzed with respect to different tool motions. Later using the results from these analyses the solid, polyhedral and vector based CWE methodologies are developed for a range of different types of cutters and multi-axis tool motions. The workpiece surfaces cover a wide range of surface geometries including sculptured surfaces. / Applied Science, Faculty of / Mechanical Engineering, Department of / Graduate

Neste trabalho, propomos um método de pontos interiores para minimização com restrições lineares de grande porte. Este método explora a linearidade das restrições, partindo de um ponto viável e preservando a viabilidade dos iterandos. Apresentamos os principais resultados de convergência global, além de uma descrição rica em detalhes de uma implementação prática de todos os passos do método. Para atestar a implementação do método, exibimos uma ampla experimentação numérica, e uma análise comparativa com métodos bem difundidos na comunidade de otimização contínua. / In this work, we propose an interior-point method for large-scale linearly constrained optimization. This method explores the linearity of the constraints, starting from a feasible point and preserving the feasibility of the iterates. We present the main global convergence results, together with a rich description of the implementation details of all the steps of the method. To validate the implementation of the method, we present a wide set of numerical experiments and a comparative analysis with well known softwares of the continuous optimization community.

The application of optimization algorithms in the design of many economical and industrial problems currently represents a significant assignment. The development of high-powered computers allows an application of difficult mathematical techniques and physical phenomena to simulate real problems with sufficient accuracy. The optimization techniques used in engineering designs are mostly represented by modified mathematical programming methods with extension of their usability. The aim of the presented thesis "Using Optimization´s Algorithms by Designing of Structures" is to analyze the applicability of optimization procedures which are available in the widely used computing system ANSYS in civil and mechanical engineering practice. The numerical analyses were performed within the frame of multi-extreme, one to three dimensional optimization problems, multi-dimensional problems expressed by minimizing the weight of a truss beam and efficient design of air gap location in wooden studs from the point of view of thermal features of the structure. The analyzed optimization processes are in plurality verified with accurate manual computing and graphical solutions and the accent is put on optimization methods´ possibilities to improve robustness, efficiency and accuracy of the optimization algorithms in civil engineering problems´ designs. The optimization methods represent a suitable approach to improve the efficient design of a wide range of civil and mechanical engineering structures and elements. By combination of their advantages and FEM/FEA method it is possible to achieve very good results, although robustness of the solutions is not guaranteed. The robustness and accuracy of the procedure could be increased by competent exploration of design space and suitable selections of optimization methods´ features.

The diploma thesis is focused on the less used method of valuation of assets. It is an analysis of the highest and best use (HABU). The theoretical part of this thesis presents the basic law governing the valuation of assets, there are also explained the basic concepts and discribes the analysis of the highest and best use method. The practical part of the access method of valuation applied to a particular case.

Finding optimal configuration of power distribution systems topology is an NP-hard combinatorial optimization problem. It becomes more complex when time varying nature of loads in large-scale distribution systems is taken into account. In the second chapter of this dissertation, a systematic approach is proposed to tackle the computational burden of the procedure. To solve the optimization problem, a novel adaptive fuzzy based parallel genetic algorithm (GA) is proposed that employs the concept of parallel computing in identifying the optimal configuration of the network. The integration of fuzzy logic into GA enhances the efficiency of the parallel GA by adaptively modifying the migration rates between different processors during the optimization process. A computationally efficient graph encoding method based on Dandelion coding strategy is developed which automatically generates radial topologies and prevents the construction of infeasible radial networks during the optimization process. The main shortcoming of the proposed algorithm in Chapter 2 is that it identifies only one single solution. It means that the system operator will not have any option but relying on the found solution. That is why a novel hybrid optimization algorithm is proposed in the third chapter of this dissertation that determines Pareto frontiers, as candidate solutions, for multi-objective distribution network reconfiguration problem. Implementing this model, the system operator will have more flexibility in choosing the best configuration among the alternative solutions. The proposed hybrid optimization algorithm combines the concept of fuzzy Pareto dominance (FPD) with shuffled frog leaping algorithm (SFLA) to recognize non-dominated suboptimal solutions identified by SFLA. The local search step of SFLA is also customized for power systems applications so that it automatically creates and analyzes only the feasible and radial configurations in its optimization procedure which significantly increases the convergence speed of the algorithm. In the fourth chapter, the problem of optimal network reconfiguration is solved for the case in which the system operator is going to employ an optimization algorithm that is automatically modifying its parameters during the optimization process. Defining three fuzzy functions, the probability of crossover and mutation will be adaptively tuned as the algorithm proceeds and the premature convergence will be avoided while the convergence speed of identifying the optimal configuration will not decrease. This modified genetic algorithm is considered a step towards making the parallel GA, presented in the second chapter of this dissertation, more robust in avoiding from getting stuck in local optimums. In the fifth chapter, the concentration will be on finding a potential smart grid solution to more high-quality suboptimal configurations of distribution networks. This chapter is considered an improvement for the third chapter of this dissertation for two reasons: (1) A fuzzy logic is used in the partitioning step of SFLA to improve the proposed optimization algorithm and to yield more accurate classification of frogs. (2) The problem of system reconfiguration is solved considering the presence of distributed generation (DG) units in the network. In order to study the new paradigm of integrating smart grids into power systems, it will be analyzed how the quality of suboptimal solutions can be affected when DG units are continuously added to the distribution network. The heuristic optimization algorithm which is proposed in Chapter 3 and is improved in Chapter 5 is implemented on a smaller case study in Chapter 6 to demonstrate that the identified solution through the optimization process is the same with the optimal solution found by an exhaustive search.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-06-16T17:52:10Z No. of bitstreams: 1 camiladefreitasfernandes.pdf: 740367 bytes, checksum: fac5ab7dcb039b31d587151b9a53fab1 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-07-13T14:25:13Z (GMT) No. of bitstreams: 1 camiladefreitasfernandes.pdf: 740367 bytes, checksum: fac5ab7dcb039b31d587151b9a53fab1 (MD5) / Made available in DSpace on 2016-07-13T14:25:13Z (GMT). No. of bitstreams: 1 camiladefreitasfernandes.pdf: 740367 bytes, checksum: fac5ab7dcb039b31d587151b9a53fab1 (MD5) Previous issue date: 2016-04-08 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Neste trabalho estudamos um algoritmo para solução de problemas de otimização irrestrita com funções não necessariamente convexas ou diferenciáveis, denominado Nonsmooth Feasible Direction Nonconvex Algorithm - NFDNA, e fazemos uma aplicação deste algoritmo que consistiu em utilizá-lo como subrotina de um outro algoritmo chamado Interior Epigraph Direction (IED) method. O IED, desenvolvido para resolver problemas de otimização não convexa, não diferenciável mas com restrições, utiliza Dualidade Lagrangeana que requer a minimização da função Lagrangeana. A eficiência do IED depende fortemente de tal minimização. Como aplicação, substituímos a rotina fminsearch do Matlab, utilizada originalmente pelo IED, pelo NFDNA. Mostramos através da solução de problemas teste que a performance do IED foi mais eficiente com a utilização do NFDNA. / In this work we study an algorithm for solving unsconstrained, not necessarily convex or differentiable optimization problems called Nonsmooth Feasible Direction Nonconvex Algorithm - NFDNA. We also employ this algorithm as a subroutine of the Interior Epigraph Directions (IED) method. The IED method, devised for solving constrained, nonconvex and nonsmooth optimization problems uses Lagrangean Duality which requires the minimization of the Lagrangean function. The effectiveness of the IED depends strongly on the Lagrangean function minimization. As an application, we replace the Matlab routine fminsearch, originally used by IED, with NFDNA. We show through the solution of test problems that the IED performance is more efficient by employing NFDNA.

This diploma thesis deals with applying analysis of the highest and best use on a specific example, which is building number 15, in the object Mosilana, at address Spitalka 60/12. The theoretical part analyzes problematics of property valuation, which is related to the work. There are described part of that method, which are: legally permissible, physical posibility, financial feasible and maximum productivity. By using of valuation techniques is this method applied on our valued property in the practical part of diploma thesis. We determine the highest and best use.

This diploma thesis deals with the issue of analyzing the highest and best use of property. Abroad, this method is quite used and referred to as Habu. The method is applied to a specific case of the Sokolovna in Mosty u Jablunkova. The first part focuses on the theoretical introduction, which describes the basic concepts and how to tackle the highest and best use. The second part of the thesis is focused on the practical application of the method to a particular case where the legal admissibility, physical, financial and maximum profitability tests are made on logically probable possibilities of use. The test results are the highest and best use of a particular case.