Finishing of flat parts led by lapping kinematics on abrasive disc dressed in agreement with overlap factors

This paper discusses the investigation of an abrasive process for finishing flat workpieces, based on the combination of important grinding and lapping characteristics. Instead of loose abrasive grains between the workpiece and the lapping plate, a resinoid grinding wheel of hot-pressed silicon carbide is placed on the plate of a device resembling a lapping machine. The resin bond grinding wheel is dressed with a single-point diamond. In addition to keeping the plate flat, dressing also plays the role of interfering in the behavior of the process by varying the overlap factor (Ud). It was found that the studied process simplify the set-up and can be controlled more easily than in lapping, whose is a painstaking process. The surface roughness and flatness deviation proved comparable to those of lapping, or even finer than it, with the additional advantage of a less contaminated workpiece surface with a shiny appearance. The process was also monitored by acoustic emission (AE), which indicates to be a promissing and suitable technique for use in this process. Copyright © 2008 by ASME.

Running behavior and its energy cost in mice selectively bred for high voluntary locomotor activity

Locomotion is central to behavior and intrinsic to many fitnesscritical activities (e.g., migration, foraging), and it competes with other life-history components for energy. However, detailed analyses of how changes in locomotor activity and running behavior affect energy budgets are scarce. We quantified these effects in four replicate lines of house mice that have been selectively bred for high voluntary wheel running (S lines) and in their four nonselected control lines (C lines). We monitored wheel speeds and oxygen consumption for 24-48 h to determine daily energy expenditure (DEE), resting metabolic rate (RMR), locomotor costs, and running behavior (bout characteristics). Daily running distances increased roughly 50%-90% in S lines in response to selection. After we controlled for body mass effects, selection resulted in a 23% increase in DEE in males and a 6% increase in females. Total activity costs (DEE - RMR) accounted for 50%-60% of DEE in both S and C lines and were 29% higher in S males and 5% higher in S females compared with their C counterparts. Energetic costs of increased daily running distances differed between sexes because S females evolved higher running distances by running faster with little change in time spent running, while S males also spent 40% more time running than C males. This increase in time spent running impinged on high energy costs because the majority of running costs stemmed from postural costs (the difference between RMR and the zero-speed intercept of the speed vs. metabolic rate relationship). No statistical differences in these traits were detected between S and C females, suggesting that large changes in locomotor behavior do not necessarily effect overall energy budgets. Running behavior also differed between sexes: within S lines, males ran with more but shorter bouts than females. Our results indicate that selection effects on energy budgets can differ dramatically between sexes and that energetic constraints in S males might partly explain the apparent selection limit for wheel running observed for over 15 generations. © 2009 by The University of Chicago. All rights reserved.

Microstructural effects on fatigue crack growth behavior of a microalloyed steel

Thermal transformations on microalloyed steels can produce multiphase microstructures with different amounts of ferrite, martensite, bainite and retained austenite. These different phases, with distinct morphologies, are determinant of the mechanical behavior of the steel and can, for instance, affect the crack path or promote crack shielding, thus resulting in changes on its propagation rate under cyclic loading. The aim of the present work is to evaluate the effects of microstructure on the tensile strength and fatigue crack growth (FCG) behaviour of a 0.08%C-1,5%Mn (wt. pct.) microalloyed steel, recently developed by a Brazilian steel maker under the designation of RD480. This steel is being considered as a promising alternative to replace low carbon steel in wheel components for the automotive industry. Various microstructural conditions were obtained by means of heat treatments followed by water quench, in which the material samples were kept at the temperatures of 800, 950 and 1200 °C. In order to describe the FCG behavior, two models were tested: the conventional Paris equation and a new exponential equation developed for materials showing non-linear FCG behavior. The results allowed correlating the tensile properties and crack growth resistance to the microstructural features. It is also shown that the Region II FCG curves of the dual and multiphase microstructural conditions present crack growth transitions that are better modeled by dividing them in two parts. The fracture surfaces of the fatigued samples were observed via scanning electron microscopy in order to reveal the fracture mechanisms presented by the various material conditions. © 2010 Published by Elsevier Ltd.

Desempenho de semeadora-adubadora em função do prepa ro de solo e espa çamento da cultura do milho

The performance of machines and agricultural implements are of fundamental importance, especially when subjected to different types of soil tillage, and have to adapt to these conditions, in order to promote good operational performance. The objective of this study was to analyze the operational performance of a Marchesan Supreme Cop grain drill, equipped with four rows, spaced 0.90 m, according to three types of tillage: conventional tillage (plowing and two harrowing series), reduced tillage (scarification with a roller), and no-tillage, in areas previously seeded with maize (Zea mays L.), at two spacing measures (0.90 m and 0.45 m). The results indicate that the demand for power, tensile stress, and motor rotation, in the sowing operation, were not influenced by tillage and maize crop. The tractor wheel slip showed different results, being lower in no-tillage and higher in conventional and reduced tillage.

Informative Radio Models in Brazil: The All-News Networks

This study analyzes the particularities of Brazilian radio networks that adopt the all-news format and briefly presents the main national and international experiences for the implementation of the model and its conceptualization. Besides the bibliographic review, we use the multiple-case study, analyzing as the empirical objects CBN and BandNews FM networks. Also, we apply methodological procedures of systematic non-participant observation, supplemented by interviews and surveys. We conclude that the different all-news programming models and network organizations influence the processes of production, information structure, broadcasting language, and therefore the stations' profile. © 2011 Copyright Taylor and Francis Group, LLC.

Anfis applied to the prediction of surface roughness in grinding of advanced ceramics

This paper introduces a methodology for predicting the surface roughness of advanced ceramics using Adaptive Neuro-Fuzzy Inference System (ANFIS). To this end, a grinding machine was used, equipped with an acoustic emission sensor and a power transducer connected to the electric motor rotating the diamond grinding wheel. The alumina workpieces used in this work were pressed and sintered into rectangular bars. Acoustic emission and cutting power signals were collected during the tests and digitally processed to calculate the mean, standard deviation, and two other statistical data. These statistics, as well the root mean square of the acoustic emission and cutting power signals were used as input data for ANFIS. The output values of surface roughness (measured during the tests) were implemented for training and validation of the model. The results indicated that an ANFIS network is an excellent tool when applied to predict the surface roughness of ceramic workpieces in the grinding process.

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 de modelos neurais aplicados na estimação de parâmetros da retificação de cerâmicas avançadas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Classificação de níveis de desgaste de dressadores de ponta única utilizando sinais de emissão acústica e redes neurais artificiais

Pós-graduação em Engenharia Elétrica - FEB

Retificação da alumina com rebolo diamantado usando diferentes métodos de lubri-refrigeração

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação de operadores de algoritmos genéticos em otimização multidimensional

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização da acessibilidade em espaços públicos: a ergonomia e o desenho universal contribuindo para a mobilidade de pessoas portadoras de necessidades especiais : estudo de casos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desempenho operacional de um subsolador de hastes com curvatura lateral (“Paraplow”), em função de diferentes velocidades de deslocamento e profundidades de trabalho

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desempenho de semeadoras-adubadoras de milho (Zea mays L.) em sistema de plantio direto

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