918 resultados para mathematical model


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This work presents a thermoeconomic optimization methodology for the analysis and design of energy systems. This methodology involves economic aspects related to the exergy conception, in order to develop a tool to assist the equipment selection, operation mode choice as well as to optimize the thermal plants design. It also presents the concepts related to exergy in a general scope and in thermoeconomics which combines the thermal sciences principles (thermodynamics, heat transfer, and fluid mechanics) and the economic engineering in order to rationalize energy systems investment decisions, development and operation. Even in this paper, it develops a thermoeconomic methodology through the use of a simple mathematical model, involving thermodynamics parameters and costs evaluation, also defining the objective function as the exergetic production cost. The optimization problem evaluation is developed for two energy systems. First is applied to a steam compression refrigeration system and then to a cogeneration system using backpressure steam turbine. (C) 2010 Elsevier Ltd. All rights reserved.

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A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RCA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models. (C) 2010 Elsevier B.V. All rights reserved.

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An efficient heuristic algorithm is presented in this work in order to solve the optimal capacitor placement problem in radial distribution systems. The proposal uses the solution from the mathematical model after relaxing the integrality of the discrete variables as a strategy to identify the most attractive bus to add capacitors to each step of the heuristic algorithm. The relaxed mathematical model is a nonlinear programming problem and is solved using a specialized interior point method, The algorithm still incorporates an additional strategy of local search that enables the finding of a group of quality solutions after small alterations in the optimization strategy. Proposed solution methodology has been implemented and tested in known electric systems getting a satisfactory outcome compared with metaheuristic methods.The tests carried out in electric systems known in specialized literature reveal the satisfactory outcome of the proposed algorithm compared with metaheuristic methods. (C) 2009 Elsevier Ltd. All rights reserved.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

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In this paper, the dynamic behaviour of the "click" mechanism is analysed. A more accurate model is used than in the past, in which the limits of movement due to the geometry of the flight mechanism are imposed. Moreover, the effects of different damping models are investigated. In previous work, the damping model was assumed to be of the linear viscous type for simplicity, but it is likely that the damping due to drag forces is nonlinear. Accordingly, a model of damping in which the damping force is proportional to the square of the velocity is used, and the results are compared with the simpler model of linear viscous damping. Because of the complexity of the model an analytical approach is not possible so the problem has been cast in terms of non-dimensional variables and solved numerically. The peak kinetic energy of the wing root per energy input in one cycle is chosen to study the effectiveness of the "click" mechanism compared with a linear resonant mechanism. It is shown that, the "click" mechanism has distinct advantages when it is driven below its resonant frequency. When the damping is quadratic, there are some further advantages compared to when the damping is linear and viscous, provided that the amplitude of the excitation force is large enough to avoid the erratic behaviour of the mechanism that occurs for small forces. (C) 2011 Elsevier Ltd. All rights reserved.

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The separation oil-water by the use of flotation process is characterized by the involvement between the liquid and gas phases. For the comprehension of this process, it s necessary to analyze the physical and chemical properties command float flotation, defining the nature and forces over the particles. The interface chemistry has an important role on the flotation technology once, by dispersion of a gas phase into a liquid mixture the particles desired get stuck into air bubbles, being conduced to a superficial layer where can be physically separated. Through the study of interface interaction involved in the system used for this work, was possible to apply the results in an mathematical model able to determine the probability of flotation using a different view related to petroleum emulsions such as oil-water. The terms of probability of flotation correlate the collision and addition between particles of oil and air bubbles, that as more collisions, better is the probability of flotation. The additional probability was analyzed by the isotherm of absorption from Freundlich, represents itself the add probability between air bubbles and oil particles. The mathematical scheme for float flotation involved the injected air flow, the size of bubbles and quantity for second, the volume of float cell, viscosity of environment and concentration of demulsifier. The results shown that the float agent developed by castor oil, pos pH variation, salt quantity, temperature, concentration and water-oil quantity, presented efficient extraction of oil from water, up to 95%, using concentrations around 11 ppm of demulsifier. The best results were compared to other commercial products, codified by ―W‖ and ―Z‖, being observed an equivalent demulsifier power between Agflot and commercial product ―W‖ and superior to commercial product ―Z‖

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Neste trabalho, ajustou-se um modelo matemático para quantificar o efeito da variação do rendimento da bomba hidráulica na variação dos custos de um sistema de bombeamento, na estrutura tarifária horossazonal verde (subgrupo A4) e o tempo de recuperação do capital investido no equipamento de maior rendimento. em seguida, o mesmo foi aplicado a um sistema de bombeamento para suprimento de um sistema de irrigação do tipo pivô central. As opções de rendimento da bomba hidráulica foram: 69,5% (bomba 1), 73% (bomba 2) e 78% (bomba 3), cujos custos de aquisição foram, respectivamente, R$ 6.176,00, R$ 8.479,00 e R$ 15.509,00. Os resultados da aplicação do modelo mostraram que: i) a substituição da bomba 1 pela bomba 2 foi viável, sendo o período de recuperação de capital 3,4 anos; ii) a substituição da bomba 1 pela bomba 3 foi viável, sendo o período de recuperação de capital 9,2 anos; iii) a substituição da bomba 2 pela bomba 3 foi inviável, sendo o período de recuperação de capital 21,1 anos superior ao período de amortização do investimento na avaliação econômica, considerado 15 anos.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In this work, we use a nonlinear control based on Optimal Linear Control. We used as mathematical model a Duffing equation to model a supporting structure for an unbalanced rotating machine with limited power (non-ideal motor). Numerical simulations are performed for a set control parameter (depending on the voltage of the motor, that is, in the static and dynamic characteristic of the motor) The interaction of the non-ideal excitation with the structure may lead to the occurrence of interesting phenomena during the forward passage through the several resonance states of the system. Chaotic behavior is obtained for values of the parameters. Then, the proposed control strategy is applied in order to regulate the chaotic behavior, in order to obtain a periodic orbit and to decrease its amplitude. Both methodologies were used in complete agreement between them. The purpose of the paper is to give suggestions and recommendations to designers and engineers on how to drive this kind of system through resonance.

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This work presents a algorithmic study of Multicast Packing Problem considering a multiobjective approach. The first step realized was an extensive review about the problem. This review serverd as a reference point for the definition of the multiobjective mathematical model. Then, the instances used in the experimentation process were defined, this instances were created based on the main caracteristics from literature. Since both mathematical model and the instances were definined, then several algoritms were created. The algorithms were based on the classical approaches to multiobjective optimization: NSGA2 (3 versions), SPEA2 (3 versions). In addition, the GRASP procedures were adapted to work with multiples objectives, two vesions were created. These algorithms were composed by three recombination operators(C1, C2 e C3), two operator for build solution, a mutation operator and a local search procedure. Finally, a long experimentation process was performed. This process has three stages: the first consisted of adjusting the parameters; the second was perfomed to indentify the best version for each algorithm. After, the best versions for each algorithm were compared in order to identify the best algorithm among all. The algorithms were evaluated based on quality indicators and Hypervolume Multiplicative Epsilon

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In this work we present a mathematical and computational modeling of electrokinetic phenomena in electrically charged porous medium. We consider the porous medium composed of three different scales (nanoscopic, microscopic and macroscopic). On the microscopic scale the domain is composed by a porous matrix and a solid phase. The pores are filled with an aqueous phase consisting of ionic solutes fully diluted, and the solid matrix consists of electrically charged particles. Initially we present the mathematical model that governs the electrical double layer in order to quantify the electric potential, electric charge density, ion adsorption and chemical adsorption in nanoscopic scale. Then, we derive the microscopic model, where the adsorption of ions due to the electric double layer and the reactions of protonation/ deprotanaç~ao and zeta potential obtained in modeling nanoscopic arise in microscopic scale through interface conditions in the problem of Stokes and Nerst-Planck equations respectively governing the movement of the aqueous solution and transport of ions. We developed the process of upscaling the problem nano/microscopic using the homogenization technique of periodic structures by deducing the macroscopic model with their respectives cell problems for effective parameters of the macroscopic equations. Considering a clayey porous medium consisting of kaolinite clay plates distributed parallel, we rewrite the macroscopic model in a one-dimensional version. Finally, using a sequential algorithm, we discretize the macroscopic model via the finite element method, along with the interactive method of Picard for the nonlinear terms. Numerical simulations on transient regime with variable pH in one-dimensional case are obtained, aiming computational modeling of the electroremediation process of clay soils contaminated

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Objective: To identify potential prognostic factors for pulmonary thromboembolism (PTE), establishing a mathematical model to predict the risk for fatal PTE and nonfatal PTE.Method: the reports on 4,813 consecutive autopsies performed from 1979 to 1998 in a Brazilian tertiary referral medical school were reviewed for a retrospective study. From the medical records and autopsy reports of the 512 patients found with macroscopically and/or microscopically,documented PTE, data on demographics, underlying diseases, and probable PTE site of origin were gathered and studied by multiple logistic regression. Thereafter, the jackknife method, a statistical cross-validation technique that uses the original study patients to validate a clinical prediction rule, was performed.Results: the autopsy rate was 50.2%, and PTE prevalence was 10.6%. In 212 cases, PTE was the main cause of death (fatal PTE). The independent variables selected by the regression significance criteria that were more likely to be associated with fatal PTE were age (odds ratio [OR], 1.02; 95% confidence interval [CI], 1.00 to 1.03), trauma (OR, 8.5; 95% CI, 2.20 to 32.81), right-sided cardiac thrombi (OR, 1.96; 95% CI, 1.02 to 3.77), pelvic vein thrombi (OR, 3.46; 95% CI, 1.19 to 10.05); those most likely to be associated with nonfatal PTE were systemic arterial hypertension (OR, 0.51; 95% CI, 0.33 to 0.80), pneumonia (OR, 0.46; 95% CI, 0.30 to 0.71), and sepsis (OR, 0.16; 95% CI, 0.06 to 0.40). The results obtained from the application of the equation in the 512 cases studied using logistic regression analysis suggest the range in which logit p > 0.336 favors the occurrence of fatal PTE, logit p < - 1.142 favors nonfatal PTE, and logit P with intermediate values is not conclusive. The cross-validation prediction misclassification rate was 25.6%, meaning that the prediction equation correctly classified the majority of the cases (74.4%).Conclusions: Although the usefulness of this method in everyday medical practice needs to be confirmed by a prospective study, for the time being our results suggest that concerning prevention, diagnosis, and treatment of PTE, strict attention should be given to those patients presenting the variables that are significant in the logistic regression model.

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This work proposes a mathematical model to aid variety selection and planting quantity of sugarcane in order to reduce crop residues, maximize energy generated by this residue, and satisfy all the supply of the mill. We propose Linear Programming with two objective. The conflict between these objectives allows the use of the Nonzero-sum Game Theory. (C) 2003 Elsevier B.V. Ltd. All rights reserved.

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The dengue virus is transmitted in regions previously infested with the mosquito Aedes aegypti. To assess the spreading and establishment of the dengue disease vector, a mathematical model is developed that takes into account the diffusion and advection phenomena. A discrete model based on the cellular automata approach, which is a good framework to deal with small populations, is also developed to be compared with the continuous modeling.