18 resultados para Quadratic

em Universidade Federal do Rio Grande do Norte(UFRN)


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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

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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

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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

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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

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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

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The petroleum industry, in consequence of an intense activity of exploration and production, is responsible by great part of the generation of residues, which are considered toxic and pollutants to the environment. Among these, the oil sludge is found produced during the production, transportation and refine phases. This work had the purpose to develop a process to recovery the oil present in oil sludge, in order to use the recovered oil as fuel or return it to the refining plant. From the preliminary tests, were identified the most important independent variables, like: temperature, contact time, solvents and acid volumes. Initially, a series of parameters to characterize the oil sludge was determined to characterize its. A special extractor was projected to work with oily waste. Two experimental designs were applied: fractional factorial and Doehlert. The tests were carried out in batch process to the conditions of the experimental designs applied. The efficiency obtained in the oil extraction process was 70%, in average. Oil sludge is composed of 36,2% of oil, 16,8% of ash, 40% of water and 7% of volatile constituents. However, the statistical analysis showed that the quadratic model was not well fitted to the process with a relative low determination coefficient (60,6%). This occurred due to the complexity of the oil sludge. To obtain a model able to represent the experiments, the mathematical model was used, the so called artificial neural networks (RNA), which was generated, initially, with 2, 4, 5, 6, 7 and 8 neurons in the hidden layer, 64 experimental results and 10000 presentations (interactions). Lesser dispersions were verified between the experimental and calculated values using 4 neurons, regarding the proportion of experimental points and estimated parameters. The analysis of the average deviations of the test divided by the respective training showed up that 2150 presentations resulted in the best value parameters. For the new model, the determination coefficient was 87,5%, which is quite satisfactory for the studied system

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Among the heterogeneous catalysts materials made from niobium show up as an alternative to meet the demand of catalysts for biodiesel production. This study aims to evaluate the potential of a heterogeneous catalyst derived from a complex of niobium in the reaction of methyl esterification of oleic acid. The catalyst was synthesized after calcination at different temperatures of a niobium complex ((NH4)3[NbO(C2O4)3].H2O) generating a niobium oxide nanostructure with a different commercial niobium oxide used to synthesize the complex. The commercial niobium oxide, the complex niobium and niobium catalyst were characterized by thermogravimetry (TG and DTA), surface area analysis (BET), scanning electron microscopy (SEM) and X-ray diffraction (XRD), showing the catalyst has researched morphological and crystallographic indicating a catalytic potential higher than that of commercial niobium oxide characteristics. Factorial with central composite design point, with three factors (calcination temperature, molar ratio of alcohol/oleic acid and mass percentage of catalyst) was performed. Noting that the optimal experimental point was given by the complex calcination temperature of 600°C, a molar ratio alcohol/oleic acid of 3.007/1 and the catalyst mass percentage of 7.998%, with a conversion of 22.44% oleic acid in methyl oleate to 60 min of reaction. We performed a composite linear and quadratic regression to determine an optimal statistical point of the reaction, the temperature of calcination of the complex at 450°C, the molar ratio of alcohol/oleic acid 3.3408/1 and mass percentage of catalyst of 7.6833% . Kinetic modeling to estimate parameters for heterogeneous catalysis it set well the experimental results with a final conversion of 85.01% with 42.38% of catalyst and without catalyst at 240 min reaction was performed. Allowing to evaluate the catalyst catalytic studied has the potential to be used in biodiesel production

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The nonionic surfactants when in aqueous solution, have the property of separating into two phases, one called diluted phase, with low concentration of surfactant, and the other one rich in surfactants called coacervate. The application of this kind of surfactant in extraction processes from aqueous solutions has been increasing over time, which implies the need for knowledge of the thermodynamic properties of these surfactants. In this study were determined the cloud point of polyethoxylated surfactants from nonilphenolpolietoxylated family (9,5 , 10 , 11, 12 and 13), the family from octilphenolpolietoxylated (10 e 11) and polyethoxylated lauryl alcohol (6 , 7, 8 and 9) varying the degree of ethoxylation. The method used to determine the cloud point was the observation of the turbidity of the solution heating to a ramp of 0.1 ° C / minute and for the pressure studies was used a cell high-pressure maximum ( 300 bar). Through the experimental data of the studied surfactants were used to the Flory - Huggins models, UNIQUAC and NRTL to describe the curves of cloud point, and it was studied the influence of NaCl concentration and pressure of the systems in the cloud point. This last parameter is important for the processes of oil recovery in which surfactant in solution are used in high pressures. While the effect of NaCl allows obtaining cloud points for temperatures closer to the room temperature, it is possible to use in processes without temperature control. The numerical method used to adjust the parameters was the Levenberg - Marquardt. For the model Flory- Huggins parameter settings were determined as enthalpy of the mixing, mixing entropy and the number of aggregations. For the UNIQUAC and NRTL models were adjusted interaction parameters aij using a quadratic dependence with temperature. The parameters obtained had good adjust to the experimental data RSMD < 0.3 %. The results showed that both, ethoxylation degree and pressure increase the cloudy points, whereas the NaCl decrease

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The aim of the present work is to contribute to the teaching-learning process in Mathematics through an alternative which tries to motivate the student so that he/she will learn the basic concepts of Complex Numbers and realize that they are not pointless. Therefore, this work s general objective is to construct a didactic sequence which contains structured activities that intends to build up, in each student s thought, the concept of Complex Numbers. The didactic sequence is initially based on a review of the main historical aspects which begot the construction of those numbers. Based on these aspects, and the theories of Richard Skemp, was elaborated a sequence of structured activities linked with Maths history, having the solution of quadratic equations as a main starting point. This should make learning more accessible, because this concept permeates the students previous work and, thus, they should be more familiar with it. The methodological intervention began with the application of that sequence of activities with grade students in public schools who did not yet know the concept of Complex Numbers. It was performed in three phases: a draft study, a draft study II and the final study. Each phase was applied in a different institution, where the classes were randomly divided into groups and each group would discuss and write down the concepts they had developed about Complex Numbers. We also use of another instrument of analysis which consisted of a recorded interview of a semi-structured type, trying to find out the ways the students thought in order to construct their own concepts, i.e. the solutions of the previous activity. Their ideas about Complex Numbers were categorized according to their similarities and then analyzed. The results of the analysis show that the concepts constructed by the students were pertinent and that they complemented each other this supports the conclusion that the use of structured activities is an efficient alternative for the teaching of mathematics

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In this work, the paper of Campos and Dorea [3] was detailed. In that article a Kernel Estimator was applied to a sequence of random variables with general state space, which were independent and identicaly distributed. In chapter 2, the estimator´s properties such as asymptotic unbiasedness, consistency in quadratic mean, strong consistency and asymptotic normality were verified. In chapter 3, using R software, numerical experiments were developed in order to give a visual idea of the estimate process

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Abstract: Several factors can affect the development of the broiler, among them we can highlight nutrition and management. In the context nutritional, mineral supplementation is a necessary practice because, in general, the diets did not contain these elements in sufficient quantity to meet the needs of poultry. Zinc is a trace mineral essential to life, participating in several important functions in the body. Generally zinc is added to diets of birds in inorganic forms (oxides, carbonates or sufatos), however in its organic form or chelated presents more bioavailable. The objective of this study was to evaluate the effect of levels of organic zinc (ZnO) in the diet of broilers from 1 to 42 days, housed in new or reused litter. The experiment was conducted in the poultry sector of the Special Unit for Agricultural Sciences EAJ / UFRN. 576 chicks were used 1 day of commercial strain Cobb, distributed in a completely randomized in a 4x2 factorial arrangement with four levels of ZnO 0, 40, 80 and 120 ppm and two environments, new bed (COn) and reused litter (CRE) resulting in eight treatments with six replications of 12 birds. In the pre-initial responses were linearly increasing levels of ZnO on feed intake and quadratic effect on body weight and weight gain. The levels of 72.41 and 70.05 ppm of ZnO in the diet of chicks improved body weight and weight gain, respectively. There was interaction between ZnO and the type of bedding used. The ZnO did not affect broiler performance in the growing phase. There was an interaction between levels of ZnO and type of bed used. The levels of 61.50 and 85.30 ppm organic zinc improves immunity and increases the deposition of zinc in tibia of broilers at 42 days, respectively. ZnO also increases the resistance of the skin of broilers at 42 days of age. Using Cre improves performance of broilers from 1 to 42 days old

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This study was conducted to evaluate the consumption and digestibility of dry matter (DM), organic matter (OM), crude protein (CP), ether extract (EE), total carbohydrates (TC), non-fiber carbohydrates (NFC) and neutral detergent fiber (NDF) in sheep fed hay moringa (Moringa oleifera Lam) obtained with four cutting ages (28, 35, 42 and 49 days). We used 20 females Morada Nova breed, with 20kg of live weight, distributed in a completely randomized design and maintained in metabolism cages. There was a negative linear effect of age of cutting on DM intake, with an estimated maximum consumption of 0.67 kg / day for the hay produced at 28 days of cutting. It was also observed linear behavior, with an estimated maximum consumption 172g/dia, 0.36 kg / day; 18g/dia, at 35, 42 and 49 days old, for CP, OM and EE, respectively. For NDF, quadratic effect was found with advancing maturity of the plant. The apparent digestibility of DM, CP, OM and TC linearly decreased with advancing age of cutting hay Moringa oleifera. It was concluded that the hay Moringa oleifera showed better nutritional value after 28 days of cutting

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The Quadratic Minimum Spanning Tree Problem (QMST) is a version of the Minimum Spanning Tree Problem in which, besides the traditional linear costs, there is a quadratic structure of costs. This quadratic structure models interaction effects between pairs of edges. Linear and quadratic costs are added up to constitute the total cost of the spanning tree, which must be minimized. When these interactions are restricted to adjacent edges, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). AQMST and QMST are NP-hard problems that model several problems of transport and distribution networks design. In general, AQMST arises as a more suitable model for real problems. Although, in literature, linear and quadratic costs are added, in real applications, they may be conflicting. In this case, it may be interesting to consider these costs separately. In this sense, Multiobjective Optimization provides a more realistic model for QMST and AQMST. A review of the state-of-the-art, so far, was not able to find papers regarding these problems under a biobjective point of view. Thus, the objective of this Thesis is the development of exact and heuristic algorithms for the Biobjective Adjacent Only Quadratic Spanning Tree Problem (bi-AQST). In order to do so, as theoretical foundation, other NP-hard problems directly related to bi-AQST are discussed: the QMST and AQMST problems. Bracktracking and branch-and-bound exact algorithms are proposed to the target problem of this investigation. The heuristic algorithms developed are: Pareto Local Search, Tabu Search with ejection chain, Transgenetic Algorithm, NSGA-II and a hybridization of the two last-mentioned proposals called NSTA. The proposed algorithms are compared to each other through performance analysis regarding computational experiments with instances adapted from the QMST literature. With regard to exact algorithms, the analysis considers, in particular, the execution time. In case of the heuristic algorithms, besides execution time, the quality of the generated approximation sets is evaluated. Quality indicators are used to assess such information. Appropriate statistical tools are used to measure the performance of exact and heuristic algorithms. Considering the set of instances adopted as well as the criteria of execution time and quality of the generated approximation set, the experiments showed that the Tabu Search with ejection chain approach obtained the best results and the transgenetic algorithm ranked second. The PLS algorithm obtained good quality solutions, but at a very high computational time compared to the other (meta)heuristics, getting the third place. NSTA and NSGA-II algorithms got the last positions

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This thesis proposes an architecture of a new multiagent system framework for hybridization of metaheuristics inspired on the general Particle Swarm Optimization framework (PSO). The main contribution is to propose an effective approach to solve hard combinatory optimization problems. The choice of PSO as inspiration was given because it is inherently multiagent, allowing explore the features of multiagent systems, such as learning and cooperation techniques. In the proposed architecture, particles are autonomous agents with memory and methods for learning and making decisions, using search strategies to move in the solution space. The concepts of position and velocity originally defined in PSO are redefined for this approach. The proposed architecture was applied to the Traveling Salesman Problem and to the Quadratic Assignment Problem, and computational experiments were performed for testing its effectiveness. The experimental results were promising, with satisfactory performance, whereas the potential of the proposed architecture has not been fully explored. For further researches, the proposed approach will be also applied to multiobjective combinatorial optimization problems, which are closer to real-world problems. In the context of applied research, we intend to work with both students at the undergraduate level and a technical level in the implementation of the proposed architecture in real-world problems

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The objective of this dissertation is the development of a general formalism to analyze the thermodynamical properties of a photon gas under the context of nonlinear electrodynamics (NLED). To this end it is obtained, through the systematic analysis of Maxwell s electromagnetism (EM) properties, the general dependence of the Lagrangian that describes this kind of theories. From this Lagrangian and in the background of classical field theory, we derive the general dispersion relation that photons must obey in terms of a background field and the NLED properties. It is important to note that, in order to achieve this result, an aproximation has been made in order to allow the separation of the total electromagnetic field into a strong background electromagnetic field and a perturbation. Once the dispersion relation is in hand, the usual Bose-Einstein statistical procedure is followed through which the thermodynamical properties, energy density and pressure relations are obtained. An important result of this work is the fact that equation of state remains identical to the one obtained under EM. Then, two examples are made where the thermodynamic properties are explicitly derived in the context of two NLED, Born-Infelds and a quadratic approximation. The choice of the first one is due to the vast appearance in literature and, the second one, because it is a first order approximation of a large class of NLED. Ultimately, both are chosen because of their simplicity. Finally, the results are compared to EM and interpreted, suggesting possible tests to verify the internal consistency of NLED and motivating further developement into the formalism s quantum case