A review of particle transport theory in a binary stochastic medium

A finalidade deste trabalho ´e apresentar uma revis˜ao da teoria do transporte de part´ıculas em meios compostos por uma mistura aleat´oria bin´aria. Para atingir este objetivo n´os apresentamos brevemente alguns conceitos b´asicos de teoria do transporte, e ent˜ao discutimos em detalhes a deriva¸c˜ao de duas abordagens desenvolvidas para a solu¸c˜ao de tais problemas: os modelos de mistura atˆomica e de Levermore-Pomraning. Providenciamos ainda, com o uso da formula¸c˜ao LTSN, compara ¸c˜oes num´ericas destes modelos com resultados de benchmark gerados atrav´es de um processo de Monte Carlo.

Effects of corn particle size and physical form of the diet on the gastrointestinal structures of broiler chickens

The objective of this experiment was to investigate the effects of different particle sizes, expressed as Geometric Mean Diameter (GMD) of corn (0.336mm, 0.585mm, 0.856mm and 1.12mm) of mash and pelleted broiler chicken diets on the weight of the gizzard, duodenum and jejunum+ileum; on the pH of the gizzard and small intestine and on the characteristics of the duodenal mucous layer (number and height of villi and crypt depth) in 42-day-old broilers. The physical form and the particle size of the diet had no significant effect on gizzard and intestine pH (p > 0.05). A greater gizzard weight was seen in the birds receiving pelleted diet and particle size of 0.336mm (p < 0.008). However, for the particle sizes of 0.856 and 1.12 mm, a greater weight was found in birds that received mash diet (p < 0.039 and p < 0.006, respectively). Also, gizzard weight was greater with increasing corn GMD independent of the physical form of the diet. In the mash diet, the increase in particle size promoted a quadratic response in the weight of duodenum and jejunum + ileum. The pelleted diet promoted a greater number of villi per transverse duodenum cut (p < 0.007) and greater crypt depth (p < 0.05). As the particle size increased, there was a linear increase of villus height and crypt depth in the duodenum, irrespective of the physical form of the diet.

Análise e otimização de superfícies seletivas de Frequência utilizando redes neurais artificiais e algoritmos de otimização natural

The bidimensional periodic structures called frequency selective surfaces have been well investigated because of their filtering properties. Similar to the filters that work at the traditional radiofrequency band, such structures can behave as band-stop or pass-band filters, depending on the elements of the array (patch or aperture, respectively) and can be used for a variety of applications, such as: radomes, dichroic reflectors, waveguide filters, artificial magnetic conductors, microwave absorbers etc. To provide high-performance filtering properties at microwave bands, electromagnetic engineers have investigated various types of periodic structures: reconfigurable frequency selective screens, multilayered selective filters, as well as periodic arrays printed on anisotropic dielectric substrates and composed by fractal elements. In general, there is no closed form solution directly from a given desired frequency response to a corresponding device; thus, the analysis of its scattering characteristics requires the application of rigorous full-wave techniques. Besides that, due to the computational complexity of using a full-wave simulator to evaluate the frequency selective surface scattering variables, many electromagnetic engineers still use trial-and-error process until to achieve a given design criterion. As this procedure is very laborious and human dependent, optimization techniques are required to design practical periodic structures with desired filter specifications. Some authors have been employed neural networks and natural optimization algorithms, such as the genetic algorithms and the particle swarm optimization for the frequency selective surface design and optimization. This work has as objective the accomplishment of a rigorous study about the electromagnetic behavior of the periodic structures, enabling the design of efficient devices applied to microwave band. For this, artificial neural networks are used together with natural optimization techniques, allowing the accurate and efficient investigation of various types of frequency selective surfaces, in a simple and fast manner, becoming a powerful tool for the design and optimization of such structures

Otimização de superfícies seletivas de frequência com elementos pré-fractais utilizando rede neural MLP e algoritmos de busca populacional

This thesis describes design methodologies for frequency selective surfaces (FSSs) composed of periodic arrays of pre-fractals metallic patches on single-layer dielectrics (FR4, RT/duroid). Shapes presented by Sierpinski island and T fractal geometries are exploited to the simple design of efficient band-stop spatial filters with applications in the range of microwaves. Initial results are discussed in terms of the electromagnetic effect resulting from the variation of parameters such as, fractal iteration number (or fractal level), fractal iteration factor, and periodicity of FSS, depending on the used pre-fractal element (Sierpinski island or T fractal). The transmission properties of these proposed periodic arrays are investigated through simulations performed by Ansoft DesignerTM and Ansoft HFSSTM commercial softwares that run full-wave methods. To validate the employed methodology, FSS prototypes are selected for fabrication and measurement. The obtained results point to interesting features for FSS spatial filters: compactness, with high values of frequency compression factor; as well as stable frequency responses at oblique incidence of plane waves. This thesis also approaches, as it main focus, the application of an alternative electromagnetic (EM) optimization technique for analysis and synthesis of FSSs with fractal motifs. In application examples of this technique, Vicsek and Sierpinski pre-fractal elements are used in the optimal design of FSS structures. Based on computational intelligence tools, the proposed technique overcomes the high computational cost associated to the full-wave parametric analyzes. To this end, fast and accurate multilayer perceptron (MLP) neural network models are developed using different parameters as design input variables. These neural network models aim to calculate the cost function in the iterations of population-based search algorithms. Continuous genetic algorithm (GA), particle swarm optimization (PSO), and bees algorithm (BA) are used for FSSs optimization with specific resonant frequency and bandwidth. The performance of these algorithms is compared in terms of computational cost and numerical convergence. Consistent results can be verified by the excellent agreement obtained between simulations and measurements related to FSS prototypes built with a given fractal iteration

Ensaios de tratabilidade aplicados a determinação de parâmetros para dimensionamento de processos de tratamento de água de manancial eutrofizado

Eutrophication is a growing process present in the water sources located in the northeast of Brazil. Among the main consequences of these changes in trophic levels of a water source, stands out adding complexity to the treatment to achieve water standards. By these considerations, this study aimed to define, on a laboratory scale, products and operational conditions to be applied in the processing steps using raw water from Gargalheiras dam, RN, Brazil. The dam mentioned shows a high number of cyanobacteria, with a concentration of cells / ml higher than that established by Decree No. 518/04 MS. The same source was also considered by the state environmental agency in 2009 as hypereutrophic. The static tests developed in this research simulated direct filtration (laboratory filters) and pre-oxidation with chlorine and powdered activated carbon adsorption. The research included the evaluation of the coagulants aluminum hydrochloride (HCA) and alum (SA). The development of the research investigated the conditions for rapid mixing, the dosages of coagulants and pHs of coagulation by the drawing of diagrams. The interference of filtration rate and particle size of filtering means were evaluated as samples and the time of contact were tested with chlorine and activated carbon. By the results of the characterization of the raw water source it was possible to identify the presence of a high pH (7.34). The true color was significant (29 uH) in relation to the apparent color and turbidity (66 uH and 13.60 NTU), reflecting in the measurement of organic matter: MON (8.41 mg.L-1) and Abs254 (0.065 cm-1). The optimization of quick mix set time of 17", the speed gradient of 700 s-1 in the coagulation with HCA and the time of 20" with speed gradient of 800 s-1 for SA. The smaller particle sizes of sand filtering means helped the treatment and the variation in filtration rate did not affect significantly the efficiency of the process. The evaluation of the processing steps found adjustment in standard color and turbidity of the Decree nº 518/04 MS, taking in consideration the average values found in raw water. In the treatment using the HCA for direct filtration the palatable pattern based on the apparent color can be achieved with a dose of 25 mg L-1. With the addition of pre-oxidation step, the standard result was achieved with a reduced dose for 12 mgHCA.L-1. The turbidity standard for water was obtained by direct filtration when the dose exceeds 25 mg L-1 of HCA. With pre-oxidation step there is the possibility of reducing the dose to 20 mg L-1.The addition of CAP adsorption, promoted drinking water for both parameters, with even lower dosage, 13 mg L-1 of HCA. With coagulation using SA removal required for the parameter of apparent color it was achieved with pre-oxidation and 22 mgSA.L-1. Despite the satisfactory results of treatment with the alum, it was not possible to provide water with turbidity less than 1.00 NTU even with the use of all stages of treatment

A route to obtain Gd2O3:Nd3+ with different particle size

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

Photoluminescence of SrTiO3: Influence of Particle Size and Morphology

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

Projections Onto Convex Sets through Particle Swarm Optimization and its application for remote sensing image restoration

Image restoration attempts to enhance images corrupted by noise and blurring effects. Iterative approaches can better control the restoration algorithm in order to find a compromise of restoring high details in smoothed regions without increasing the noise. Techniques based on Projections Onto Convex Sets (POCS) have been extensively used in the context of image restoration by projecting the solution onto hyperspaces until some convergence criteria be reached. It is expected that an enhanced image can be obtained at the final of an unknown number of projections. The number of convex sets and its combinations allow designing several image restoration algorithms based on POCS. Here, we address two convex sets: Row-Action Projections (RAP) and Limited Amplitude (LA). Although RAP and LA have already been used in image restoration domain, the former has a relaxation parameter (A) that strongly depends on the characteristics of the image that will be restored, i.e., wrong values of A can lead to poorly restoration results. In this paper, we proposed a hybrid Particle Swarm Optimization (PS0)-POCS image restoration algorithm, in which the A value is obtained by PSO to be further used to restore images by POCS approach. Results showed that the proposed PSO-based restoration algorithm outperformed the widely used Wiener and Richardson-Lucy image restoration algorithms. (C) 2010 Elsevier B.V. All rights reserved.

Effects Due to a Scalar Coupling on the Particle-Antiparticle Production in the Duffin-Kemmer-Petiau Theory

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Wear Particle Classifier System Based on an Artificial Neural Network

This paper describes a method of identifying morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others. (C) 2010 Journal of Mechanical Engineering. All rights reserved.

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

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

Effects of the particle size and nucleation temperature on tellurite 20Li(2)O-80TeO(2) glass crystallization

20Li(2)O-80TeMO(2) glasses were heat annealed at different temperatures between T-g and T-x and studied by using XRD, FTIR spectroscopy and DSC techniques to understand the crystallization kinetics in this glass matrix. The infrared band structure of this glass is similar to what was observed in glassy TeO2. XRD results reveal the presence of three distinct crystalline gamma-TeO2, alpha-TeO2 and Li2Te2O5 phases during the crystallization process. This is a first report of gamma-TeO2 phase crystallization in this glass matrix. DSC results confinn the crystallization of three distinct structures in the glass. In summary, our results suggest a crystallization hierarchy on this glass matrix since the gamma-TeO2 and alpha-TeO2 phases crystallization occurs before the Li2Te2O5 phase crystallization. (c) 2006 Elsevier B.V. All rights reserved.