5 resultados para Luus-Jaakola optimization method

em Universidade Federal do Rio Grande do Norte(UFRN)


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This work proposes a computational methodology to solve problems of optimization in structural design. The application develops, implements and integrates methods for structural analysis, geometric modeling, design sensitivity analysis and optimization. So, the optimum design problem is particularized for plane stress case, with the objective to minimize the structural mass subject to a stress criterion. Notice that, these constraints must be evaluated at a series of discrete points, whose distribution should be dense enough in order to minimize the chance of any significant constraint violation between specified points. Therefore, the local stress constraints are transformed into a global stress measure reducing the computational cost in deriving the optimal shape design. The problem is approximated by Finite Element Method using Lagrangian triangular elements with six nodes, and use a automatic mesh generation with a mesh quality criterion of geometric element. The geometric modeling, i.e., the contour is defined by parametric curves of type B-splines, these curves hold suitable characteristics to implement the Shape Optimization Method, that uses the key points like design variables to determine the solution of minimum problem. A reliable tool for design sensitivity analysis is a prerequisite for performing interactive structural design, synthesis and optimization. General expressions for design sensitivity analysis are derived with respect to key points of B-splines. The method of design sensitivity analysis used is the adjoin approach and the analytical method. The formulation of the optimization problem applies the Augmented Lagrangian Method, which convert an optimization problem constrained problem in an unconstrained. The solution of the Augmented Lagrangian function is achieved by determining the analysis of sensitivity. Therefore, the optimization problem reduces to the solution of a sequence of problems with lateral limits constraints, which is solved by the Memoryless Quasi-Newton Method It is demonstrated by several examples that this new approach of analytical design sensitivity analysis of integrated shape design optimization with a global stress criterion purpose is computationally efficient

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In recent years there has been a significant growth in technologies that modify implant surfaces, reducing healing time and allowing their successful use in areas with low bone density. One of the most widely used techniques is plasma nitration, applied with excellent results in titanium and its alloys, with greater frequency in the manufacture of hip, ankle and shoulder implants. However, its use in dental implants is very limited due to high process temperatures (between 700 C o and 800 C o ), resulting in distortions in these geometrically complex and highly precise components. The aim of the present study is to assess osseointegration and mechanical strength of grade II nitrided titanium samples, through configuration of hollow cathode discharge. Moreover, new formulations are proposed to determine the optimum structural topology of the dental implant under study, in order to perfect its shape, make it efficient, competitive and with high definition. In the nitriding process, the samples were treated at a temperature of 450 C o and pressure of 150 Pa , during 1 hour of treatment. This condition was selected because it obtains the best wettability results in previous studies, where different pressure, temperature and time conditions were systematized. The samples were characterized by X-ray diffraction, scanning electron microscope, roughness, microhardness and wettability. Biomechanical fatigue tests were then conducted. Finally, a formulation using the three dimensional structural topology optimization method was proposed, in conjunction with an hadaptive refinement process. The results showed that plasma nitriding, using the hollow cathode discharge technique, caused changes in the surface texture of test specimens, increases surface roughness, wettability and microhardness when compared to the untreated sample. In the biomechanical fatigue test, the treated implant showed no flaws, after five million cycles, at a maximum fatigue load of 84.46 N. The results of the topological optimization process showed well-defined optimized layouts of the dental implant, with a clear distribution of material and a defined edge

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The topology optimization problem characterize and determine the optimum distribution of material into the domain. In other words, after the definition of the boundary conditions in a pre-established domain, the problem is how to distribute the material to solve the minimization problem. The objective of this work is to propose a competitive formulation for optimum structural topologies determination in 3D problems and able to provide high-resolution layouts. The procedure combines the Galerkin Finite Elements Method with the optimization method, looking for the best material distribution along the fixed domain of project. The layout topology optimization method is based on the material approach, proposed by Bendsoe & Kikuchi (1988), and considers a homogenized constitutive equation that depends only on the relative density of the material. The finite element used for the approach is a four nodes tetrahedron with a selective integration scheme, which interpolate not only the components of the displacement field but also the relative density field. The proposed procedure consists in the solution of a sequence of layout optimization problems applied to compliance minimization problems and mass minimization problems under local stress constraint. The microstructure used in this procedure was the SIMP (Solid Isotropic Material with Penalty). The approach reduces considerably the computational cost, showing to be efficient and robust. The results provided a well defined structural layout, with a sharpness distribution of the material and a boundary condition definition. The layout quality was proporcional to the medium size of the element and a considerable reduction of the project variables was observed due to the tetrahedrycal element

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One of several techniques applied to production processes oil is the artificial lift, using equipment in order to reduce the bottom hole pressure, providing a pressure differential, resulting in a flow increase. The choice of the artificial lift method depends on a detailed analysis of the some factors, such as initial costs of installation, maintenance, and the existing conditions in the producing field. The Electrical Submersible Pumping method (ESP) appears to be quite efficient when the objective is to produce high liquid flow rates in both onshore and offshore environments, in adverse conditions of temperature and in the presence of viscous fluids. By definition, ESP is a method of artificial lift in which a subsurface electric motor transforms electrical into mechanical energy to trigger a centrifugal pump of multiple stages, composed of a rotating impeller (rotor) and a stationary diffuser (stator). The pump converts the mechanical energy of the engine into kinetic energy in the form of velocity, which pushes the fluid to the surface. The objective of this work is to implement the optimization method of the flexible polyhedron, known as Modified Simplex Method (MSM) applied to the study of the influence of the modification of the input and output parameters of the centrifugal pump impeller in the channel of a system ESP. In the use of the optimization method by changing the angular parameters of the pump, the resultant data applied to the simulations allowed to obtain optimized values of the Head (lift height), lossless efficiency and the power with differentiated results.

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Launching centers are designed for scientific and commercial activities with aerospace vehicles. Rockets Tracking Systems (RTS) are part of the infrastructure of these centers and they are responsible for collecting and processing the data trajectory of vehicles. Generally, Parabolic Reflector Radars (PRRs) are used in RTS. However, it is possible to use radars with antenna arrays, or Phased Arrays (PAs), so called Phased Arrays Radars (PARs). Thus, the excitation signal of each radiating element of the array can be adjusted to perform electronic control of the radiation pattern in order to improve functionality and maintenance of the system. Therefore, in the implementation and reuse projects of PARs, modeling is subject to various combinations of excitation signals, producing a complex optimization problem due to the large number of available solutions. In this case, it is possible to use offline optimization methods, such as Genetic Algorithms (GAs), to calculate the problem solutions, which are stored for online applications. Hence, the Genetic Algorithm with Maximum-Minimum Crossover (GAMMC) optimization method was used to develop the GAMMC-P algorithm that optimizes the modeling step of radiation pattern control from planar PAs. Compared with a conventional crossover GA, the GAMMC has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, the GAMMC prevents premature convergence, increases population fitness and reduces the processing time. Therefore, the GAMMC-P uses a reconfigurable algorithm with multiple objectives, different coding and genetic operator MMC. The test results show that GAMMC-P reached the proposed requirements for different operating conditions of a planar RAV.