119 resultados para Modelagem cinética
Resumo:
This work presents a model of bearingless induction machine with divided winding. The main goal is to obtain a machine model to use a simpler control system as used in conventional induction machine and to know its behavior. The same strategies used in conventional machines were used to reach the bearingless induction machine model, which has made possible an easier treatment of the involved parameters. The studied machine is adapted from the conventional induction machine, the stator windings were divided and all terminals had been available. This method does not need an auxiliary stator winding for the radial position control which results in a more compact machine. Another issue about this machine is the variation of inductances array also present in result of the rotor displacement. The changeable air-gap produces variation in magnetic flux and in inductances consequently. The conventional machine model can be used for the bearingless machine when the rotor is centered, but in rotor displacement condition this model is not applicable. The bearingless machine has two sets of motor-bearing, both sets with four poles. It was constructed in horizontal position and this increases difficulty in implementation. The used rotor has peculiar characteristics; it is projected according to the stator to yield the greatest torque and force possible. It is important to observe that the current unbalance generated by the position control does not modify the machine characteristics, this only occurs due the radial rotor displacement. The obtained results validate the work; the data reached by a supervisory system corresponds the foreseen results of simulation which verify the model veracity
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In this dissertation new models of propagation path loss predictions are proposed by from techniques of optimization recent and measures of power levels for the urban and suburban areas of Natal, city of Brazilian northeast. These new proposed models are: (i) a statistical model that was implemented based in the addition of second-order statistics for the power and the altimetry of the relief in model of linear losses; (ii) a artificial neural networks model used the training of the algorithm backpropagation, in order to get the equation of propagation losses; (iii) a model based on the technique of the random walker, that considers the random of the absorption and the chaos of the environment and than its unknown parameters for the equation of propagation losses are determined through of a neural network. The digitalization of the relief for the urban and suburban areas of Natal were carried through of the development of specific computational programs and had been used available maps in the Statistics and Geography Brazilian Institute. The validations of the proposed propagation models had been carried through comparisons with measures and propagation classic models, and numerical good agreements were observed. These new considered models could be applied to any urban and suburban scenes with characteristic similar architectural to the city of Natal
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This work presents simulation results of an identification platform compatible with the INPE Brazilian Data Collection System, modeled with SystemC-AMS. SystemC-AMS that is a library of C++ classes dedicated to the simulation of heterogeneous systems, offering a powerful resource to describe models in digital, analog and RF domains, as well as mechanical and optic. The designed model was divided in four parts. The first block takes into account the satellite s orbit, necessary to correctly model the propagation channel, including Doppler effect, attenuation and thermal noise. The identification block detects the satellite presence. It is composed by low noise amplifier, band pass filter, power detector and logic comparator. The controller block is responsible for enabling the RF transmitter when the presence of the satellite is detected. The controller was modeled as a Petri net, due to the asynchronous nature of the system. The fourth block is the RF transmitter unit, which performs the modulation of the information in BPSK ±60o. This block is composed by oscillator, mixer, adder and amplifier. The whole system was simulated simultaneously. The results are being used to specify system components and to elaborate testbenchs for design verification
Resumo:
The incorporate of industrial automation in the medical are requires mechanisms to safety and efficient establishment of communication between biomedical devices. One solution to this problem is the MP-HA (Multicycles Protocol to Hospital Automation) that down a segmented network by beds coordinated by an element called Service Provider. The goal of this work is to model this Service Provider and to do performance analysis of the activities executed by in establishment and maintenance of hospital networks
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This study aims to use a computational model that considers the statistical characteristics of the wind and the reliability characteristics of a wind turbine, such as failure rates and repair, representing the wind farm by a Markov process to determine the estimated annual energy generated, and compare it with a real case. This model can also be used in reliability studies, and provides some performance indicators that will help in analyzing the feasibility of setting up a wind farm, once the power curve is known and the availability of wind speed measurements. To validate this model, simulations were done using the database of the wind farm of Macau PETROBRAS. The results were very close to the real, thereby confirming that the model successfully reproduced the behavior of all components involved. Finally, a comparison was made of the results presented by this model, with the result of estimated annual energy considering the modeling of the distribution wind by a statistical distribution of Weibull
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This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot
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The control, automation and optimization areas help to improve the processes used by industry. They contribute to a fast production line, improving the products quality and reducing the manufacturing costs. Didatic plants are good tools for research in these areas, providing a direct contact with some industrial equipaments. Given these capabilities, the main goal of this work is to model and control a didactic plant, which is a level and flow process control system with an industrial instrumentation. With a model it is possible to build a simulator for the plant that allows studies about its behaviour, without any of the real processes operational costs, like experiments with controllers. They can be tested several times before its application in a real process. Among the several types of controllers, it was used adaptive controllers, mainly the Direct Self-Tuning Regulators (DSTR) with Integral Action and the Gain Scheduling (GS). The DSTR was based on Pole-Placement design and use the Recursive Least Square to calculate the controller parameters. The characteristics of an adaptive system was very worth to guarantee a good performance when the controller was applied to the plant
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This work has as main objective the application of Artificial Neural Networks, ANN, in the resolution of problems of RF /microwaves devices, as for example the prediction of the frequency response of some structures in an interest region. Artificial Neural Networks, are presently a alternative to the current methods of analysis of microwaves structures. Therefore they are capable to learn, and the more important to generalize the acquired knowledge, from any type of available data, keeping the precision of the original technique and adding the low computational cost of the neural models. For this reason, artificial neural networks are being increasily used for modeling microwaves devices. Multilayer Perceptron and Radial Base Functions models are used in this work. The advantages/disadvantages of these models and the referring algorithms of training of each one are described. Microwave planar devices, as Frequency Selective Surfaces and microstrip antennas, are in evidence due the increasing necessities of filtering and separation of eletromagnetic waves and the miniaturization of RF devices. Therefore, it is of fundamental importance the study of the structural parameters of these devices in a fast and accurate way. The presented results, show to the capacities of the neural techniques for modeling both Frequency Selective Surfaces and antennas
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On this research we investigated how new technologies can help the process of design and manufacturing of furniture in such small manufacturers in Rio Grande do Norte state. Google SketchUp, a 3D software tool, was developed in such a way that its internal structures are opened and can be accessed using SketchUp s API for Ruby and programs written in Ruby language (plugins). Using the concepts of the so-called Group Technology and the flexibility that enables adding new functionalities to this software, it was created a Methodology for Modeling of Furniture, a Coding System and a plugin for Google s tool in order to implement the Methodology developed. As resulted, the following facilities are available: the user may create and reuse the library s models over-and-over; reports of the materials manufacturing process costs are provided and, finally, detailed drawings, getting a better integration between the furniture design and manufacturing process
Resumo:
Annular flow is the prevailing pattern in transport and energy conversion systems and therefore, one of the most important patterns in multiphase flow in ducts. The correct prediction of the pressure gradient and heat transfer coefficient is essential for optimizing the system s capacity. The objective of this work is to develop and implement a numerical algorithm capable of predicting hydrodynamic and thermal characteristics for upflow, vertical, annular flow. The numerical algorithm is then complemented with the physical modeling of phenomena that occurs in this flow pattern. These are, turbulence, entrainment and deposition and phase change. For the development of the numerical model, axial diffusion of heat and momentum is neglected. In this way the time-averaged equations are solved in their parabolic form obtaining the velocity and temperature profiles for each axial step at a time, together with the global parameters, namely, pressure gradient, mean film thickness and heat transfer coefficient, as well as their variation in the axial direction. The model is validated for the following conditions: fully-developed laminar flow with no entrainment; fully developed laminar flow with heat transfer, fully-developed turbulent flow with entrained drops, developing turbulent annular flow with entrained drops, and turbulent flow with heat transfer and phase change
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Currently there is still a high demand for quality control in manufacturing processes of mechanical parts. This keeps alive the need for the inspection activity of final products ranging from dimensional analysis to chemical composition of products. Usually this task may be done through various nondestructive and destructive methods that ensure the integrity of the parts. The result generated by these modern inspection tools ends up not being able to geometrically define the real damage and, therefore, cannot be properly displayed on a computing environment screen. Virtual 3D visualization may help identify damage that would hardly be detected by any other methods. One may find some commercial softwares that seek to address the stages of a design and simulation of mechanical parts in order to predict possible damages trying to diminish potential undesirable events. However, the challenge of developing softwares capable of integrating the various design activities, product inspection, results of non-destructive testing as well as the simulation of damage still needs the attention of researchers. This was the motivation to conduct a methodological study for implementation of a versatile CAD/CAE computer kernel capable of helping programmers in developing softwares applied to the activities of design and simulation of mechanics parts under stress. In this research it is presented interesting results obtained from the use of the developed kernel showing that it was successfully applied to case studies of design including parts presenting specific geometries, namely: mechanical prostheses, heat exchangers and piping of oil and gas. Finally, the conclusions regarding the experience of merging CAD and CAE theories to develop the kernel, so as to result in a tool adaptable to various applications of the metalworking industry are presented
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A critical problem in mature gas wells is the liquid loading. As the reservoir pressure decreases, gas superficial velocities decreases and the drag exerted on the liquid phase may become insufficient to bring all the liquid to the surface. Liquid starts to drain downward, flooding the well and increasing the backpressure which decreases the gas superficial velocity and so on. A popular method to remedy this problem is the Plunger Lift. This method consists of dropping the "plunger"to the bottom of the tubing well with the main production valve closed. When the plunger reaches the well bottom the production valve is opened and the plunger carry the liquid to the surface. However, models presented in literature for predicting the behavior in plunger lift are simplistic, in many cases static (not considering the transient effects). Therefore work presents the development and validation of a numerical algorithm to solve one-dimensional compressible in gas wells using the Finite Volume Method and PRIME techniques for treating coupling of pressure and velocity fields. The code will be then used to develop a dynamic model for the plunger lift which includes the transient compressible flow within the well
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Ensure the integrity of the pipeline network is an extremely important factor in the oil and gas industry. The engineering of pipelines uses sophisticated robotic inspection tools in-line known as instrumented pigs. Several relevant factors difficult the inspection of pipelines, especially in offshore field which uses pipelines with multi-diameters, radii of curvature accentuated, wall thickness of the pipe above the conventional, multi-phase flow and so on. Within this context, appeared a new instrumented Pig, called Feeler PIG, for detection and sizing of thickness loss in pipelines with internal damage. This tool was developed to overcome several limitations that other conventional instrumented pigs have during the inspection. Several factors influence the measurement errors of the pig affecting the reliability of the results. This work shows different operating conditions and provides a test rig for feeler sensors of an inspection pig under different dynamic loads. The results of measurements of the damage type of shoulder and holes in a cyclic flat surface are evaluated, as well as a mathematical model for the sensor response and their errors from the actual behavior
Resumo:
The determination of the rheology of drilling fluids is of fundamental importance to select the best composition and the best treatment to be applied in these fluids. This work presents a study of the rheological behavior of some addictives used as viscosifiers in water-based drilling fluids. The evaluated addictives were: Carboxymethylcellulose (CMC), Xanthan gum (GX), and Bentonite. The main objective was to rheologically characterize suspensions composed by these addictives, by applying mathematical models for fluid flow behavior, in order to determine the best flow equation to represent the system, as well as the model parameters. The mathematical models applied in this research were: the Bingham Model, the Ostwald de Wale Model, and the Herschel-Bulkley Model. A previous study of hydration time for each used addictive was accomplished seeking to evaluate the effect of polymer and clay hydration on rheological behavior of the fluid. The rheological characterization was made through typical rheology experiments, using a coaxial cylinder viscosimeter, where the flow curves and the thixotropic magnitude of each fluid was obtained. For each used addictive the rheological behavior as a function of temperature was also evaluated as well as fluid stability as a function of the concentration and kind of addictive used. After analyses of results, mixtures of polymer and clay were made seeking to evaluate the rheological modifications provided by the polymer incorporation in the water + bentonite system. The obtained results showed that the Ostwald de Waale model provided the best fit for fluids prepared using CMC and for fluids with Xanthan gum and Bentonite the best fit was given by the Herschel-Bulkley one
Resumo:
The extraction with pressurized fluids has become an attractive process for the extraction of essential oils, mainly due the specific characteristics of the fluids near the critical region. This work presents results of the extraction process of the essential oil of Cymbopogon winterianus J. with CO2 under high pressures. The effect of the following variables was evaluated: solvent flow rate (from 0.37 to 1.5 g CO2/min), pressure (66.7 and 75 bar) and temperature (8, 10, 15, 20 and 25 ºC) on the extraction kinetics and the total yield of the process, as well as in the solubility and composition of the C. winterianus essential oil. The experimental apparatus consisted of an extractor of fixed bed and the dynamic method was adopted for the calculation of the oil solubility. Extractions were also accomplished by conventional techniques (steam and organic solvent extraction). The determination and identification of extract composition were done by gas chromatography coupled with a mass spectrometer (GC-MS). The extract composition varied in function of the studied operational conditions and also related to the used extraction method. The main components obtained in the CO2 extraction were elemol, geraniol, citronellol and citronellal. For the steam extraction were the citronellal, citronellol and geraniol and for the organic solvent extraction were the azulene and the hexadecane. The most yield values (2.76%) and oil solubility (2.49x10-2 g oil/ g CO2) were obtained through the CO2 extraction in the operational conditions of T = 10°C, P = 66.7 bar and solvent flow rate 0.85 g CO2/min