989 resultados para otimização não-linear
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Este trabalho tem por objetivo o estudo do m~todo da Programação Linear e de sua aplicação no planejamento da empresa agricola, tendo em vista a demonstração de sua importancia como instrumento analItico no processo de tomada de decisões. Inicialmente ~ feita uma abordagem sobre a problematica da programação e seus fundamentos, sendo examinados os principais conceitos sobre os quais o assunto se baseia. A discussão encaminhada no sentido de chamar a atenção para o fato de que, em vista das pressões a que esta submetida a agricultura no estagio contemporâneo do desenvolvimento, - que lhe exigem melhores niveis de desempenho traduzidos em Indices mais elevados de produtividade, generalizou-se o consenso sobre a conveniência de se dar maior atenção i programação das atividades do setor agrIcola, tanto a nIvel de Região como no ambito de sua area empresarial. Entre os varias modelos gerados com o objetivo de oferecer respostas aos problemas de organização da produção, otimização de resuItados c racionalização do uso dos fatores, o da Programação Linear considerado o mais geralmente aceito pela comunidade cientIfica, por sua estrutura teórico sofisticada e pela capacidade de dar respostas exatas e diretas a questões de maior complexidade. A parte teórica do metodo da Programação Linear ~ examinada no Capítulo 11. De maneira sumária são abordados os seus fundamentos matemáticos e discutidos os principais teoremas sobre conjuntos convexos, corno elementos do espaço das soluções possiveis. A álgebra do algorÍtmo Simplex ~ abordada em sua forma ardinária, com a demonstração dos passos sucessivos do algoritmo, ato encontro do vertice característico da solução otima. No Capítulo 111 os conceitos teoricos da Programação Linear sao aplicados aos dados de uma empresa agricola, com a finalidade de demonstrar a operacionalização do algoritmo Simplcx ! através de programas de computador.
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O uso de opções no mercado financeiro tem ganhado relevância devido ao seu payoff não-linear e a possibilidade de alterar o perfil da distribuição de retornos de um portfolio. Existem diversas estratégias que são adequadas para cada cenário que o investidor acredita estar exposto, mas como o conjunto de cenários forma uma distribuição de retornos, devemos utilizar uma medida adequada para trabalhar com este tipo de informação. Assim, foi utilizada a medida Omega, que é uma medida capaz de capturar todos os momentos de uma distribuição, dado um limiar de retornos. Este trabalho se propõe a desenvolver uma metodologia que possibilite otimizar a medida Omega de um portfolio, através do uso de opções sobre o IBOVESPA. Para a geração das distribuições de retornos foi utilizada simulação de Monte Carlo, com jumps e volatilidade estocástica. Finalmente, foram feitas diversas análises sobre os resultados obtidos, afim de comparar a estratégia otimizada com diversas estratégias aleatórias, e também, realizado um backtest para avaliar a eficácia da implementação da estratégia otimizada.
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VARELA, M.L. et al. Otimização de uma metodologia para análise mineralógica racional de argilominerais. Cerâmica, São Paulo, n. 51, p. 387-391, 2005.
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Over recent years the structural ceramics industry in Brazil has found a very favorable market for growth. However, difficulties related to productivity and product quality are partially inhibiting this possible growth. An alternative for trying to solve these problems and, thus, provide the pottery industry the feasibility of full development, is the substitution of firewood used in the burning process by natural gas. In order to contribute to this process of technological innovation, this paper studies the effect of co-use of ceramic phyllite and kaolin waste on the properties of a clay matrix, verifying the possible benefits that these raw materials can give to the final product, as well as the possibility of such materials to reduce the heat load necessary to obtain products with equal or superior quality. The study was divided into two steps: characterization of materials and study of formulations. Two clays, a phyllite and a residue of kaolin were characterized by the following techniques: laser granulometry, plasticity index by Atterberg limits, X-ray fluorescence, X-ray diffraction, mineralogical composition by Rietveld, thermogravimetric and differential thermal analysis. To study the formulations, specifically for evaluation of technological properties of the parts, was performed an experimental model that combined planning involving a mixture of three components (standard mass x phyllite x kaolin waste) and a 23 factorial design with central point associated with thermal processing parameters. The experiment was performed with restricted strip-plot randomization. In total, 13 compositional points were investigated within the following constraints: phyllite ≤ 20% by weight, kaolin waste ≤ 40% by weight, and standard mass ≥ 60% by weight. The thermal parameters were used at the following levels: 750 and 950 °C to the firing temperature, 5 and 15 °C/min at the heating rate, 15 and 45min to the baseline. The results showed that the introduction of phyllite and/or kaolin waste in ceramic body produced a number of benefits in properties of the final product, such as: decreased absorption of water, apparent porosity and linear retraction at burn; besides the increase in apparent specific mass and mechanical properties of parts. The best results were obtained in the compositional points where the sum of the levels of kaolin waste and phyllite was maximal (40% by weight), as well as conditions which were used in firing temperatures of 950 °C. Regarding the prospect of savings in heat energy required to form the desired microstructure, the phyllite and the residue of kaolin, for having small particle sizes and constitutions mineralogical phases with the presence of fluxes, contributed to the optimization of the firing cycle.
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Tuberculosis is a serious disease, but curable in practically 100% of new cases, since complied the principles of modern chemotherapy. Isoniazid (ISN), Rifampicin (RIF), Pyrazinamide (PYR) and Chloride Ethambutol (ETA) are considered first line drugs in the treatment of tuberculosis, by combining the highest level of efficiency with acceptable degree of toxicity. Concerning USP 33 - NF28 (2010) the chromatography analysis to 3 of 4 drugs (ISN, PYR and RIF) last in average 15 minutes and 10 minutes more to obtain the 4th drug (ETA) using a column and mobile phase mixture different, becoming its industrial application unfavorable. Thus, many studies have being carried out to minimize this problem. An alternative would use the UFLC, which is based with the same principles of HPLC, however it uses stationary phases with particles smaller than 2 μm. Therefore, this study goals to develop and validate new analytical methods to determine simultaneously the drugs by HPLC/DAD and UFLC/DAD. For this, a analytical screening was carried out, which verified that is necessary a gradient of mobile phase system A (acetate buffer:methanol 94:6 v/v) and B (acetate buffer:acetonitrile 55:45 v/v). Furthermore, to the development and optimization of the method in HPLC and UFLC, with achievement of the values of system suitability into the criteria limits required for both techniques, the validations have began. Standard solutions and tablets test solutions were prepared and injected into HPLC and UFLC, containing 0.008 mg/mL ISN, 0.043 mg/mL PYR, 0.030 mg.mL-1 ETA and 0.016 mg/mL RIF. The validation of analytical methods for HPLC and UFLC was carried out with the determination of specificity/selectivity, analytical curve, linearity, precision, limits of detection and quantification, accuracy and robustness. The methods were adequate for determination of 4 drugs separately without interfered with the others. Precise, due to the fact of the methods demonstrated since with the days variation, besides the repeatability, the values were into the level required by the regular agency. Linear (R> 0,99), once the methods were capable to demonstrate results directly proportional to the concentration of the analyte sample, within of specified range. Accurate, once the methods were capable to present values of variation coefficient and recovery percentage into the required limits (98 to 102%). The methods showed LOD and LOQ very low showing the high sensitivity of the methods for the four drugs. The robustness of the methods were evaluate, facing the temperature and flow changes, where they showed robustness just with the preview conditions established of temperature and flow, abrupt changes may influence with the results of methods
Forma da paisagem como critério para otimização amostral de latossolos sob cultivo de cana-de-açúcar
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Antenna arrays are able to provide high and controlled directivity, which are suitable for radiobase stations, radar systems, and point-to-point or satellite links. The optimization of an array design is usually a hard task because of the non-linear characteristic of multiobjective, requiring the application of numerical techniques, such as genetic algorithms. Therefore, in order to optimize the electronic control of the antenna array radiation pattem through genetic algorithms in real codification, it was developed a numerical tool which is able to positioning the array major lobe, reducing the side lobe levels, canceling interference signals in specific directions of arrival, and improving the antenna radiation performance. This was accomplished by using antenna theory concepts and optimization methods, mainly genetic algorithms ones, allowing to develop a numerical tool with creative genes codification and crossover rules, which is one of the most important contribution of this work. The efficiency of the developed genetic algorithm tool is tested and validated in several antenna and propagation applications. 11 was observed that the numerical results attend the specific requirements, showing the developed tool ability and capacity to handle the considered problems, as well as a great perspective for application in future works.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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A hierarchical fuzzy control scheme is applied to improve vibration suppression by using an electro-mechanical system based on the lever principle. The hierarchical intelligent controller consists of a hierarchical fuzzy supervisor, one fuzzy controller and one robust controller. The supervisor combines controllers output signal to generate the control signal that will be applied on the plant. The objective is to improve the performance of the electromechanical system, considering that the supervisor could take advantage of the different techniques based controllers. The robust controller design is based on a linear mathematical model. Genetic algorithms are used on the fuzzy controller and the supervisor tuning, which are based on non-linear mathematical model. In order to attest the efficiency of the hierarchical fuzzy control scheme, digital simulations were employed. Some comparisons involving the optimized hierarchical controller and the non-optimized hierarchical controller will be made to prove the efficiency of the genetic algorithms and the advantages of its use
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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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This work purposes the application of a methodology to optimize the implantation cost of an wind-solar hybrid system for oil pumping. The developed model is estimated the implantation cost of system through Multiple Linear Regression technique, on the basis of the previous knowledge of variables: necessary capacity of storage, total daily energy demand, wind power, module power and module number. These variables are gotten by means of sizing. The considered model not only can be applied to the oil pumping, but also for any other purposes of electric energy generation for conversion of solar, wind or solar-wind energy, that demand short powers. Parametric statistical T-student tests had been used to detect the significant difference in the average of total cost to being considered the diameter of the wind, F by Snedecor in the variance analysis to test if the coefficients of the considered model are significantly different of zero and test not-parametric statistical by Friedman, toverify if there is difference in the system cost, by being considered the photovoltaic module powers. In decision of hypothesis tests was considered a 5%-significant level. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 3 HP. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 5 HP only to wind speed of 4m/s and 6 m/s in wind of 3 m, 4m and 5 m of diameter. There was not significant difference in costs to diameters of winds of 3 m and 4m. The mathematical model and the computational program may be used to others applications which require electrical between 2.250 W and 3.750 W. A computational program was developed to assist the study of several configurations that optimizes the implantation cost of an wind-solar system through considered mathematical model
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This work proposes a formulation for optimization of 2D-structure layouts submitted to mechanic and thermal shipments and applied an h-adaptive filter process which conduced to computational low spend and high definition structural layouts. The main goal of the formulation is to minimize the structure mass submitted to an effective state of stress of von Mises, with stability and lateral restriction variants. A criterion of global measurement was used for intents a parametric condition of stress fields. To avoid singularity problems was considerate a release on the stress restriction. On the optimization was used a material approach where the homogenized constructive equation was function of the material relative density. The intermediary density effective properties were represented for a SIMP-type artificial model. The problem was simplified by use of the method of finite elements of Galerkin using triangles with linear Lagrangian basis. On the solution of the optimization problem, was applied the augmented Lagrangian Method, that consists on minimum problem sequence solution with box-type restrictions, resolved by a 2nd orderprojection method which uses the method of the quasi-Newton without memory, during the problem process solution. This process reduces computational expends showing be more effective and solid. The results materialize more refined layouts with accurate topologic and shape of structure definitions. On the other hand formulation of mass minimization with global stress criterion provides to modeling ready structural layouts, with violation of the criterion of homogeneous distributed stress
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This work presents an optimization technique based on structural topology optimization methods, TOM, designed to solve problems of thermoelasticity 3D. The presented approach is based on the adjoint method of sensitivity analysis unified design and is intended to loosely coupled thermomechanical problems. The technique makes use of analytical expressions of sensitivities, enabling a reduction in the computational cost through the use of a coupled field adjoint equation, defined in terms the of temperature and displacement fields. The TOM used is based on the material aproach. Thus, to make the domain is composed of a continuous distribution of material, enabling the use of classical models in nonlinear programming optimization problem, the microstructure is considered as a porous medium and its constitutive equation is a function only of the homogenized relative density of the material. In this approach, the actual properties of materials with intermediate densities are penalized based on an artificial microstructure model based on the SIMP (Solid Isotropic Material with Penalty). To circumvent problems chessboard and reduce dependence on layout in relation to the final optimal initial mesh, caused by problems of numerical instability, restrictions on components of the gradient of relative densities were applied. The optimization problem is solved by applying the augmented Lagrangian method, the solution being obtained by applying the finite element method of Galerkin, the process of approximation using the finite element Tetra4. This element has the ability to interpolate both the relative density and the displacement components and temperature. As for the definition of the problem, the heat load is assumed in steady state, i.e., the effects of conduction and convection of heat does not vary with time. The mechanical load is assumed static and distributed
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Different compositions of Ni0,5-xCuxZn0,5Fe2O4 and Ni0,5-xCoxZn0,5Fe2O4 0 ≤ x ≤ 0.3 were synthesized ferrite y the citrate precursor method. The stoichiometric compositions were calcined in air at 350°C and then pressed into pellets and toroids. The pressed samples were sintered at temperatures of 1000, 1050 and 1100°C/3h in air control at the speed of heating and cooling. The calcined powders were characterized by XRD, TGA / DTG, FTIR, SEM and vibrating sample magnetometry (VSM) and the sintered samples by XRD, SEM, MAV, density and measurements of permeability and magnetic losses. There was pure phase formation ferrimagnetism applied at all temperatures except for A-I composition at all sintering temperatures and A-II only at a temperature of 1100°C. Crystallite sizes were obtained by Rietveld analysis, nanometer size from 11 to 20 nm for the calcined powders. For SEM, the sintered samples showed grain size between 1 and 10 micrometers. Bulk density (ρ) of sintered material presented to the Families almost linear behavior with increasing temperature and a tendency to decrease with increasing concentration of copper, different behavior of the B Family, where the increase in temperature decreased the density. The magnetic measurements revealed the powder characteristics of a soft ferrimagnetic material. Two processes of magnetization were considered, the superparamagnetism at low temperatures (350°C) and the formation of magnetic domains at higher temperatures. Obtaining the best parameters for P and B-II magnetic ferrites at high temperatures. The sintered material at 1000°C showed a relative permeability (μ) from 50 to 800 for the A Family and from 10 to 600 for the B Family. The samples sintered at 1100°C, B Family showed a variation from 10 to 1000 and the magnetic loss (tan δ) of A and B Families, around of 1. The frequency response of the toroidal core is in the range of 0.3 kHz. Several factors contribute to the behavior of microstructure considering the quantities μ and tan δ, such as the grain size, inter-and intragranular porosity, amount of grain boundary and the aspects of the dynamics of domain walls at high frequencies.
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The separation methods are reduced applications as a result of the operational costs, the low output and the long time to separate the uids. But, these treatment methods are important because of the need for extraction of unwanted contaminants in the oil production. The water and the concentration of oil in water should be minimal (around 40 to 20 ppm) in order to take it to the sea. Because of the need of primary treatment, the objective of this project is to study and implement algorithms for identification of polynomial NARX (Nonlinear Auto-Regressive with Exogenous Input) models in closed loop, implement a structural identification, and compare strategies using PI control and updated on-line NARX predictive models on a combination of three-phase separator in series with three hydro cyclones batteries. The main goal of this project is to: obtain an optimized process of phase separation that will regulate the system, even in the presence of oil gushes; Show that it is possible to get optimized tunings for controllers analyzing the mesh as a whole, and evaluate and compare the strategies of PI and predictive control applied to the process. To accomplish these goals a simulator was used to represent the three phase separator and hydro cyclones. Algorithms were developed for system identification (NARX) using RLS(Recursive Least Square), along with methods for structure models detection. Predictive Control Algorithms were also implemented with NARX model updated on-line, and optimization algorithms using PSO (Particle Swarm Optimization). This project ends with a comparison of results obtained from the use of PI and predictive controllers (both with optimal state through the algorithm of cloud particles) in the simulated system. Thus, concluding that the performed optimizations make the system less sensitive to external perturbations and when optimized, the two controllers show similar results with the assessment of predictive control somewhat less sensitive to disturbances