Tratamento térmico de normalização em tampos de vasos de pressão fabricados de material P275NH

In a market environment increasingly competitive, the companies need to control of this process accurately, avoiding rework or rejection of materials during industrialization. This can be achieved by defining procedure that assure the maintenance of the materials characteristics, as specified initially in the projects. This graduation work has the objective of defining the best heat treatment parameter of normalizing for Heads, part of a pressure vessel, formed in P275NH material. The methodology applied is based on the execution of a sequence of Heat Treatments, using different parameters. The process variables were the cooling velocity, the hold time and the hold temperature variation. As a result of this study, it is noticed that the mechanical properties of the materials are strongly influenced by the hold temperature variation and by the cooling velocity, both determined for the heat treatment cycle

An electrochemical sensor for (L)-dopa based on oxovanadium-salen thin film electrode applied flow injection system

An oxovanadium-salen complex (NAP-ethylene-bis(salicylidenciminato) oxovanadium) thin film deposited on a graphite-polyurethane electrode was investigated with regard to its potential use for detection of L-dopa in flow injection system. The oxovanadium(IV)/oxovanadium(V) redox couple of the modified electrode was found to mediate the L-dopa oxidation before its use in the FIA system. Experimental parameters, such as pH of the carrier solution, flow rate, sample volume injection and probable interferents were investigated. Under the optimized FIA conditions, the amperometric signal was linearly dependent on the L-dopa concentration over the range 1.0 x 10(-1) to 1.0 x 10(-4) mol L-1 (I-anodic, mu A) = 0.01 + 0.25 [L-dopa mu mol L-1]) with a detection limit (S/N = 3) of 8.0 x 10(-7) mol L-1 and a sampling frequency of 90 h(-1) was achieved. For a concentration of 1.0 x 10(-5) mol L-1 L-dopa, the R.S.D. of nine consecutive measurements was 3.7%. (c) 2006 Elsevier B.V. All rights reserved.

Study of the interaction between cardiolipin bilayers and methylene blue in polymer-based Layer-by-Layer and Langmuir films applied as membrane mimetic systems

An increase of the reports involving mimetic systems has been observed. Briefly, these systems use biological phospholipids to exploit specific interactions between membrane-models and drugs. Here, the Layer-by-Layer (LbL) and Langmuir techniques were used to investigate the interaction between cardiolipin (CLP-negative phospholipid) and a cationic-like drug methylene blue (MB). Supported by a cationic polyelectrolyte (PAH), LbL films containing PAH/(CLP + MB) and PAH/(CLP + MB + AgNP) were grown up to 14 bilayers. The optical microscopy analysis revealed a decrease of the CLP vesicle sizes in the presence of MB as a possible consequence of the MB action onto the mechanical properties of the CLP membrane. From FTIR spectra, changes mainly related to peak position and band intensity and shape were observed in the spectra from PAH/CLP when in the presence of MB. The latter supports that the interactions between the phosphate and amine charged groups from CLP and PAH, respectively, established during the LbL film fabrication, besides the CLP hydrocarbon environment, are influenced by the presence of MB. Using the micro-Raman technique, a chemical mapping was build based on MB spectrum by resonance Raman scattering (RRS) and surface-enhanced resonance Raman scattering (SERRS). The later phenomenon was activated by Ag nanoparticles (AgNPs) trapped within the LbL film allowing collecting spectra for a single bilayer of PAH/(CLP + MB + AgNP). A rough estimation showed a SERRS amplification of 10(3) in comparison to RRS spectra. As a complementary approach, Langmuir films of CLP in the presence of co-spread MB were investigated through surface pressure vs mean molecular area (pi-A) isotherms. The results showed that for concentrations of MB below 100 mol%, the drug is expelled to water subphase for high values of surface pressure (condensed phase). For concentration at 100% and higher, the MB keeps bound to CLP floating monolayer. (C) 2010 Elsevier B.V. All rights reserved.

A novel approach based on recurrent neural networks applied to nonlinear systems optimization

This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network. (c) 2005 Elsevier B.V. All rights reserved.

A DOE based approach for the design of RBF artificial neural networks applied to prediction of surface roughness in AISI 52100 hardened Steel turning

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimization Strategies Based on Sequential Quadratic Programming Applied for a Fermentation Process for Butanol Production

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

Effect of cerium (IV) ions on the anticorrosion properties of siloxane-poly(methyl methacrylate) based film applied on tin coated steel

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

Biocompatibility of resin-based dental materials applied as liners in deep cavities prepared in human teeth

Background: Since only a few data have been published concerning the effects of resinous dental materials on the pulp-dentin complex, the aim of this study was to evaluate the biocompatibility of resin-based materials applied as liners in deep cavities prepared in duman teeth. Methods: After preparing class V cavities, the following dental materials were applied on the axial walls: group 1, Vitrebond™ (VIT; 3M ESPE); group 2, Ultra-Blend® Plus™ (UBP; Untradent); and group 3, Clearfil™ SE Bond (CSEB; Kuraray). In group 4 (control), the hard-setting calcium hydroxide cement Dycal (CH; Caulk/Dentsply) was used. The teeth extracted at 7 days or between 30 and 85 days after the clinical procedures were processed for histological evaluation. Results: For all the experimental and control groups, most of specimens exhibited no pulpal response or slight inflammatory reaction associated with slight tissue disorganization at 7-day period. Moderate inflammatory pulpal response occurred only in one tooth (RDT = 262 μm) of group 3 in which transdentinal diffusion of resin components was observed. Conclusion: The resin-based dental cements VIT and UBP as well as the bonding agent CSEB presented acceptable biocompatibility when applied in deep cavities prepared in sound human teeth. © 2006 Wiley Periodicals, Inc.

Knowledge-based integrated Production Management Model applied to automotive companies

This paper aims to examine the relevance of a production management model, in the shop-floor operations environment, that integrates the dimensions of production organisation (lean and mass production), work organisation (enriched and semi-autonomous groups) and knowledge management. A theoretical model has been applied to automotive companies to verify model adherence. Each of those dimensions has been described by factors. Shop-floor personnel interviews were conducted to confirm the factors relevance to that company. Results have shown that the model represented the reality of those companies concerning the researched dimensions. The factors allow managers to promote a favourable context for knowledge sharing. © 2010 Inderscience Enterprises Ltd.

Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company

Due to an increased awareness and significant environmental pressures from various stakeholders, companies have begun to realize the significance of incorporating green practices into their daily activities. This paper proposes a framework using Fuzzy TOPSIS to select green suppliers for a Brazilian electronics company; our framework is built on the criteria of green supply chain management (GSCM) practices. An empirical analysis is made, and the data are collected from a set of 12 available suppliers. We use a fuzzy TOPSIS approach to rank the suppliers, and the results of the proposed framework are compared with the ranks obtained by both the geometric mean and the graded mean methods of fuzzy TOPSIS methodology. Then a Spearman rank correlation coefficient is used to find the statistical difference between the ranks obtained by the three methods. Finally, a sensitivity analysis has been performed to examine the influence of the preferences given by the decision makers for the chosen GSCM practices on the selection of green suppliers. Results indicate that the four dominant criteria are Commitment of senior management to GSCM; Product designs that reduce, reuse, recycle, or reclaim materials, components, or energy; Compliance with legal environmental requirements and auditing programs; and Product designs that avoid or reduce toxic or hazardous material use. © 2013 Elsevier B.V. All rights reserved.

An innovative material based on natural rubber and leather tannery waste to be applied as antistatic flooring

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

Nonlinear formulation based on FEM, Mazars damage criterion and Fick's law applied to failure assessment of reinforced concrete structures subjected to chloride ingress and reinforcements corrosion

Structural durability is an important design criterion, which must be assessed for every type of structure. In this regard, especial attention must be addressed to the durability of reinforced concrete (RC) structures. When RC structures are located in aggressive environments, its durability is strongly reduced by physical/chemical/mechanical processes that trigger the corrosion of reinforcements. Among these processes, the diffusion of chlorides is recognized as one of major responsible of corrosion phenomenon start. To accurate modelling the corrosion of reinforcements and to assess the durability of RC structures, a mechanical model that accounts realistically for both concrete and steel mechanical behaviour must be considered. In this context, this study presents a numerical nonlinear formulation based on the finite element method applied to structural analysis of RC structures subjected to chloride penetration and reinforcements corrosion. The physical nonlinearity of concrete is described by Mazars damage model whereas for reinforcements elastoplastic criteria are adopted. The steel loss along time due to corrosion is modelled using an empirical approach presented in literature and the chloride concentration growth along structural cover is represented by Fick's law. The proposed model is applied to analysis of bended structures. The results obtained by the proposed numerical approach are compared to responses available in literature in order to illustrate the evolution of structural resistant load after corrosion start. (C) 2014 Elsevier Ltd. All rights reserved.

An improved interolog mapping-based computational prediction of protein protein interactions with increased network coverage

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Evolutionary optimization applied for fine-tuning parameter estimation in optical flow-based environments

Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work we have proposed an evolutionary-based framework for such task, thus introducing three techniques for such purpose: Particle Swarm Optimization, Harmony Search and Social-Spider Optimization. The proposed framework has been compared against with the well-known Large Displacement Optical Flow approach, obtaining the best results in three out eight image sequences provided by a public dataset. Additionally, the proposed framework can be used with any other optimization technique.