Modelagem e simulação de um sistema de bombeio mecânico em poços direcionais utilizando parâmetros concentrados

This work aims presenting the development of a model and computer simulation of a sucker rod pumping system. This system take into account the well geometry, the flow through the tubing, the dynamic behavior of the rod string and the use of a induction motor model. The rod string were modeled using concentrated parameters, allowing the use of ordinary differential equations systems to simulate it s behavior

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

Simulação computacional da interação fluido-estrutura em bombas de cavidades progressivas

The pumping through progressing cavities system has been more and more employed in the petroleum industry. This occurs because of its capacity of elevation of highly viscous oils or fluids with great concentration of sand or other solid particles. A Progressing Cavity Pump (PCP) consists, basically, of a rotor - a metallic device similar to an eccentric screw, and a stator - a steel tube internally covered by a double helix, which may be rigid or deformable/elastomeric. In general, it is submitted to a combination of well pressure with the pressure generated by the pumping process itself. In elastomeric PCPs, this combined effort compresses the stator and generates, or enlarges, the clearance existing between the rotor and the stator, thus reducing the closing effect between their cavities. Such opening of the sealing region produces what is known as fluid slip or slippage, reducing the efficiency of the PCP pumping system. Therefore, this research aims to develop a transient three-dimensional computational model that, based on single-lobe PCP kinematics, is able to simulate the fluid-structure interaction that occurs in the interior of metallic and elastomeric PCPs. The main goal is to evaluate the dynamic characteristics of PCP s efficiency based on detailed and instantaneous information of velocity, pressure and deformation fields in their interior. To reach these goals (development and use of the model), it was also necessary the development of a methodology for generation of dynamic, mobile and deformable, computational meshes representing fluid and structural regions of a PCP. This additional intermediary step has been characterized as the biggest challenge for the elaboration and running of the computational model due to the complex kinematic and critical geometry of this type of pump (different helix angles between rotor and stator as well as large length scale aspect ratios). The processes of dynamic generation of meshes and of simultaneous evaluation of the deformations suffered by the elastomer are fulfilled through subroutines written in Fortan 90 language that dynamically interact with the CFX/ANSYS fluid dynamic software. Since a structural elastic linear model is employed to evaluate elastomer deformations, it is not necessary to use any CAE package for structural analysis. However, an initial proposal for dynamic simulation using hyperelastic models through ANSYS software is also presented in this research. Validation of the results produced with the present methodology (mesh generation, flow simulation in metallic PCPs and simulation of fluid-structure interaction in elastomeric PCPs) is obtained through comparison with experimental results reported by the literature. It is expected that the development and application of such a computational model may provide better details of the dynamics of the flow within metallic and elastomeric PCPs, so that better control systems may be implemented in the artificial elevation area by PCP

Sistema microemulsionado: caracterização e aplicação na indústria de petróleo

Alkyl polyethoxylates are surfactants widely used in vastly different fields, from oil exploitation to pharmaceutical applications. One of the most interesting characteristics of these surfactants is their ability to form micellar systems with specific geometry, the so-called wormlike micelle. In this work, microemulsions with three distinct compositions (C/T = 40 %, 30 % and 25 %) was used with contain UNITOL / butanol / water / xylene, cosurfactant / surfactante (C/S) ratio equal to 0,5. The microemulsion was characterized by dynamic light scattering (DLS), capillary viscometry, torque rheometry and surface tensiometry experiments carried out with systems based on xylene, water, butanol (cosurfactant) and nonaethyleneglycolmonododecyl ether (surfactant), with fixed surfactant:cosurfactant:oil composition (with and without oil phase) and varying the overall concentration of the microemulsion. The results showed that a transition from wormlike micelles to nanodrops was characterized by maximum relative viscosity (depending on how relative viscosity was defined), which was connected to maximum effective diameter, determined by DLS. Surface tension suggested that adsorption at the air water interface had a Langmuir character and that the limiting value of the surfactant surface excess was independent of the presence of cosurfactant and xylene. The results of the solubilization of oil sludge and oil recovery with the microemulsion: C/S = 40%, 30% and 25% proved to be quite effective in solubilization of oil sludge, with the percentage of solubilization (%solubilization) as high as 92.37% and enhanced oil recovery rates up to 90.22% for the point with the highest concentration of active material (surfactant), that is, 40%.

Controle ativo de vibração em estruturas inteligentes utilizando um controlador por modos deslizantes com compensação difusa

Smart structures and systems have the main purpose to mimic living organisms, which are essentially characterized by an autoregulatory behavior. Therefore, this kind of structure has adaptive characteristics with stimulus-response mechanisms. The term adaptive structure has been used to identify structural systems that are capable of changing their geometry or physical properties with the purpose of performing a specific task. In this work, a sliding mode controller with fuzzy inference is applied for active vibration control in an SMA two-bar truss. In order to obtain a simpler controller, a polynomial model is used in the control law, while a more sophisticated version, which presents close agreement with experimental data, is applied to describe the SMA behavior of the structural elements. This system has a rich dynamic response and can easily reach a chaotic behavior even at moderate loads and frequencies. Therefore, this approach has the advantage of not only obtaining a simpler control law, but also allows its robustness be evidenced. Numerical simulations are carried out in order to demonstrate the control system performance.

Controle ativo de vibração em estruturas inteligentes utilizando um controlador por modos deslizantes com compensação difusa

Smart structures and systems have the main purpose to mimic living organisms, which are essentially characterized by an autoregulatory behavior. Therefore, this kind of structure has adaptive characteristics with stimulus-response mechanisms. The term adaptive structure has been used to identify structural systems that are capable of changing their geometry or physical properties with the purpose of performing a specific task. In this work, a sliding mode controller with fuzzy inference is applied for active vibration control in an SMA two-bar truss. In order to obtain a simpler controller, a polynomial model is used in the control law, while a more sophisticated version, which presents close agreement with experimental data, is applied to describe the SMA behavior of the structural elements. This system has a rich dynamic response and can easily reach a chaotic behavior even at moderate loads and frequencies. Therefore, this approach has the advantage of not only obtaining a simpler control law, but also allows its robustness be evidenced. Numerical simulations are carried out in order to demonstrate the control system performance.

An automated approach for performance deviation analysis of evolving software systems

A manutenção e evolução de sistemas de software tornou-se uma tarefa bastante crítica ao longo dos últimos anos devido à diversidade e alta demanda de funcionalidades, dispositivos e usuários. Entender e analisar como novas mudanças impactam os atributos de qualidade da arquitetura de tais sistemas é um pré-requisito essencial para evitar a deterioração de sua qualidade durante sua evolução. Esta tese propõe uma abordagem automatizada para a análise de variação do atributo de qualidade de desempenho em termos de tempo de execução (tempo de resposta). Ela é implementada por um framework que adota técnicas de análise dinâmica e mineração de repositório de software para fornecer uma forma automatizada de revelar fontes potenciais – commits e issues – de variação de desempenho em cenários durante a evolução de sistemas de software. A abordagem define quatro fases: (i) preparação – escolher os cenários e preparar os releases alvos; (ii) análise dinâmica – determinar o desempenho de cenários e métodos calculando seus tempos de execução; (iii) análise de variação – processar e comparar os resultados da análise dinâmica para releases diferentes; e (iv) mineração de repositório – identificar issues e commits associados com a variação de desempenho detectada. Estudos empíricos foram realizados para avaliar a abordagem de diferentes perspectivas. Um estudo exploratório analisou a viabilidade de se aplicar a abordagem em sistemas de diferentes domínios para identificar automaticamente elementos de código fonte com variação de desempenho e as mudanças que afetaram tais elementos durante uma evolução. Esse estudo analisou três sistemas: (i) SIGAA – um sistema web para gerência acadêmica; (ii) ArgoUML – uma ferramenta de modelagem UML; e (iii) Netty – um framework para aplicações de rede. Outro estudo realizou uma análise evolucionária ao aplicar a abordagem em múltiplos releases do Netty, e dos frameworks web Wicket e Jetty. Nesse estudo foram analisados 21 releases (sete de cada sistema), totalizando 57 cenários. Em resumo, foram encontrados 14 cenários com variação significante de desempenho para Netty, 13 para Wicket e 9 para Jetty. Adicionalmente, foi obtido feedback de oito desenvolvedores desses sistemas através de um formulário online. Finalmente, no último estudo, um modelo de regressão para desempenho foi desenvolvido visando indicar propriedades de commits que são mais prováveis a causar degradação de desempenho. No geral, 997 commits foram minerados, sendo 103 recuperados de elementos de código fonte degradados e 19 de otimizados, enquanto 875 não tiveram impacto no tempo de execução. O número de dias antes de disponibilizar o release e o dia da semana se mostraram como as variáveis mais relevantes dos commits que degradam desempenho no nosso modelo. A área de característica de operação do receptor (ROC – Receiver Operating Characteristic) do modelo de regressão é 60%, o que significa que usar o modelo para decidir se um commit causará degradação ou não é 10% melhor do que uma decisão aleatória.

An automated approach for performance deviation analysis of evolving software systems

A manutenção e evolução de sistemas de software tornou-se uma tarefa bastante crítica ao longo dos últimos anos devido à diversidade e alta demanda de funcionalidades, dispositivos e usuários. Entender e analisar como novas mudanças impactam os atributos de qualidade da arquitetura de tais sistemas é um pré-requisito essencial para evitar a deterioração de sua qualidade durante sua evolução. Esta tese propõe uma abordagem automatizada para a análise de variação do atributo de qualidade de desempenho em termos de tempo de execução (tempo de resposta). Ela é implementada por um framework que adota técnicas de análise dinâmica e mineração de repositório de software para fornecer uma forma automatizada de revelar fontes potenciais – commits e issues – de variação de desempenho em cenários durante a evolução de sistemas de software. A abordagem define quatro fases: (i) preparação – escolher os cenários e preparar os releases alvos; (ii) análise dinâmica – determinar o desempenho de cenários e métodos calculando seus tempos de execução; (iii) análise de variação – processar e comparar os resultados da análise dinâmica para releases diferentes; e (iv) mineração de repositório – identificar issues e commits associados com a variação de desempenho detectada. Estudos empíricos foram realizados para avaliar a abordagem de diferentes perspectivas. Um estudo exploratório analisou a viabilidade de se aplicar a abordagem em sistemas de diferentes domínios para identificar automaticamente elementos de código fonte com variação de desempenho e as mudanças que afetaram tais elementos durante uma evolução. Esse estudo analisou três sistemas: (i) SIGAA – um sistema web para gerência acadêmica; (ii) ArgoUML – uma ferramenta de modelagem UML; e (iii) Netty – um framework para aplicações de rede. Outro estudo realizou uma análise evolucionária ao aplicar a abordagem em múltiplos releases do Netty, e dos frameworks web Wicket e Jetty. Nesse estudo foram analisados 21 releases (sete de cada sistema), totalizando 57 cenários. Em resumo, foram encontrados 14 cenários com variação significante de desempenho para Netty, 13 para Wicket e 9 para Jetty. Adicionalmente, foi obtido feedback de oito desenvolvedores desses sistemas através de um formulário online. Finalmente, no último estudo, um modelo de regressão para desempenho foi desenvolvido visando indicar propriedades de commits que são mais prováveis a causar degradação de desempenho. No geral, 997 commits foram minerados, sendo 103 recuperados de elementos de código fonte degradados e 19 de otimizados, enquanto 875 não tiveram impacto no tempo de execução. O número de dias antes de disponibilizar o release e o dia da semana se mostraram como as variáveis mais relevantes dos commits que degradam desempenho no nosso modelo. A área de característica de operação do receptor (ROC – Receiver Operating Characteristic) do modelo de regressão é 60%, o que significa que usar o modelo para decidir se um commit causará degradação ou não é 10% melhor do que uma decisão aleatória.