Modelação de redes de distribuição de energia elétrica com carregamento não linear, incluindo elementos de regulação e compensação

Pós-graduação em Engenharia Elétrica - FEIS

Caracterização experimental de sistemas mecânicos com comportamento não-linear

Pós-graduação em Engenharia Mecânica - FEIS

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Análise genética de escores de avaliação visual de bovinos com modelos bayesianos de limiar e linear

O objetivo deste trabalho foi comparar as estimativas de parâmetros genéticos obtidas em análises bayesianas uni-característica e bi-característica, em modelo animal linear e de limiar, considerando-se as características categóricas morfológicas de bovinos da raça Nelore. Os dados de musculosidade, estrutura física e conformação foram obtidos entre 2000 e 2005, em 3.864 animais de 13 fazendas participantes do Programa Nelore Brasil. Foram realizadas análises bayesianas uni e bi-características, em modelos de limiar e linear. de modo geral, os modelos de limiar e linear foram eficientes na estimação dos parâmetros genéticos para escores visuais em análises bayesianas uni-características. Nas análises bi-características, observou-se que: com utilização de dados contínuos e categóricos, o modelo de limiar proporcionou estimativas de correlação genética de maior magnitude do que aquelas do modelo linear; e com o uso de dados categóricos, as estimativas de herdabilidade foram semelhantes. A vantagem do modelo linear foi o menor tempo gasto no processamento das análises. Na avaliação genética de animais para escores visuais, o uso do modelo de limiar ou linear não influenciou a classificação dos animais, quanto aos valores genéticos preditos, o que indica que ambos os modelos podem ser utilizados em programas de melhoramento genético.

Growth curve in Santa Ines sheep

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Utilização de modelos de programação não-linear para sistematização de terras para irrigação em áreas regulares

Objetivou-se com este trabalho, desenvolver modelos de programação não-linear para sistematização de terras, aplicáveis para áreas com formato regular e que minimizem a movimentação de terra, utilizando o software GAMS para o cálculo. Esses modelos foram comparados com o Método dos Quadrados Mínimos Generalizado, desenvolvido por Scaloppi & Willardson (1986), sendo o parâmetro de avaliação o volume de terra movimentado. Concluiu-se que, ambos os modelos de programação não-linear desenvolvidos nesta pesquisa mostraram-se adequados para aplicação em áreas regulares e forneceram menores valores de movimentação de terra quando comparados com o método dos quadrados mínimos.

Períodos de interferência de uma comunidade de plantas daninhas na cultura da batata

Objetivou-se neste trabalho avaliar diferentes períodos de controle e de convivência de uma comunidade de plantas daninhas na cultura da batata 'Atlantic'. O experimento foi realizado no município de Botucatu-SP, e o delineamento experimental utilizado foi de blocos ao acaso com quatro repetições. Os tratamentos constituíram-se de seis períodos de controle, nos quais a cultura foi mantida livre da comunidade de plantas daninhas e após cada período, as plantas daninhas foram deixadas crescer livremente; e de seis períodos de convivência, nos quais a cultura foi mantida na presença da comunidade de plantas daninhas e após cada período, as plantas daninhas foram eliminadas até a colheita. Os períodos foram de 7, 14, 21, 28, 35 e 42 dias após o plantio dos tubérculos, além de uma testemunha mantida sempre livre de plantas daninhas e outra mantida sempre na presença dessas plantas. Foram identificadas 9 famílias e 15 espécies de plantas daninhas, com destaque para Bidens pilosa, Galinsoga parviflora,Brachiaria plantaginea,Commelina benghalensis e Digitaria horizontalis. Os resultados de produção de tubérculos ajustaram-se ao modelo de regressão não-linear: y = 8,907+(17,722/[1+(x/16,865)-8,412]), (R² = 0,963*) - equação para os períodos de controle e y = 5,728+(24,789/[1+(x/39,292)2,247 ]), (R² = 0,947*) - equação para os períodos de convivência. Assim, considerando perda de 5% na produtividade como aceitável, foram determinados o período anterior à interferência (PAI), que foi de 20 dias; o período total de prevenção à interferência (PTPI), de 21 dias; e o período crítico de prevenção da interferência (PCPI), de apenas de um dia, dos 20 aos 21 dias após o plantio dos tubérculos.

Solid-liquid transition in Nb powder determined by third harmonic susceptibility

Measurements of the third harmonic of the AC-susceptibility were employed to determine the boundaries of the linear regime of the magnetic response of Nb powder. Non-linear contributions to the magnetic response reveal the occurrence of a structured phase, disappearing as the vortex lattice melts to the liquid state. A systematic study of the third harmonic was conducted to determine how its onset temperature depends on experimental parameters, such as the frequency and amplitude of the excitation field. The melting line (ML) has been extracted from the onset temperature measured at low-frequencies and low-excitation fields in the presence of DC magnetic fields. The study indicates that the ML can be described by a 3D vortex-glass model, except at lower fields, where the system experiences a depinning crossover, and the best description of the experimental data is provided by a 3D Bose-glass model. (c) 2008 Elsevier B. V. All rights reserved.

Two-dimensional modeling of material failure in reinforced concrete by means of a continuum strong discontinuity approach

The paper presents a new methodology to model material failure, in two-dimensional reinforced concrete members, using the Continuum Strong Discontinuity Approach (CSDA). The mixture theory is used as the methodological approach to model reinforced concrete as a composite material, constituted by a plain concrete matrix reinforced with two embedded orthogonal long fiber bundles (rebars). Matrix failure is modeled on the basis of a continuum damage model, equipped with strain softening, whereas the rebars effects are modeled by means of phenomenological constitutive models devised to reproduce the axial non-linear behavior, as well as the bondslip and dowel effects. The proposed methodology extends the fundamental ingredients of the standard Strong Discontinuity Approach, and the embedded discontinuity finite element formulations, in homogeneous materials, to matrix/fiber composite materials, as reinforced concrete. The specific aspects of the material failure modeling for those composites are also addressed. A number of available experimental tests are reproduced in order to illustrate the feasibility of the proposed methodology. (c) 2007 Elsevier B.V. All rights reserved.

A mixture theory based method for three-dimensional modeling of reinforce concrete members with embedded crack finite elements

The paper presents a methodology to model three-dimensional reinforced concrete members by means of embedded discontinuity elements based on the Continuum Strong Discontinuous Approach (CSDA). Mixture theory concepts are used to model reinforced concrete as a 31) composite material constituted of concrete with long fibers (rebars) bundles oriented in different directions embedded in it. The effects of the rebars are modeled by phenomenological constitutive models devised to reproduce the axial non-linear behavior, as well as the bond-slip and dowel action. The paper presents the constitutive models assumed for the components and the compatibility conditions chosen to constitute the composite. Numerical analyses of existing experimental reinforced concrete members are presented, illustrating the applicability of the proposed methodology.

An efficient Hopfield network to solve economic dispatch problems with transmission system representation

Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. The ability of neural networks to realize some complex non-linear function makes them attractive for system optimization. All ED models solved by neural approaches described in the literature fail to represent the transmission system. Therefore, such procedures may calculate dispatch policies, which do not take into account important active power constraints. Another drawback pointed out in the literature is that some of the neural approaches fail to converge efficiently toward feasible equilibrium points. A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper. The transmission system is represented through linear load flow equations and constraints on active power flows. The internal parameters of such modified Hopfield networks are computed using the valid-subspace technique. These parameters guarantee the network convergence to feasible equilibrium points, which represent the solution for the ED problem. Simulation results and a sensitivity analysis involving IEEE 14-bus test system are presented to illustrate efficiency of the proposed approach. (C) 2004 Elsevier Ltd. All rights reserved.

Application of neural networks to identify features of dynamical grounding systems

The accurate identification of features of dynamical grounding systems are extremely important to define the operational safety and proper functioning of electric power systems. Several experimental tests and theoretical investigations have been carried out to obtain characteristics and parameters associated with the technique of grounding. The grounding system involves a lot of non-linear parameters. This paper describes a novel approach for mapping characteristics of dynamical grounding systems using artificial neural networks. The network acts as identifier of structural features of the grounding processes. So that output parameters can be estimated and generalized from an input parameter set. The results obtained by the network are compared with other approaches also used to model grounding systems.

Continuously deformable topological structure

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Conventional and microwave sintering of CaCu(3)Ti(4)O(12)/CaTiO(3) ceramic composites: non-ohmic and dielectric properties

The non-ohmic and dielectric properties as well as the dependence on the microstructural features of CaCu(3)Ti(4)O(12)/CaTiO(3) ceramic composites obtained by conventional and microwave sintering were investigated. It was demonstrated that the non-ohmic and dielectric properties depend strongly on the sintering conditions. It was found that the non-linear coefficient reaches values of 65 for microwave-sintered samples and 42 for samples sintered in a conventional furnace when a current density interval of 1-10 mA cm(-2) is considered. The non-linear coefficient value of 65 is equivalent to 1500 for samples sintered in the microwave if a current interval of 5-30 mA is considered as is shortly discussed by Chung et al (2004 Nature Mater. 3 774). Due to a high non-linear coefficient and a low leakage current (90 mu A) under both processing conditions, these samples are promising for varistor applications. The conventionally sintered samples exhibit a higher relative dielectric constant at 1 kHz (2960) compared with the samples sintered in the microwave furnace (2100). At high frequencies, the dielectric constant is also larger in the samples sintered in the conventional furnace. Depending on the application, one or another synthesis methodology is recommended, that is, for varistor applications sintered in a microwave furnace and for dielectric application sintered in a conventional furnace.

Comparative degradation of ZnO- and SnO(2)-based polycrystalline non-ohmic devices by current pulse stress

The degradation behaviour of SnO(2)-based varistors (SCNCr) due to current pulses (8/20 mu s) is reported here for the first time in comparison with the ZnO-based commercial varistors (ZnO). Puncturing and/or cracking failures were observed in ZnO-based varistors possessing inferior thermo-mechanical properties in comparison with that found in a SCNCr system free of failures. Both systems presented electric degradation related to the increase in the leakage current and decrease in the electric breakdown field, non-linear coefficient and average value of the potential barrier height. However, it was found that a more severe degradation occurred in the ZnO-based varistors concerning their non-ohmic behaviour, while in the SCNCr system, a strong non-ohmic behaviour remained after the degradation. These results indicate that the degradation in the metal oxide varistors is controlled by a defect diffusion process whose rate depends on the mobility, the concentration of meta-stable defects and the amount of electrically active interfaces. The improved behaviour of the SCNCr system is then inferred to be associated with the higher amount of electrically active interfaces (85%) and to a higher energy necessary to activate the diffusion of the specific defects.