126 resultados para Engenharia de sistemas
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Cementing operation is one of the most important stages in the oil well drilling processes and has main function to form hydraulic seal between the various permeable zones traversed by the well. However, several problems may occur with the cement sheath, either during primary cementing or during the well production period. Cements low resistance can cause fissures in the cement sheath and compromise the mechanical integrity of the annular, resulting in contamination of groundwater and producing zones. Several researches show that biomass ash, in particular, those generated by the sugarcane industry have pozzolanic activity and can be added in the composition of the cementing slurries in diverse applications, providing improvements in mechanical properties, revenue and cement durability. Due to the importance of a low cost additive that increases the mechanical properties in a well cementing operations, this study aimed to potentiate the use of sugarcane bagasse ash as pozzolanic material, evaluate the mechanisms of action of this one on cement pastes properties and apply this material in systems slurries aimed to cementing a well with 800 m depth and geothermal gradient of 1.7 °F/100 ft, as much primary cementing operations as squeeze. To do this, the ash beneficiation methods were realized through the processes of grinding, sifting and reburning (calcination) and then characterization by X-ray fluorescence, XRD, TG / DTG, specific surface area, particle size distribution by laser diffraction and mass specific. Moreover, the ash pozzolanic activity added to the cement at concentrations of 0%, 20% and 40% BWOC was evaluated by pozzolanic activity index with lime and with Portland cement. The evaluation of the pozzolanic activity by XRD, TG / DTG and compressive strength confirmed the ash reactivity and indicated that the addition of 20% in the composition of cement slurries produces improvement 34% in the mechanical properties of the slurry cured. Cement slurries properties evaluated by rheological measurements, fluid loss, free fluid, slurry sedimentation, thickening time and sonic strength (UCA) were satisfactory and showed the viability of using the sugarcane ash in cement slurries composition for well cementing
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Organizations are seeking new ideas, tools and methods aiming to improve management process and performance. On the other hand, system performance measurement needs to portray organizational changes and provide managers with a set of true and more appropriate information for the decision-making process. This work aims to propose a performance measurement system in the academic field regarding Research, Development and Innovation (RDI) in the oil and gas industry. The research performed a bibliographic review in a descriptive exploratory manner. A field research was conducted with an expert focus group in order to gather new indicators. As for the validation of these indicators, a survey with experienced professional was also realized. The research surveyed four segments in and outside of the Federal University of Rio Grande do Norte-Brazil such as oil and gas project coordinators, staff at Academic Planning Offices, FUNPEC employees as well as coordinators from Petrobrás. The performance measuring system created from this study features three interrelated performance indicators pointed out as: process indicators, outcome indicators and global indicators. The proposal includes performance indicators that seek to establish more appropriate strategies for effective institution management. It might help policy making of university-industry interaction policies
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This work provides great contribution to the documental study of the Work Safety courses offered by CEFETs in Brazil, under the perspective of safety management and occupational health, using as a referential the specification OHSAS 18001 (BSI, 1999), as well as directions provided by OIT (ILO, 2001). The theoretical research compares technical and managing competences of the projects of Work Safety courses at CEFETs with the international legislation mentioned above. For field research, questionnaires containing open and close questions were answered by teachers and students aiming at identifying the importance of technical and managing competences for the formation of Work Safety technicians, besides trying to identify which level of minimal formal knowledge should be required to perform managing activities in the area of Work Safety Management Systems and Occupational Health (SGSSO, in Portuguese). The results of the theoretical research point out differences between the projects of the Work Safety technical courses at CEFETs under the perspective of SGSSO. The field research shows that students and teachers opinions converge about most technical and managing competences. In relation to academic formation, the research suggests divergences to the criterion stated by the norm ISO 19011(ABNT, 2002)
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The importance of the airport sector in the development of a country refers to the need for studies on management of airports, to aid the process of decision making. In Brazil, growth in passenger demand is why investments in order to balance the capacity of an airport with air demand. Thus, the study aims to develop a model for Dynamic Systems able to assist airport management in Brazilian sizing subsystems an airport (Passenger Terminal, Runway and Patio). The methodology of this work consists in the steps of defining the problem, formulating the hypothesis dynamic building simulation model, and validation experiments. Finally, we examined the status of each subsystem in thirteen Brazilian airports in scenarios current, most likely and optimistic for air passenger demand
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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This thesis aims at analyzing from the perspective of the manager the importance of the use of quality management tools and concepts in Federal Universities. It was motivated by the following research problem: do Federal University managers consider it to be relevant the quality management in their institution? Therefore, we sought to gather evidence for a satisfactory approach that addresses the complexity of the topic researched: quality, higher education and quality management systems. We chose to adopt an applied study, the exploratory-descriptive research as to the objective and the quantitative and qualitative research as to the approach to the problem. The object of study is composed by the Planning Provosts of Federal Universities listed in the University Ranking Sheet - (RUF) in 2013. We chose to restrict the sample listing only the provosts of the 20 best-placed universities in the ranking of the Federal Universities. The research instrument was composed of 26 questions, of which 6 questions were designed to identify the profile of the manager, 16 questions of perception (manifested variables) on the importance of quality management in the University, where the managers assigned values (answers) to the affirmatives (that address the main topic of this thesis) based on a Likert scale of 5 points, and 4 open and optional questions, in order to identify general management practices used. It was used for statistical analysis (data analysis) descriptive and factorial statistics. The responses collected through the questionnaire portray the managers´ perception regarding the importance of quality management in their institutions. Sixteen variables were addressed, the results of factor analysis of importance were "Important" and "Very Important", where the variable (V2) was "Important" and all others "Very important." With this information, it is possible to prioritize some areas that deserve immediate action. As it was observed that some variables are "Very important" for the vast majority of managers, others did not show the same result as example (V2, V10, V11). It is concluded that the manager´s perception of quality management in his or her institution is relevant, but the same importance is not given to quality programs implemented in other segments of the economy, and that, despite the advancements offered by SINAES, the model does not evaluate the institution in a global way. Thus, with the results, it is expected to contribute to the advancement of the subject, trying to arouse interest from the managers of Federal Universities in the subject, emphasizing the importance of quality management systems as a necessary tool to raise the institutional quality
Sistema de detecção e isolamento de falhas em sistemas dinâmicos baseado em identificação paramétrica
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The present research aims at contributing to the area of detection and diagnosis of failure through the proposal of a new system architecture of detection and isolation of failures (FDI, Fault Detection and Isolation). The proposed architecture presents innovations related to the way the physical values monitored are linked to the FDI system and, as a consequence, the way the failures are detected, isolated and classified. A search for mathematical tools able to satisfy the objectives of the proposed architecture has pointed at the use of the Kalman Filter and its derivatives EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter). The use of the first one is efficient when the monitored process presents a linear relation among its physical values to be monitored and its out-put. The other two are proficient in case this dynamics is no-linear. After that, a short comparative of features and abilities in the context of failure detection concludes that the UFK system is a better alternative than the EKF one to compose the architecture of the FDI system proposed in case of processes of no-linear dynamics. The results shown in the end of the research refer to the linear and no-linear industrial processes. The efficiency of the proposed architecture may be observed since it has been applied to simulated and real processes. To conclude, the contributions of this thesis are found in the end of the text
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We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative
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This paper presents a new multi-model technique of dentification in ANFIS for nonlinear systems. In this technique, the structure used is of the fuzzy Takagi-Sugeno of which the consequences are local linear models that represent the system of different points of operation and the precursors are membership functions whose adjustments are realized by the learning phase of the neuro-fuzzy ANFIS technique. The models that represent the system at different points of the operation can be found with linearization techniques like, for example, the Least Squares method that is robust against sounds and of simple application. The fuzzy system is responsible for informing the proportion of each model that should be utilized, using the membership functions. The membership functions can be adjusted by ANFIS with the use of neural network algorithms, like the back propagation error type, in such a way that the models found for each area are correctly interpolated and define an action of each model for possible entries into the system. In multi-models, the definition of action of models is known as metrics and, since this paper is based on ANFIS, it shall be denominated in ANFIS metrics. This way, ANFIS metrics is utilized to interpolate various models, composing a system to be identified. Differing from the traditional ANFIS, the created technique necessarily represents the system in various well defined regions by unaltered models whose pondered activation as per the membership functions. The selection of regions for the application of the Least Squares method is realized manually from the graphic analysis of the system behavior or from the physical characteristics of the plant. This selection serves as a base to initiate the linear model defining technique and generating the initial configuration of the membership functions. The experiments are conducted in a teaching tank, with multiple sections, designed and created to show the characteristics of the technique. The results from this tank illustrate the performance reached by the technique in task of identifying, utilizing configurations of ANFIS, comparing the developed technique with various models of simple metrics and comparing with the NNARX technique, also adapted to identification
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The main purpose of this work was the development of ceramic dielectric substrates of bismuth niobate (BiNbO4) doped with vanadium pentoxide (V2O5), with high permittivity, used in the construction of microstrip patch antennas with applications in wireless communications systems. The high electrical permittivity of the ceramic substrate provided a reduction of the antenna dimensions. The numerical results obtained in the simulations and the measurements performed with the microstrip patch antennas showed good agreement. These antennas can be used in wireless communication systems in various frequency bands. Results were satisfactory for antennas operating at frequencies in the S band, in the range between 2.5 GHz and 3.0 GHz.
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In this work we use Interval Mathematics to establish interval counterparts for the main tools used in digital signal processing. More specifically, the approach developed here is oriented to signals, systems, sampling, quantization, coding and Fourier transforms. A detailed study for some interval arithmetics which handle with complex numbers is provided; they are: complex interval arithmetic (or rectangular), circular complex arithmetic, and interval arithmetic for polar sectors. This lead us to investigate some properties that are relevant for the development of a theory of interval digital signal processing. It is shown that the sets IR and R(C) endowed with any correct arithmetic is not an algebraic field, meaning that those sets do not behave like real and complex numbers. An alternative to the notion of interval complex width is also provided and the Kulisch- Miranker order is used in order to write complex numbers in the interval form enabling operations on endpoints. The use of interval signals and systems is possible thanks to the representation of complex values into floating point systems. That is, if a number x 2 R is not representable in a floating point system F then it is mapped to an interval [x;x], such that x is the largest number in F which is smaller than x and x is the smallest one in F which is greater than x. This interval representation is the starting point for definitions like interval signals and systems which take real or complex values. It provides the extension for notions like: causality, stability, time invariance, homogeneity, additivity and linearity to interval systems. The process of quantization is extended to its interval counterpart. Thereafter the interval versions for: quantization levels, quantization error and encoded signal are provided. It is shown that the interval levels of quantization represent complex quantization levels and the classical quantization error ranges over the interval quantization error. An estimation for the interval quantization error and an interval version for Z-transform (and hence Fourier transform) is provided. Finally, the results of an Matlab implementation is given
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In the recovering process of oil, rock heterogeneity has a huge impact on how fluids move in the field, defining how much oil can be recovered. In order to study this variability, percolation theory, which describes phenomena involving geometry and connectivity are the bases, is a very useful model. Result of percolation is tridimensional data and have no physical meaning until visualized in form of images or animations. Although a lot of powerful and sophisticated visualization tools have been developed, they focus on generation of planar 2D images. In order to interpret data as they would be in the real world, virtual reality techniques using stereo images could be used. In this work we propose an interactive and helpful tool, named ZSweepVR, based on virtual reality techniques that allows a better comprehension of volumetric data generated by simulation of dynamic percolation. The developed system has the ability to render images using two different techniques: surface rendering and volume rendering. Surface rendering is accomplished by OpenGL directives and volume rendering is accomplished by the Zsweep direct volume rendering engine. In the case of volumetric rendering, we implemented an algorithm to generate stereo images. We also propose enhancements in the original percolation algorithm in order to get a better performance. We applied our developed tools to a mature field database, obtaining satisfactory results. The use of stereoscopic and volumetric images brought valuable contributions for the interpretation and clustering formation analysis in percolation, what certainly could lead to better decisions about the exploration and recovery process in oil fields
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This work presents a study of implementation procedures for multiband microstrip patch antennas characterization, using on wireless communication systems. An artificial neural network multilayer perceptron is used to locate the bands of operational frequencies of the antenna for different geometrics configurations. The antenna is projected, simulated and tested in laboratory. The results obtained are compared in order to validate the performance of archetypes that resulted in a good one agreement in metric terms. The neurocomputationals procedures developed can be extended to other electromagnetic structures of wireless communications systems
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This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented
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This master dissertation presents the development of a fault detection and isolation system based in neural network. The system is composed of two parts: an identification subsystem and a classification subsystem. Both of the subsystems use neural network techniques with multilayer perceptron training algorithm. Two approaches for identifica-tion stage were analyzed. The fault classifier uses only residue signals from the identification subsystem. To validate the proposal we have done simulation and real experiments in a level system with two water reservoirs. Several faults were generated above this plant and the proposed fault detection system presented very acceptable behavior. In the end of this work we highlight the main difficulties found in real tests that do not exist when it works only with simulation environments