986 resultados para Análise Fractal


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In this work we have investigated some aspects of the two-dimensional flow of a viscous Newtonian fluid through a disordered porous medium modeled by a random fractal system similar to the Sierpinski carpet. This fractal is formed by obstacles of various sizes, whose distribution function follows a power law. They are randomly disposed in a rectangular channel. The velocity field and other details of fluid dynamics are obtained by solving numerically of the Navier-Stokes and continuity equations at the pore level, where occurs actually the flow of fluids in porous media. The results of numerical simulations allowed us to analyze the distribution of shear stresses developed in the solid-fluid interfaces, and find algebraic relations between the viscous forces or of friction with the geometric parameters of the model, including its fractal dimension. Based on the numerical results, we proposed scaling relations involving the relevant parameters of the phenomenon, allowing quantifying the fractions of these forces with respect to size classes of obstacles. Finally, it was also possible to make inferences about the fluctuations in the form of the distribution of viscous stresses developed on the surface of obstacles.

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As variáveis econômicas são frequentemente governadas por processos dinâmicos e não-lineares que podem gerar relações de dependência de longo prazo e padrões cíclicos não-periódicos com mudanças abruptas de tendências. Para o caso dos preços agrícolas este comportamento não é diferente e as peculiaridades destes mercados podem gerar séries temporais fracionalmente integradas, cujas singularidades não seriam adequadamente capturadas pelos tradicionais modelos analíticos fundamentados na hipótese dos mercados eficientes e de passeio aleatório. Sendo assim, o presente estudo buscou investigar a presença de estruturas fractais no mercado à vista de algumas das principais commodities agrícolas brasileiras: café, boi gordo, açúcar, milho, soja e bezerro. Foram empregadas técnicas tradicionais e específicas para a análise de séries temporais fractais como a análise de R/S e a aplicação de modelos das famílias ARFIMA e FIGARCH. Os resultados indicaram que, com exceção do bezerro, o componente de drift destas séries não apresentou comportamento fractal, ao contrário do observado para o componente da volatilidade, que apresentou aspecto de estrutura fractal para todas as commodities analisadas.

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Um dos principais fatores de estudo do mercado de capitais é a discussão a respeito da teoria de eficiência de mercado, que no caso diverge em relação ao comportamento do preço da maioria dos ativos. Este trabalho tem o intuito de analisar o comportamento do principal índice de preços do mercado de bitcoins (BPI) durante o período de julho de 2010 a setembro de 2014. Inicialmente será testada a hipótese do passeio aleatório para o BPI. Em seguida serão verificadas as correlações de longa data nas séries financeiras temporais utilizando como instrumento de análise o expoente de Hurst (H), que inicialmente foi usado para calcular correlações em fenômenos naturais e posteriormente sua abrangência alcançou a área financeira. O estudo avalia o expoente H através de métodos distintos destacando-se a análise R/S e a DFA. Para o cálculo do expoente ao longo do tempo, utiliza-se uma janela móvel de 90 dias deslocando-se de 10 em 10 dias. Já para o cálculo em diferentes escalas verifica-se, para cada dia, o valor do expoente H nos últimos 360, 180 e 90 dias respectivamente. Os resultados evidenciaram que o índice BPI apresenta memória longa persistente em praticamente todo o período analisado. Além disso, a análise em diferentes escalas indica a possibilidade de previsão de eventos turbulentos no índice neste mesmo período. Finalmente foi possível comprovar a hipótese de mercados fractais para a série histórica de retornos do BPI.

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The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.

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The bidimensional periodic structures called frequency selective surfaces have been well investigated because of their filtering properties. Similar to the filters that work at the traditional radiofrequency band, such structures can behave as band-stop or pass-band filters, depending on the elements of the array (patch or aperture, respectively) and can be used for a variety of applications, such as: radomes, dichroic reflectors, waveguide filters, artificial magnetic conductors, microwave absorbers etc. To provide high-performance filtering properties at microwave bands, electromagnetic engineers have investigated various types of periodic structures: reconfigurable frequency selective screens, multilayered selective filters, as well as periodic arrays printed on anisotropic dielectric substrates and composed by fractal elements. In general, there is no closed form solution directly from a given desired frequency response to a corresponding device; thus, the analysis of its scattering characteristics requires the application of rigorous full-wave techniques. Besides that, due to the computational complexity of using a full-wave simulator to evaluate the frequency selective surface scattering variables, many electromagnetic engineers still use trial-and-error process until to achieve a given design criterion. As this procedure is very laborious and human dependent, optimization techniques are required to design practical periodic structures with desired filter specifications. Some authors have been employed neural networks and natural optimization algorithms, such as the genetic algorithms and the particle swarm optimization for the frequency selective surface design and optimization. This work has as objective the accomplishment of a rigorous study about the electromagnetic behavior of the periodic structures, enabling the design of efficient devices applied to microwave band. For this, artificial neural networks are used together with natural optimization techniques, allowing the accurate and efficient investigation of various types of frequency selective surfaces, in a simple and fast manner, becoming a powerful tool for the design and optimization of such structures

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The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm

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The microstrip antennas are in constant evidence in current researches due to several advantages that it presents. Fractal geometry coupled with good performance and convenience of the planar structures are an excellent combination for design and analysis of structures with ever smaller features and multi-resonant and broadband. This geometry has been applied in such patch microstrip antennas to reduce its size and highlight its multi-band behavior. Compared with the conventional microstrip antennas, the quasifractal patch antennas have lower frequencies of resonance, enabling the manufacture of more compact antennas. The aim of this work is the design of quasi-fractal patch antennas through the use of Koch and Minkowski fractal curves applied to radiating and nonradiating antenna s edges of conventional rectangular patch fed by microstrip inset-fed line, initially designed for the frequency of 2.45 GHz. The inset-fed technique is investigated for the impedance matching of fractal antennas, which are fed through lines of microstrip. The efficiency of this technique is investigated experimentally and compared with simulations carried out by commercial software Ansoft Designer used for precise analysis of the electromagnetic behavior of antennas by the method of moments and the neural model proposed. In this dissertation a study of literature on theory of microstrip antennas is done, the same study is performed on the fractal geometry, giving more emphasis to its various forms, techniques for generation of fractals and its applicability. This work also presents a study on artificial neural networks, showing the types/architecture of networks used and their characteristics as well as the training algorithms that were used for their implementation. The equations of settings of the parameters for networks used in this study were derived from the gradient method. It will also be carried out research with emphasis on miniaturization of the proposed new structures, showing how an antenna designed with contours fractals is capable of a miniaturized antenna conventional rectangular patch. The study also consists of a modeling through artificial neural networks of the various parameters of the electromagnetic near-fractal antennas. The presented results demonstrate the excellent capacity of modeling techniques for neural microstrip antennas and all algorithms used in this work in achieving the proposed models were implemented in commercial software simulation of Matlab 7. In order to validate the results, several prototypes of antennas were built, measured on a vector network analyzer and simulated in software for comparison

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In this thesis, a frequency selective surface (FSS) consists of a two-dimensional periodic structure mounted on a dielectric substrate, which is capable of selecting signals in one or more frequency bands of interest. In search of better performance, more compact dimensions, low cost manufacturing, among other characteristics, these periodic structures have been continually optimized over time. Due to its spectral characteristics, which are similar to band-stop or band-pass filters, the FSSs have been studied and used in several applications for more than four decades. The design of an FSS with a periodic structure composed by pre-fractal elements facilitates the tuning of these spatial filters and the adjustment of its electromagnetic parameters, enabling a compact design which generally has a stable frequency response and superior performance relative to its euclidean counterpart. The unique properties of geometric fractals have shown to be useful, mainly in the production of antennas and frequency selective surfaces, enabling innovative solutions and commercial applications in microwave range. In recent applications, the FSSs modify the indoor propagation environments (emerging concept called wireless building ). In this context, the use of pre-fractal elements has also shown promising results, allowing a more effective filtering of more than one frequency band with a single-layer structure. This thesis approaches the design of FSSs using pre-fractal elements based on Vicsek, Peano and teragons geometries, which act as band-stop spatial filters. The transmission properties of the periodic surfaces are analyzed to design compact and efficient devices with stable frequency responses, applicable to microwave frequency range and suitable for use in indoor communications. The results are discussed in terms of the electromagnetic effect resulting from the variation of parameters such as: fractal iteration number (or fractal level), scale factor, fractal dimension and periodicity of FSS, according the pre-fractal element applied on the surface. The analysis of the fractal dimension s influence on the resonant properties of a FSS is a new contribution in relation to researches about microwave devices that use fractal geometry. Due to its own characteristics and the geometric shape of the Peano pre-fractal elements, the reconfiguration possibility of these structures is also investigated and discussed. This thesis also approaches, the construction of efficient selective filters with new configurations of teragons pre-fractal patches, proposed to control the WLAN coverage in indoor environments by rejecting the signals in the bands of 2.4~2.5 GHz (IEEE 802.11 b) and 5.0~6.0 GHz (IEEE 802.11a). The FSSs are initially analyzed through simulations performed by commercial software s: Ansoft DesignerTM and HFSSTM. The fractal design methodology is validated by experimental characterization of the built prototypes, using alternatively, different measurement setups, with commercial horn antennas and microstrip monopoles fabricated for low cost measurements

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Frequency Selective Surfaces (FSS) are periodic structures in one or two dimensions that act as spatial filters, can be formed by elements of type conductors patches or apertures, functioning as filters band-stop or band-pass respectively. The interest in the study of FSS has grown through the years, because such structures meet specific requirements as low-cost, reduced dimensions and weighs, beyond the possibility to integrate with other microwave circuits. The most varied applications for such structures have been investigated, as for example, radomes, antennas systems for airplanes, electromagnetic filters for reflective antennas, absorbers structures, etc. Several methods have been used for the analysis of FSS, among them, the Wave Method (WCIP). Are various shapes of elements that can be used in FSS, as for example, fractal type, which presents a relative geometric complexity. This work has as main objective to propose a simplification geometric procedure a fractal FSS, from the analysis of influence of details (gaps) of geometry of the same in behavior of the resonance frequency. Complementarily is shown a simple method to adjust the frequency resonance through analysis of a FSS, which uses a square basic cell, in which are inserted two reentrance and dimensions these reentrance are varied, making it possible to adjust the frequency. For this, the structures are analyzed numerically, using WCIP, and later are characterized experimentally comparing the results obtained. For the two cases is evaluated, the influence of electric and magnetic fields, the latter through the electric current density vector. Is realized a bibliographic study about the theme and are presented suggestions for the continuation of this work

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Educação Matemática - IGCE

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É objetivo do presente trabalho implantar como modelos para estudo da formação hipocampal das aves migratórias as espécies de maçarico Calidris pusilla e Actitis macularia que abandonam as regiões geladas do Canadá, fugindo do inverno, em direção à costa da América do Sul e do Caribe onde permanecem até a primavera quando então retornam ao hemisfério norte. Mais especificamente pretende-se descrever a organização morfológica qualitativa e quantitativa da formação hipocampal, empregando citoarquitetonia com cresil violeta e imunomarcação para neurônios e células da glia, sucedidas por estimativas estereológicas do número total de células identificadas com marcadores seletivos para aquelas células, assim como comparar a morfologia tridimensional da micróglia das aves com a dos mamíferos. As coletas de campo para a caracterização da formação hipocampal do Calidris pusilla e Actitis macularia em seus aspectos morfológicos foram feitas no Brasil na Ilha Canelas (0°47'21.95"S e 46°43'7.34"W) na Costa da Região Nordeste do Pará no município de Bragança, e no Canadá, na Baia de Fundy perto de Johnson's Mills na cidade de New Brunswick (45°50'19.3" N 64°31'5.39" W). A definição dos limites da formação hipocampal foi feita empregando-se as técnicas de Nissl e de imunomarcação para NeuN. Para a definição dos objetos de interesse das estimativas estereológicas e das reconstruções tridimensionais empregou-se imunomarcação com anticorpo anti-NeuN para neurônios e anti-IBA- 1 para micróglia. As estimativas estereológicas revelaram em média número similar de neurônios nas duas espécies enquanto que no hipocampo de Actitis macularia observou-se número de micróglias 37% maior do que no de Calidris pusilla. Além disso, encontrou-se que em média o volume da formação hipocampal do Actitis macularia é 38% maior do que o encontrado em Calidris pusilla. Os estudos comparativos da morfologia microglial das duas espécies de aves com a dos mamíferos Rattus novergicus e Cebus apella revelaram diferenças morfológicas significantes que indicam que as micróglias das aves mostram em média, menor complexidade (dimensão fractal), tem diâmetros e perímetros de soma menores e possuem ramos mais finos do que aquelas do rato e do macaco.