Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes

This work presents an investigation into the use of the finite element method and artificial neural networks in the identification of defects in industrial plants metallic tubes, due to the aggressive actions of the fluids contained by them, and/or atmospheric agents. The methodology used in this study consists of simulating a very large number of defects in a metallic tube, using the finite element method. Both variations in width and height of the defects are considered. Then, the obtained results are used to generate a set of vectors for the training of a perceptron multilayer artificial neural network. Finally, the obtained neural network is used to classify a group of new defects, simulated by the finite element method, but that do not belong to the original dataset. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Determination of resonant frequencies of triangular and rectangular microstrip antennas, using artificial neural networks

This paper presents models that can be used in the design of microstrip antennas for mobile communications. The antennas can be triangular or rectangular. The presented models are compared with deterministic and empirical models based on artificial neural networks (ANN) presented in the literature. The models are based on Perceptron Multilayer (PML) and Radial Basis Function (RBF) ANN. RBF based models presented the best results. Also, the models can be embedded in CAD systems, in order to design microstrip antennas for mobile communications.

Determinação da freqüência de ressonância de antenas tipo microfita triangular e retangular utilizando redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Evaluation of Different Conditions of Contact for Caprolactam Migration from Multilayer Polyamide Films into Food Simulants

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Multilayer adsorption of Cu(II) and Cd(II) over Brazilian Orchid Tree (Pata-de-vaca) and its adsorptive properties

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

Effect of gamma irradiation on caprolactam migration from multilayer polyamide 6 films into food simulants: development and validation of a gas chromatographic method

A GC method to determine caprolactam in water, 15 ethanol, and olive oil food simulants was developed and validated. Linear ranges varied from 0.96 to 642.82 g/mL for water, 0.64 to 800.32 g/mL for 15 ethanol, and 1.06 to 1062.34 g/g for olive oil, with correlation coefficients higher than 0.999. Method precision studies showed RSD values lower than 5.45, while method accuracy studies showed recovery from 72 to 111 for all simulants. The effect of gamma irradiation on caprolactam migration from multilayer polyamide 6 (PA-6) films intended for cheese into water, 15 ethanol, olive oil, and 3 acetic acid simulants was also studied. For migration assay, non-irradiated and irradiated (12 kGy) films were placed in contact with the simulant and exposed at 40C for 10 days. The validated method was used to quantify caprolactam migration from multilayer PA-6 films into the simulants, which ranged from 1.03 to 7.59 mg/kg for non-irradiated films, and from 4.82 to 11.32 mg/kg for irradiated films. Irradiation caused almost no changes in caprolactam levels, with the exception of olive oil, which showed an increase in the caprolactam level. All multilayer PA-6 films were in accordance with the requirements of the legislation for caprolactam migration.

Endovascular repair of a juxtarenal saccular aneurysm using the Multilayer Flow Modulator: report of the first case performed in a Public Hospital in Brazil

Endovascular aortic aneurysm repair (EVAR) involving renal and visceral arteries remains a great challenge. Several techniques have been developed over the time to treat juxtarenal, pararenal and thoracoabdominal aneurysms, highlighting the fenestrated and branched endografts, parallel prostheses as Chimney, Periscope and Sandwich Techniques and the use of flow modulation by multilayer stent. We report a case of saccular juxtarenal aortic aneurysm with high surgical risk for complex airway access due to a history of radical laryngectomy for laryngeal neoplasm. Due to chronic aorto-iliac obstructive disease, ostial stenosis of renal artery and limited diameter of the suprarenal aorta, we discarded options involving fenestrated/branched endografts and involving parallel prostheses techniques. We present this case as a therapeutic challenge and a successful treatment option in the short-term evaluation.

Electrical properties of polymer/metal interface in polymer light-emitting devices: electron injection barrier suppression

The electrical characterization of a high efficient multilayer polymer light emitting diode using poly[(2-methoxy-5-hexyloxy)-p-phenylenevinylene] as the emissive layer and an anionic fluorinated surfactant as the electron transport layer was performed. For the sake of comparison, a conventional single layer device was fabricated. The density current vs. voltage measurements revealed that the conventional device has a higher threshold voltage and lower current compared to the surfactant modified device. The effective barrier height for electron injection was suppressed. The influence of the interfaces and bulk contributions to the dc and high frequencies conductivities of the devices was also discussed. (c) 2006 Springer Science + Business Media, Inc.

Taking Advantage of Electrostatic Interactions To Grow Langmuir-Blodgett Films Containing Multilayers of the Phospholipid Dipalmitoylphosphatidylglycerol

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

Natural Polysaccharides as Active Biomaterials in Nanostructured Films for Sensing

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

Effect of Gamma Irradiation on Caprolactam Migration from Multi layer Polyamide 6 Films into Food Simulants: Development and Validation of a Gas Chromatographic Method

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Automatic detection of thermal damage in grinding process by artificial neural network

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.

Wear Particle Classifier System Based on an Artificial Neural Network

This paper describes a method of identifying morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others. (C) 2010 Journal of Mechanical Engineering. All rights reserved.

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Analysis of Acid Alizarin Violet N Dye Removal Using Sugarcane Bagasse as Adsorbent

With the development of the textile industry, there has been a demand for dye removal from contaminated effluents. In recent years, attention has been directed toward various natural solid materials that are capable of removing pollutants from contaminated water at low cost. One such material is sugarcane bagasse. The aim of the present study was to evaluate adsorption of the dye Acid Violet Alizarin N with different concentrations of sugarcane bagasse and granulometry in agitated systems at different pH. The most promising data (achieved with pH 2.5) was analyzed with both Freundlich and Langmuir isotherms equations. The model that better fits dye adsorption interaction into sugarcane bagasse is Freundlich equation, and thus the multilayer model. Moreover, a smaller bagasse granulometry led to greater dye adsorption. The best treatment was achieved with a granulometry value lower than 0.21 mm at pH 2.50, in which the total removal was estimated at a concentration of 16.25 mg mL(-1). Hence, sugarcane bagasse proves to be very attractive for dye removal from textile effluents.