932 resultados para Damage of flood


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The objective of this study was to characterize acrosomal ultrastructure following discontinuous Percoll gradient centrifugation of cryopreserved bovine sperm. Semen was collected from six bulls of different breeds and three ejaculates per bull were evaluated. Frozen semen samples were thawed and the acrosomal region of sperm cells was evaluated by transmission electron microscopy (TEM) before (n = 18) and after (n = 18) Percoll centrifugation. The evaluation of 20 sperm heads from each of the 36 samples analyzed ensured that a large number of cells were investigated. The data were subjected to analysis of variance at a level of significance of 5%. Percoll centrifugation reduced the percentage of sperm exhibiting normal acrosomes (from 61.77 to 30.24%), reduced the percentage of sperm presenting atypical acrosome reactions (from 28.38 to 4.84%) and increased the percentage of sperm exhibiting damage in the acrosome (from 6.14 to 64.26%). The percentage of sperm with typical acrosome reactions was not significantly different before (3.70%) and after (0.67%) centrifugation. TEM distinguished four different types of acrosomal status and enabled ultrastructural characterization of acrosomal injuries. The percentage of sperm exhibiting normal acrosomes decreased and damage in the acrosome was the most frequent acrosomal injury with the Percoll gradient centrifugation protocol utilized.

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

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This work deals with the initial applications and formulation of an aniscitropic plastic-damage constitutive model proposed for non-linear analysis of reinforced concrete structures submitted to a loading with change of the sign. The original constitutive model is based on the fundamental hypothesis of energy equivalence between real and continuous medium following the concepts of the Continuum Damage Mechanics. The concrete is assumed as an initial elastic isotropic medium presenting anisotropy, permanent strains and bimodularity (distinct elastic responses whether traction or compression stress states prevail) induced by damage evolution. In order to take into account the bimodularity, two damage tensors governing the rigidity in tension or compression regimes are introduced. Then, some conditions are introduced in the original version of the model in order to simulate the damage unilateral effect. The three-dimensional version of the proposed model is analyzed in order to validate its formulation when compared to micromechanical theory. The one-dimensional version of the model is applied in the analyses of a reinforced concrete beam submitted to a loading with change of the sign. Despite the parametric identification problems, the initial applications show the good performance of the model.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

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Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

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

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This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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