Granulometria e textura do milho em dietas para poedeiras comerciais: consumo de energia elétrica, desempenho e qualidade de ovos

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

Aproveitamento de resíduos da indústria de celulose e papel em argamassa mista de revestimento interno

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Simulações por dinâmica molecular fine-e coarse-grained das interações intermoleculares entre peptídeos antimicrobianos da família Mastoparano e membranas modelo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Utilization of teflon and aluminum oxide for wheel cleaning in Minimum Quantity Lubrication (MQL) grinding

Researches concerning cooling-lubrication optimization in grinding have been conducted to contribute to a more sustainable process. An alternative to flood coolant is minimum quantity lubrication (MQL), which spray oil droplets in a compressed air jet. However, problems related to wheel cleaning were reported, due to wheel loading by a mixture of chips and oil, resulting in worsening of surface quality. This work aims to evaluate the viability of Teflon and aluminum oxide for wheel cleaning, compared to MQL without cleaning and MQL with cleaning by compressed air, through the following output variables: surface roughness, roundness, wheel wear, grinding power and acoustic emission. Vickers microhardness measurements and optical microscopy were also carried out. The results showed that both materials were efficient in cleaning the wheel, compared to MQL without cleaning, but not as satisfactory as compressed air. Much work is to be done in order to select the right material for wheel cleaning.

Fine-tuning of a nanostructure, swelling, and drug delivery profile by blending ureasil-PEO and ureasil-PPO hybrids

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Dynamics of soil exploration by fine roots down to a depth of 10 m throughout the entire rotation in Eucalyptus grandis plantations

Although highly weathered soils cover considerable areas in tropical regions, little is known about exploration by roots in deep soil layers. Intensively managed Eucalyptus plantations are simple forest ecosystems that can provide an insight into the belowground growth strategy of fast-growing tropical trees. Fast exploration of deep soil layers by eucalypt fine roots may contribute to achieving a gross primary production that is among the highest in the world for forests. Soil exploration by fine roots down to a depth of 10 m was studied throughout the complete cycle in Eucalyptus grandis plantations managed in short rotation. Intersects of fine roots, less than 1 mm in diameter, and medium-sized roots, 1-3 mm in diameter, were counted on trench walls in a chronosequence of 1-, 2-, 3.5-, and 6-year-old plantations on a sandy soil, as well as in an adjacent 6-year-old stand growing in a clayey soil. Two soil profiles were studied down to a depth of 10 m in each stand (down to 6 m at ages 1 and 2 years) and 4 soil profiles down to 1.5-3.0 m deep. The root intersects were counted on 224 m(2) of trench walls in 15 pits. Monitoring the soil water content showed that, after clear cutting, almost all the available water stored down to a depth of 7 m was taken up by tree roots within 1.1 year of planting. The soil space was explored intensively by fine roots down to a depth of 3 m from 1 year after planting, with an increase in anisotropy in the upper layers throughout the rotation. About 60% of fine root intersects were found at a depth of more than 1 m, irrespective of stand age. The root distribution was isotropic in deep soil layers and kriged maps showed fine root clumping. A considerable volume of soil was explored by fine roots in eucalypt plantations on deep tropical soils, which might prevent water and nutrient losses by deep drainage after canopy closure and contribute to maximizing resource uses.

Utilization of Minimum Quantity Lubrication (MQL) with Water in CBN Grinding of Steel

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

Evaluation of different methods of cooling-lubrication in cylindrical grinding of advanced ceramic dip

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

Neural tool condition estimation in the grinding of advanced ceramics

Ceramic parts are increasingly replacing metal parts due to their excellent physical, chemical and mechanical properties, however they also make them difficult to manufacture by traditional machining methods. The developments carried out in this work are used to estimate tool wear during the grinding of advanced ceramics. The learning process was fed with data collected from a surface grinding machine with tangential diamond wheel and alumina ceramic test specimens, in three cutting configurations: with depths of cut of 120 mu m, 70 mu m and 20 mu m. The grinding wheel speed was 35m/s and the table speed 2.3m/s. Four neural models were evaluated, namely: Multilayer Perceptron, Radial Basis Function, Generalized Regression Neural Networks and the Adaptive Neuro-Fuzzy Inference System. The models'performance evaluation routines were executed automatically, testing all the possible combinations of inputs, number of neurons, number of layers, and spreading. The computational results reveal that the neural models were highly successful in estimating tool wear, since the errors were lower than 4%.

Grinding process monitoring based on electromechanical impedance measurements

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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.

Effect of low-temperature aging on the mechanical behavior of ground Y-TZP

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.

Primary squamous cell carcinoma of the thyroid diagnosed as anaplastic carcinoma: failure in fine-needle aspiration cytology?

A case of primary squamous-cell carcinoma (SCC) of the thyroid which had been initially diagnosed as an anaplastic carcinoma (ATC) is described: female, 73 years old, with a fast-growing cervical nodule on the left side and hoarseness for 3 months. Ultrasonography showed a 4.5 cm solid nodule. FNA was compatible with poorly differentiated carcinoma with immunoreactivity for AE1/AE3, EMA. Thyroidectomy was performed. Histopathological examination showed a nonencapsulated tumor. Immunohistochemistry disclosed positivity for AE1/AE3, p53,p63, and Ki67. The diagnosis was ATC. A second opinion reported tumor consisting of squamous cells, with intense inflammatory infiltrate both in tumor and in the adjacent thyroid, with final diagnosis of SCC, associated with Hashimoto thyroiditis. No other primary focus of SCC was found. Patient has shown a 48-month survival period. Clinically, primary SCCs of the thyroid and ATCs are similar. The distinction is often difficult particularly when based on the cytological analysis of FNA material.

Grinding of AISI 4340 steel with interrupted cutting by aluminum oxide grinding wheel

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