35 resultados para 291400 Materials Engineering


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Recovered substrates have been extensively used in the aerospace field. Cadmium electroplating has been widely applied to promote protective coatings in aeronautical components, resulting in excellent corrosion protection combined with a good performance in cyclic loading. Ecological considerations allied to the increasing demands for corrosion resistance have resulted in the search for possible alternatives. Zinc-nickel (Zn-Ni) alloys have received considerable interest recently, because these coatings show advantages such as a good resistance to white and red rust, high plating rates, and acceptance in the market. In this study, the effect of electroplated Zn-Ni coatings on AISI 4340 high-strength steel was analyzed for rotating bending fatigue strength, corrosion, and adhesion resistance. The compressive residual stress field was measured by x-ray diffraction prior to fatigue tests. Optical microscopy documented coating thickness, adhesion characteristics, and coverage extent for nearly all substrates. Fractured fatigue specimens were investigated using scanning electron microscopy (SEM). Three different Zn-Ni coating thicknesses were tested, and comparisons with the rotating bending fatigue data from electroplated Cd specimens were performed. Experimental results differentiated the effects of the various coatings on the AISI 4340 steel behaviour when submitted to fatigue testing and the influence of coating thickness on the fatigue strength.

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In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function and the Backpropagation algorithm, as an algorithm to train the network. This methodology allows you to make the prediction at various points in power system, considering different types of consumers (residential, commercial, industrial) of the electric grid, is applied to the problem short-term electric load forecasting (24 hours ahead). We use a database (Centralised Dataset - CDS) provided by the Electricity Commission de New Zealand to this work.

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This paper presents the linear optimal control technique for reducing the chaotic movement of the micro-electro-mechanical Comb Drive system to a small periodic orbit. We analyze the non-linear dynamics in a micro-electro-mechanical Comb Drive and demonstrated that this model has a chaotic behavior. Chaos control problems consist of attempts to stabilize a chaotic system to an equilibrium point, a periodic orbit, or more general, about a given reference trajectory. This technique is applied in analyzes the nonlinear dynamics in an MEMS Comb drive. The simulation results show the identification by linear optimal control is very effective.

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The aim of this study was to evaluate the effect of unilateral misfit at different levels on a crown-implant-retention screw system of implant-supported crowns. Hexagon castable UCLA abutments were cast in Co-Cr alloy to fabricate 48 metallic crowns divided into four groups (n = 12). Group A: crowns did not present misfit; Groups B, C and D: crowns were fabricated with unilateral misfit of 50, 100, and 200 mu m, respectively. The crowns were attached by titanium retention screw with 30 N/cm to external hexagonal osseointegrated implants embedded in acrylic resin. After 2 min, the retention screw of each replica was submitted to detorque evaluation by an analogic torque gauge. Three retention screws were used to perform detorque evaluation at each replica and the procedure was repeated twice with each screw. Each group was submitted to 72 detorque measurements. Data were evaluated by ANOVA and Tukey test (P < 0.05). All groups exhibited significant decrease (P < 0.05) in preload and the lowest decrease occurred in Group A. Groups B, C, and D were statistically significant different from Group A (P < 0.05), but there was no statistically significant difference between Groups B and D (P > 0.05). Crowns with unilateral misfit presented higher preload decrease than crowns completely fitted to osseointegrated implants.

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

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Postweld heat treatment (PWHT) is frequently applied to steel pressure vessels, following the requirements of the ASME code (section VIII), which establishes the parameters of the PWHT based on the thickness and chemical composition of the welded section. This work shows the results of an analysis undertaken on a sample of ASTM A537 C1 steel subjected to qualifying welding procedure tests including PWHT (650 degreesC/5 h), the results obtained showed that this PWHT practice promoted a reduction in the mechanical properties of the base metal and the heat-affected zone (HAZ).

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This article reports on a series of experiments with polyethylene terepthalate (PET) treated in a radio frequency plasma reactor using argon and oxygen as a gas fuel, for treatment times equal to 5 s, 20 s, 30 s, and 100 s. The mechanical strength modification of PET fibers, evaluated by tensile tests on monofilaments, showed that oxygen and argon plasma treatment resulted in a decrease in the average tensile strength compared with the untreated fibers. This reduction in tensile strength is more significant for argon plasma and is very sensitive to the treatment time for oxygen plasma. Scanning electron microscopy (SEM) used to analyze the effects of cold plasma treatment on fiber surfaces indicates differences in roughness profiles depending on the type of treatments, which were associated with variations in mechanical strength. Differences in the roughness profile, surveyed through an image analysis method, provided the distance of roughness interval, D-ri. This parameter represents the number of peaks contained in a unit length and was introduced to correlate fiber surface condition, before and after cold plasma treatments, and average tensile strength. Statistical analysis of experimental data, using Weibull cumulative distribution and linear representation, was performed to explain influences of treatment time and environmental effects on mechanical properties. The shape parameter, alpha, and density parameter, beta, from the Weibull distribution function were used to indicate the experimental data range and to confirm the mechanical performance obtained experimentally.

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Pós-graduação em Ciência da Informação - FFC

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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This study aimed to investigate physical performance of particleboards produced with waste from sawmills, containing different wood species, and two adhesives: urea-formaldehyde (UF) based resin and castor-oil (PU) based bi-component polyurethane resin. Panels were produced with nominal density 0.8gcm(-3); pressing temperature 110 degrees C; pressing time 10 min; specific pressure 5 MPa. Water absorption (2 and 24h); thickness swelling (2 and 24h); density; and moisture content were investigated. Results confirmed that the produced panels presented compatible physical properties in comparison with other researches referred in literature, proving the feasibility of inputs employed. Panels produced PU showed better performance than those produced with UF.

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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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Fiber metal laminates (FML) offer significant improvements over current available materials for aircraft structures due to their excellent mechanical characteristics and relatively low density. Non-destructive testing techniques are being used in the characterization of composite materials. Among these, vibration testing is one of the most used tools because it allows the determination of the mechanical properties. In this work, the viscoelastic properties such as elastic (E') and viscous (E) responses were obtained for aluminum 2024 alloy; carbon fiber/epoxy; glass fiber/epoxy and their hybrids aluminum 2024 alloy/carbon fiber/epoxy and aluminum 2024 alloy/glass fiber/epoxy composites. The experimental results were compared to calculated E modulus values by using the composite micromechanics approach. For all specimens studied, the experimental values showed good agreement with the theoretical values. The damping behavior, i.e. The storage modulus and the loss factor, from the aluminum 2024 alloy and fiber epoxy composites can be used to estimate the viscoelastic response of the hybrid FML. (c) 2005 Elsevier Ltd. All rights reserved.

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This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically>30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, two sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with an experimental example, an investigation on a massive quarter scale model of a steel bridge section, in order to verify the performance of this proposed methodology.

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

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