Modelagem e simulação de um separador bifásico com inversão de fases induzida

The present work has the main goal to study the modeling and simulation of a biphasic separator with induced phase inversion, the MDIF, with the utilization of the finite differences method for the resolution of the partial differencial equations which describe the transport of contaminant s mass fraction inside the equipment s settling chamber. With this aim, was developed the deterministic differential model AMADDA, wich was admensionalizated and then semidiscretizated with the method of lines. The integration of the resultant system of ordinary differential equations was realized by means of a modified algorithm of the Adam-Bashfort- Moulton method, and the sthocastic optimization routine of Basin-Hopping was used in the model s parameter estimation procedure . With the aim to establish a comparative referential for the results obtained with the model AMADDA, were used experimental data presented in previous works of the MDIF s research group. The experimental data and those obtained with the model was assessed regarding its normality by means of the Shapiro-Wilk s test, and validated against the experimental results with the Student s t test and the Kruskal-Wallis s test, depending on the result. The results showed satisfactory performance of the model AMADDA in the evaluation of the MDIF s separation efficiency, being possible to determinate that at 1% significance level the calculated results are equivalent to those determinated experimentally in the reference works

Estudo da recuperação de óleo por drenagem gravitacional assistida por injeção de vapor

Steam assisted gravity drainage process (SAGD) involves two parallel horizontal wells located in a same vertical plane, where the top well is used as steam injector and the bottom well as producer. The dominant force in this process is gravitational. This improved oil recovery method has been demonstrated to be economically viable in commercial projects of oil recovery for heavy and extra heavy oil, but it is not yet implemented in Brazil. The study of this technology in reservoirs with characteristics of regional basins is necessary in order to analyze if this process can be used, minimizing the steam rate demand and improving the process profitability. In this study, a homogeneous reservoir was modeled with characteristics of Brazilian Northeast reservoirs. Simulations were accomplished with STARS , a commercial software from Computer Modelling Group, which is used to simulate improved oil recovery process in oil reservoirs. In this work, a steam optimization was accomplished in reservoirs with different physical characteristics and in different cases, through a technical-economic analysis. It was also studied a semi-continuous steam injection or with injection stops. Results showed that it is possible to use a simplified equation of the net present value, which incorporates earnings and expenses on oil production and expenses in steam requirement, in order to optimize steam rate and obtaining a higher net present value in the process. It was observed that SAGD process can be or not profitable depending on reservoirs characteristics. It was also obtained that steam demand can still be reduced injecting in a non continuous form, alternating steam injection with stops at several time intervals. The optimization of these intervals allowed to minimize heat losses and to improve oil recovery

Viabilidade técnica de uma rota não convencional para a produção de leite de cabra em pó em cooperativas do Rio Grande do Norte

Nowadays, Brazil has both the greatest goat herd and the greatest goat milk production of South America. The state of Rio Grande do Norte, located in northeast of Brazil, has an average year production of three thousand cubic meters of goat milk in natura. Part of this milk production is homemade and it comes from small farms, which unite in rural cooperatives created to encourage the production and implementation of industrial processes for preservation and processing of milk. Results presented by literature and obtained from preliminary essays in this thesis show that non conventional dryer of spouted bed with inert particles is able to produce powder milk from in natura milk (cattle or goat), with the same quality of spray dryer, however, operating at low cost. The method of drying in spouted bed consists of injecting milk emulsion on the bed of inert particles gushed by hot air. This emulsion covers the particles with a thin film, which dries and is reduced to powder during the circulation of inerts inside the bed. The powder is dragged by exhaustion air and separated in the cyclone. The friction among particles resulted from the particles circulation, encourages high taxes of shear in the thin film of emulsion, breaking the cohesive forces and making this process possible. Studying the drying process and the powder goat milk production in one unit of spouted bed with inert particles, seeing the development of a low cost technological route for powder milk production is the aim of this thesis. The powder milk produced by this route must attend the local demand of food industries which need an intermediate product to be used as a food ingredient (ice-cream, milk candy). In order to reach this aim, this thesis approaches the aspects related to physical, thermodynamics and physic-chemicals characteristics of goat milk, whose complete data are still inexistent in the literature. The properties of materials are of great importance to the project of any process which involves the operations of transportation of movement, heat and mass quantity, such as the dryers which operate in fluid dynamically active regime, like the spouted bed. It was obtained new data related to the goat milk properties in function of concentration of solids and temperature. It is also important to mention the study developed about the kinetic of solids retention in the bed of inert particles during the drying of goat milk. It was found more adequate processes conditions to the proposed technological route to be implemented in small and micro-industries, with simplifications in the system of milk injection as well as in the form of operation of the dryer. Important data were obtained for a posterior stage of this research which involves the v modeling, simulation, control and optimization of the process. The results obtained in this thesis, in relation to process performance as well as to the quality of produced powder milk validate the proposal of using the spouted bed dryer in the production of powder goat milk

Three-Dimensional Semiautomatic Road Extraction From a High-Resolution Aerial Image by Dynamic-Programming Optimization in the Object Space

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

Toward the Optimization of an e-Tongue System Using Information Visualization: A Case Study with Perylene Tetracarboxylic Derivative Films in the Sensing Units

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

Numerical simulation of drop impact and jet buckling problems using the eXtended Pom-Pom model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multivariate optimization and validation of an analytical methodology by RP-HPLC for the determination of losartan potassium in capsules

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Static simulation of bulk and selected surfaces of anatase TiO2

A theoretical investigation has been carried out to characterize bulk and selected surfaces of anatase TiO2. The calculations are performed using a B3LYP hybrid functional and 6-31G basis set within the periodic density functional approximation. Optimization procedures have been employed to determine the equilibrium geometry of the crystal and slab surface models. The compressibility, band structure, and the bulk and surface charge distributions are reported. The surface relative energies are identified to follow the sequence: (001) < (101) < (100) much less than (110) < < < (111), from the most stable surface to the least stable one. Relaxation of (001) and (101) surfaces are moderate, with no displacements exceeding; approximate to0.19 Angstrom. The theoretical results are compared with previous theoretical studies and available experimental data. (C) 2001 Elsevier B.V. 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.

Stability and convergence analysis of a neural model applied in nonlinear systems optimization

A neural model for solving nonlinear optimization problems is presented in this paper. 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 network is shown to be completely stable and globally convergent to the solutions of nonlinear optimization problems. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are presented to validate the developed methodology.

A novel approach for solving constrained nonlinear optimization problems using neurofuzzy systems

A neural network model for solving constrained nonlinear optimization problems with bounded variables is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are completed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of constrained nonlinear optimization problems. A fuzzy logic controller is incorporated in the network to minimize convergence time. Simulation results are presented to validate the proposed approach.

Design and analysis of an efficient neural network model for solving nonlinear optimization problems

This paper presents an efficient approach based on a recurrent neural network for solving constrained 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 handles optimization and constraint terms in different stages with no interference from each other. Moreover, the proposed approach does not require specification for penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyse its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network.

Numerical simulation of magnetic field enhanced plasma immersion ion implantation

The behavior of plasma and sheath characteristics under the action of an applied magnetic field is important in many applications including plasma probes and material processing. Plasma immersion ion implantation (PIII) has been developed as a fast and efficient surface modification technique of complex shaped three-dimensional objects. The PIII process relies on the acceleration of ions across a high-voltage plasma sheath that develops around the target. Recent studies have shown that the sheath dynamics is significantly affected by an external magnetic field. In this work we describe a two-dimensional computer simulation of magnetic field enhanced plasma immersion implantation system. Negative bias voltage is applied to a cylindrical target located on the axis of a grounded cylindrical vacuum chamber filled with uniform nitrogen plasma. An axial magnetic field is created by a solenoid installed inside the cylindrical target. The computer code employs the Monte Carlo method for collision of electrons and neutrals in the plasma and a particle-in-cell (PIC) algorithm for simulating the movement of charged particles in the electromagnetic field. Secondary electron emission from the target subjected to ion bombardment is also included. It is found that a high-density plasma region is formed around the cylindrical target due to the intense background gas ionization by the magnetized electrons drifting in the crossed ExB fields. An increase of implantation current density in front of high density plasma region is observed. (C) 2007 Elsevier B.V. All rights reserved.

A Beam Search Method to Solve the Problem of Assignment Cells to Switches in a Cellular Mobile Network

Assigning cells to switches in a cellular mobile network is known as an NP-hard optimization problem. This means that the alternative for the solution of this type of problem is the use of heuristic methods, because they allow the discovery of a good solution in a very satisfactory computational time. This paper proposes a Beam Search method to solve the problem of assignment cell in cellular mobile networks. Some modifications in this algorithm are also presented, which allows its parallel application. Computational results obtained from several tests confirm the effectiveness of this approach and provide good solutions for large scale problems.

Interior point method for long-term generation scheduling of large-scale hydrothermal systems

This paper presents an interior point method for the long-term generation scheduling of large-scale hydrothermal systems. The problem is formulated as a nonlinear programming one due to the nonlinear representation of hydropower production and thermal fuel cost functions. Sparsity exploitation techniques and an heuristic procedure for computing the interior point method search directions have been developed. Numerical tests in case studies with systems of different dimensions and inflow scenarios have been carried out in order to evaluate the proposed method. Three systems were tested, with the largest being the Brazilian hydropower system with 74 hydro plants distributed in several cascades. Results show that the proposed method is an efficient and robust tool for solving the long-term generation scheduling problem.