Dielectric thermal analysis as a tool for quantitative-evaluation of the viscosity and the kinetics of epoxy resin cure

Dielectric thermal analysis has been proved as a valuable tool for monitoring the epoxy curing process and the related rheological properties in the fabrication of polymer-matrix composite materials. This technique also has the potential to be applied in the monitoring of magnet impregnation processes as well as in quality control. In this work we present the quantitative evaluation of the viscosity changing and the curing kinetics for a commercial Stycast epoxy resin system at different temperatures through the impedance analysis. The results showed correlation between the real component of the complex impedance and the isothermal reaction extent. Comparing the dielectric analysis result with the viscosity measured by rotational rheometer we observed a similar behavior reported for dynamic mechanic analysis. The results comparison have shown that the kinetics parameters obtained from DSC and DETA analysis showed different sensitivities related to the characteristics of curing stages. We concluded that the dielectric thermal analysis should be applied in quantitative evaluation of cure kinetics.

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Lubricating coating prepared by PIIID on a forming tool

In this work, the performance of a-C: H films produced by the hybrid Plasma Immersion Ion Implantation and Deposition technique as lubricating layers for a steel forming tool has been investigated. Hardened steel (AISI M2, 64 HRC) plates coated with a commercial TiN layer were used as substrates and the films were deposited in a vacuum chamber fitted with two parallel-plate electrodes. The discharges were generated in atmospheres composed of 91% C2H2 and 9% Ar by the application of radiofrequency power (13.56 MHz, 100 W) to the upper electrode while the lower one, also used as the sample holder, was biased with high voltage negative pulses (3.6 kV, 30 mu s, 300 Hz). A deposition time of 840 s was used. The effects of the gas pressure, p, on thickness, molecular structure, wettability, surface morphology and topography, hardness and friction coefficient of the films lwere investigated. Film thickness increased from 0.3 to 0.5 mu m when p was increased from 2.7 to 16.5 Pa. Generally, the films were slightly hydrophilic, with contact angles of around 84 degrees, and the deposition decreased the roughness of the steel. A polymer-like structure was detected in high pressure depositions and an amorphous carbon structure derived from the low pressure procedures. Hardness decreased from 8.2 to 7.0 GPa with increasing p. Improvement in tribological performance was indicated by the fall in the friction coefficient from 0.5 to 0.2 as the deposition pressure was reduced. Operating at the latter value (of mu) would lead to a significant reduction in wear and hence to significant economy in diverse industrial applications.

An easy-learning and easy-teaching tool for indoor thermal analysis - ArcTech

ArcTech is a software being developed, applied and improved with the aim of becoming an efficient sensitization tool to support the teaching-learning process of Architecture courses. The application deals initially with the thermal comfort of buildings. The output generated by the software shows if a student is able to produce a pleasant environment, in terms of thermal sensation along a 24-hours period. Although one can find the very same characteristics in fully-developed commercial software, the reason to create ArcTech is related to the flexibility of the system to be adapted by the instructor and also to the need of simple tools for the evaluation of specific topics along the courses. The first part of ArcTech is dedicated to data management and that was developed using the visual programming language Delphi 7 and Firebird as the database management system. The second part contains the parameters that can be changed by the system administrator and those related to project visualization. The interface of the system, in which the student will learn how to implement and to evaluate the project alternatives, was built using Macromedia Flash. The software was applied to undergraduate students revealing its easy-learning and easy-teaching interface.

Development of ceramic cutting tools for future application on dry machining

Advanced ceramic materials constitute a mature technology with a very broad base of current and potential applications and a growing list of material compositions. Within the advanced ceramics category, silicon nitride based ceramics are wear-resistant, corrosion-resistant and lightweight materials, and are superior to many materials with regard to stability in high-temperature environments. Because of this combination the silicon nitride ceramics have an especially high potential to resolve a wide number of machining problems in the industries. Presently the Si3N4 ceramic cutting tool inserts are developed using additives powders that are pressed and sintered in the form of a cutting tool insert at a temperature of 1850 °C using pressureless sintering. The microstructure of the material was observed and analyzed using XRD, SEM, and the mechanical response of this array microstructure was characterized for hardness Vickers and fracture toughness. The results show that Si3N4/20 wt.% (AlN and Y 2O3) gives the best balance between hardness Vickers and fracture toughness. The Si3N4/15 wt.% (AlN and Y 2O3) composition allows the production of a very fine-grained microstructure with low decreasing of the fracture toughness and increased hardness Vickers. These ceramic cutting tools present adequate characteristics for future application on dry machining. © (2010) Trans Tech Publications.

A visual tool for building synchronous generator capability curves

Synchronous generators are essential components of electric power systems. They are present both in hydro and thermal power plants, performing the function of converting mechanical into electrical energy. This paper presents a visual approach to manipulate parameters that affect operation limits of synchronous generators, using a specifically designed software. The operating characteristics of synchronous generators, for all possible modes of operation, are revised in order to link the concepts to the graphic objects. The approach matches the distance learning tool requirements and also enriches the learning process by developing student trust and understanding of the concepts involved in building synchronous machine capability curves. © 2012 IEEE.

Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Avaliação da freqüência cardíaca nas atividades de colheita de Eucalipto, utilizando a motosserra, como fator para a determinação de pausas adequadas

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

Análise macro e micrográfica da liga AA-356 conforme a taxa de resfriamento

The present work aims to study the characteristics of the alloy Al - 7 % Si - 0 , 3Mg ( AA356 ) , more specifically characterize the macrostructure and microstructure and mechanical properties of the alloy ingots AA356 obtained in metal molds and sand molds for power studying the structures through the difference of cooling rates . This alloy is explained by the fact of referring league has excellent combination of properties such as low solidification shrinkage and good fluidity, good weldability , high wear resistance , high strength to weight ratio, has wide application in general engineering , and particularly in the automotive and aerospace engineering . In this work we will verify this difference in properties through two different cooling rates . We monitor the solid solidification temperatures by thermocouples building with them the cooling curve as a tool that will aid us to evaluate the effectiveness of the grain refining because it achieved with some important properties of the alloy as the latent heat of solidification fraction the liquid and solid temperatures, the total solidification time, and identify the presence of inoculants for grain refinement. Thermal analysis will be supported by the study of graphic software “Origin “will be achieved where the cooling curve and its first derivative that is the cooling rate. Made thermal analysis, analysis will be made in macrographs ingots obtained for observation of macrostructures obtained in both types of ingots and also analysis of micrographs where sampling will occur in strategic positions ingots to correlate with the microstructure. Finally will be collecting data from Brinell hardness of ingots and so then correlating the properties of their respective ingots with cooling rate. We found that obtained with cast metal ingots showed superior properties to the ingots obtained with sand mold

Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks

The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.

Myoglobin from the burrowing reptile Amphisbaena alba: concentrations and functional characteristics

1. 1. Myoglobin from the subterranean reptile Amphisbaena alba was isolated for measurement of concentrations and physico-chemical properties. 2. 2. The concentrations (averaging 12.1 mg.g-1 wet weight in the temporal muscles and 5.8-6.0 in the muscles that motivate the wedge-shaped head which forms the burrowing tool) far exceed those earlier reported for reptiles and other terrestrial vertebrates. 3. 3. The myoglobin has a low O2 affinity compared to mammals (P50 = 2mmHg at 25°C). In the presence of the same myoglobin O2 tension as in mammals this appears to favour similar in vivo O2 saturations at the lower reptilian body temperature. 4. 4. The temperature sensitivity of P50 reflect a heat of oxygenation, ΔH near -13 kcal· mol-1. The myoglobin is monomeric and thus lacks cooperativity in O2 binding and there is no Bohr effect. 5. 5. The pattern of microheterogeneity is similar to that of myoglobin of terrestrial vertebrates but different to aquatic mammals and reptiles. The major and two minor components exhibit very similar O2 affinities. 6. 6. The concentrations and oxygen-binding characteristics of Amphisbaena myoglobin are discussed with regard to the flow of O2 to the mitochondria during digging activity in hypoxic burrow environments. © 1981.

Estudo experimental do uso de rebolos convencionais na usinagem do aço VP-50 utilizado na retificação cilíndrica, por meio de diferentes métodos de lubri-refrigeração

Pós-graduação em Engenharia Mecânica - FEB

Avaliação da erosão hídrica e transporte de sedimentos através do modelo hidrossedimentológico SWAT (Soil and Water Assessment Tool)

Pós-graduação em Geociências e Meio Ambiente - IGCE

Do oral biofilms influence the wear and corrosion behavior of titanium?

The main aim of this work was to study the simultaneous wear-corrosion of titanium (Ti) in the presence of biofilms composed of Streptococcus mutans and Candida albicans. Both organisms were separately grown in specific growth media, and then mixed in a medium supplemented with a high sucrose concentration. Corrosion and tribocorrosion tests were performed after 48 h and 216 h of biofilm growth. Electrochemical corrosion tests indicated a decrease in the corrosion resistance of Ti in the presence of the biofilms although the TiO2 film presented the characteristics of a compact oxide film. While the open circuit potential of Ti indicated a tendency to corrosion in the presence of the biofilms, tribocorrosion tests revealed a low friction on biofilm covered Ti. The properties of the biofilms were similar to those of the lubricant agents used to decrease the wear rate of materials. However, the pH-lowering promoted by microbial species, can lead to corrosion of Ti-based oral rehabilitation systems.