22 resultados para Simulation de Monte Carlo


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ABSTRACT The citriculture consists in several environmental risks, as weather changes and pests, and also consists in considerable financial risk, mainly due to the period ofreturn on the initial investment. This study was motivated by the need to assess the risks of a business activity such as citriculture. Our objective was to build a stochastic simulation model to achieve the economic and financial analysis of an orange producer in the Midwest region of the state of Sao Paulo, under conditions of uncertainty. The parameters used were the Net Present Value (NPV), the Modified Internal Rate of Return(MIRR), and the Discounted Payback. To evaluate the risk conditions we built a probabilistic model of pseudorandom numbers generated with Monte Carlo method. The results showed that the activity analyzed provides a risk of 42.8% to reach a NPV negative; however, the yield assessed by MIRR was 7.7%, higher than the yield from the reapplication of the positive cash flows. The financial investment pays itself after the fourteenth year of activity.

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A study was carried out on the urea geometries using ab initio calculation and Monte Carlo computational simulation of liquids. The ab initio calculated results showed that urea has a non-planar conformation in the gas phase in which the hydrogen atoms are out of the plane formed by the heavy atoms. Free energies associated to the rotation of the amino groups of urea in water were obtained using the Monte Carlo method in which the thermodynamic perturbation theory is implemented. The magnitude of the free energy obtained from this simulation did not permit us to conclude that urea is non-planar in water.

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The ellipticines constitute a broad class of molecules with antitumor activity. In the present work we analyzed the structure and properties of a series of ellipticine derivatives in the gas phase and in solution using quantum mechanical and Monte Carlo methods. The results showed a good correlation between the solvation energies in water obtained with the continuum model and the Monte Carlo simulation. Molecular descriptors were considered in the development of QSAR models using the DNA association constant (log Kapp) as biological data. The results showed that the DNA binding is dominated by electronic parameters, with small contributions from the molecular volume and area.

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The aim of this paper is to present a simple way of treating the general equation for acid-base titrations based on the concept of degree of dissociation, and to propose a new spreadsheet approach for simulating the titration of mixtures of polyprotic compounds. The general expression, without any approximation, is calculated a simple iteration method, making number manipulation easy and painless. The user-friendly spreadsheet was developed by using MS-Excel and Visual-Basic-for-Excel. Several graphs are drawn for helping visualizing the titration behavior. A Monte Carlo function for error simulation was also implemented. Two examples for titration of alkalinity and McIlvaine buffer are presented.

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The most widespread literature for the evaluation of uncertainty - GUM and Eurachem - does not describe explicitly how to deal with uncertainty of the concentration coming from non-linear calibration curves. This work had the objective of describing and validating a methodology, as recommended by the recent GUM Supplement approach, to evaluate the uncertainty through polynomial models of the second order. In the uncertainty determination of the concentration of benzatone (C) by chromatography, it is observed that the uncertainty of measurement between the methodology proposed and Monte Carlo Simulation, does not diverge by more than 0.0005 unit, thus validating the model proposed for one significant digit.

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The Practical Stochastic Model is a simple and robust method to describe coupled chemical reactions. The connection between this stochastic method and a deterministic method was initially established to understand how the parameters and variables that describe the concentration in both methods were related. It was necessary to define two main concepts to make this connection: the filling of compartments or dilutions and the rate of reaction enhancement. The parameters, variables, and the time of the stochastic methods were scaled with the size of the compartment and were compared with a deterministic method. The deterministic approach was employed as an initial reference to achieve a consistent stochastic result. Finally, an independent robust stochastic method was obtained. This method could be compared with the Stochastic Simulation Algorithm developed by Gillespie, 1977. The Practical Stochastic Model produced absolute values that were essential to describe non-linear chemical reactions with a simple structure, and allowed for a correct description of the chemical kinetics.

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Techniques of evaluation of risks coming from inherent uncertainties to the agricultural activity should accompany planning studies. The risk analysis should be carried out by risk simulation using techniques as the Monte Carlo method. This study was carried out to develop a computer program so-called P-RISCO for the application of risky simulations on linear programming models, to apply to a case study, as well to test the results comparatively to the @RISK program. In the risk analysis it was observed that the average of the output variable total net present value, U, was considerably lower than the maximum U value obtained from the linear programming model. It was also verified that the enterprise will be front to expressive risk of shortage of water in the month of April, what doesn't happen for the cropping pattern obtained by the minimization of the irrigation requirement in the months of April in the four years. The scenario analysis indicated that the sale price of the passion fruit crop exercises expressive influence on the financial performance of the enterprise. In the comparative analysis it was verified the equivalence of P-RISCO and @RISK programs in the execution of the risk simulation for the considered scenario.