Projeto, construção e análise de um prototipo vibracional em escala de bancada aplicável ao tratamento de água de produção de petróleo bruto, mediante inovadora operação híbrida de adsorção e auto-flotação

A self-flotator vibrational prototype electromechanical drive for treatment of oil and water emulsion or like emulsion is presented and evaluated. Oil production and refining to obtain derivatives is carried out under arrangements technically referred to as on-shore and off-shore, ie, on the continent and in the sea. In Brazil 80 % of the petroleum production is taken at sea and area of deployment and it cost scale are worrisome. It is associated, oily water production on a large scale, carrier 95% of the potential pollutant of activity whose final destination is the environment medium, terrestrial or maritime. Although diversified set of techniques and water treatment systems are in use or research, we propose an innovative system that operates in a sustainable way without chemical additives, for the good of the ecosystem. Labyrinth adsor-bent is used in metal spirals, and laboratory scale flow. Equipment and process patents are claimed. Treatments were performed at different flow rates and bands often monitored with control systems, some built, other bought for this purpose. Measurements of the levels of oil and grease (OGC) of efluents treaty remained within the range of legal framework under test conditions. Adsorbents were weighed before and after treatment for obtaining oil impregna-tion, the performance goal of vibratory action and treatment as a whole. Treatment technolo-gies in course are referenced, to compare performance, qualitatively and quantitatively. The vibration energy consumption is faced with and without conventional flotation and self-flotation. There are good prospects for the proposed, especially in reducing the residence time, by capillary action system. The impregnation dimensionless parameter was created and confronted with consecrated dimensionless parameters, on the vibrational version, such as Weber number and Froude number in quadratic form, referred to as vibrational criticality. Re-sults suggest limits to the vibration intensity

Adrien-Marie Legendre (1752-1833) e suas obras em Teoria dos Números

The present thesis is an analysis of Adrien-Marie Legendre s works on Number Theory, with a certain emphasis on his 1830 edition of Theory of Numbers. The role played by these works in their historical context and their influence on the development of Number Theory was investigated. A biographic study of Legendre (1752-1833) was undertaken, in which both his personal relations and his scientific productions were related to certain historical elements of the development of both his homeland, France, and the sciences in general, during the 18th and 19th centuries This study revealed notable characteristics of his personality, as well as his attitudes toward his mathematical contemporaries, especially with regard to his seemingly incessant quarrels with Gauss about the priority of various of their scientific discoveries. This is followed by a systematic study of Lagrange s work on Number Theory, including a comparative reading of certain topics, especially that of his renowned law of quadratic reciprocity, with texts of some of his contemporaries. In this way, the dynamics of the evolution of his thought in relation to his semantics, the organization of his demonstrations and his number theoretical discoveries was delimited. Finally, the impact of Legendre s work on Number Theory on the French mathematical community of the time was investigated. This investigation revealed that he not only made substantial contributions to this branch of Mathematics, but also inspired other mathematicians to advance this science even further. This indeed is a fitting legacy for his Theory of Numbers, the first modern text on Higher Arithmetic, on which he labored half his life, producing various editions. Nevertheless, Legendre also received many posthumous honors, including having his name perpetuated on the Trocadéro face of the Eiffel Tower, which contains a list of 72 eminent scientists, and having a street and an alley in Paris named after him

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

Uma proposta de um controlador adaptativo por posicionamento de pólos e estrutura variável

There are two main approaches for using in adaptive controllers. One is the so-called model reference adaptive control (MRAC), and the other is the so-called adaptive pole placement control (APPC). In MRAC, a reference model is chosen to generate the desired trajectory that the plant output has to follow, and it can require cancellation of the plant zeros. Due to its flexibility in choosing the controller design methodology (state feedback, compensator design, linear quadratic, etc.) and the adaptive law (least squares, gradient, etc.), the APPC is the most general type of adaptive control. Traditionally, it has been developed in an indirect approach and, as an advantage, it may be applied to non-minimum phase plants, because do not involve plant zero-pole cancellations. The integration to variable structure systems allows to aggregate fast transient and robustness to parametric uncertainties and disturbances, as well. In this work, a variable structure adaptive pole placement control (VS-APPC) is proposed. Therefore, new switching laws are proposed, instead of using the traditional integral adaptive laws. Additionally, simulation results for an unstable first order system and simulation and practical results for a three-phase induction motor are shown

Sistema de navegação para robôs móveis autônomos

The main task and one of the major mobile robotics problems is its navigation process. Conceptualy, this process means drive the robot from an initial position and orientation to a goal position and orientation, along an admissible path respecting the temporal and velocity constraints. This task must be accomplished by some subtasks like robot localization in the workspace, admissible path planning, trajectory generation and motion control. Moreover, autonomous wheeled mobile robots have kinematics constraints, also called nonholonomic constraints, that impose the robot can not move everywhere freely in its workspace, reducing the number of feasible paths between two distinct positions. This work mainly approaches the path planning and trajectory generation problems applied to wheeled mobile robots acting on a robot soccer environment. The major dificulty in this process is to find a smooth function that respects the imposed robot kinematic constraints. This work proposes a path generation strategy based on parametric polynomials of third degree for the 'x' and 'y' axis. The 'theta' orientation is derived from the 'y' and 'x' relations in such a way that the generated path respects the kinematic constraint. To execute the trajectory, this work also shows a simple control strategy acting on the robot linear and angular velocities

Algoritmos genéticos aplicados a um comitê de LS-SVM em problemas de classificação

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers

Controlador preditivo não linear aplicado ao controle de golfadas em processos de produção de petróleo

Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC