106 resultados para Monte Carlo methods


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Matematica Aplicada e Computacional - FCT

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Pós-graduação em Biofísica Molecular - IBILCE

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In an ever more competitive environment, power distribution companies must satisfy two conflicting objectives: minimizing investment costs and the satisfaction of reliability targets. The network reconfiguration of a distribution system is a technique that well adapts to this new deregulated environment for it allows improvement of reliability indices only opening and closing switches, without the onus involved in acquiring new equipment. Due to combinatorial explosion problem characteristic, in the solution are employed metaheuristics methods, which converge to optimal or quasi-optimal solutions, but with a high computational effort. As the main objective of this work is to find the best configuration(s) of the distribution system with the best levels of reliability, the objective function used in the metaheuristics is to minimize the LOLC - Loss Of Load Cost, which is associated with both, number and duration of electric power interruptions. Several metaheuristics techniques are tested, and the tabu search has proven to be most appropriate to solve the proposed problem. To characterize computationally the problem of the switches reconfiguring was developed a vector model (with integers) of the representation of the switches, where each normally open switch is associated with a group of normally closed switches. In this model simplifications have been introduced to reduce computational time and restrictions were made to exclude solutions that do not supply energy to any load point of the system. To check violation of the voltage and loading criteria a study of power flow for the ten best solutions is performed. Also for the ten best solutions a reliability evaluation using Monte Carlo sequential simulation is performed, where it is possible to obtain the probability distributions of the indices and thus calculate the risk of paying penalty due to not meeting the goals. Finally, the methodology is applied in a real Brazilian distribution network, and the results are discussed.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In this paper distinct prior distributions are derived in a Bayesian inference of the two-parameters Gamma distribution. Noniformative priors, such as Jeffreys, reference, MDIP, Tibshirani and an innovative prior based on the copula approach are investigated. We show that the maximal data information prior provides in an improper posterior density and that the different choices of the parameter of interest lead to different reference priors in this case. Based on the simulated data sets, the Bayesian estimates and credible intervals for the unknown parameters are computed and the performance of the prior distributions are evaluated. The Bayesian analysis is conducted using the Markov Chain Monte Carlo (MCMC) methods to generate samples from the posterior distributions under the above priors.

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Due the differences between interaction physics process with matter for protons and photons, the proton beam tomography (pCT) has some vantages to comparison with conventional tomography. Also it is confirmed that usually pCT has better dose distribution and highest contrast resolution. The pCT allow not only view the internal structure of an object without destroying it, but also directly measure of volume density of electrons. Also it is confirmed that usually pCT has better dose distribution and highest contrast resolution. At the same time, there are many scientific and technical aspects to a detailed study: the capacity and limitations of the pCT methods are not well clarified. Through computations, based on Monte Carlo Method was carried out a detailed study of the contribution of non-elastic nuclear spreading, and together was compared with an analytical model for the deflection angle and the lateral deflection of protons in the target volume. The programs used were SRIM 2006 code and MCNPX v.2.50 code

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The goal of this work is to study the process of interaction of protons with matter through Monte Carlo simulation. For this purpose, it was employed the SRIM program (Stopping and Range of Ions in Matter ) and MCNPX (Monte Carlo N-Particle eXtended) v2.50. This work is going to support the development of a tomography system with protons. It was studied the interaction of proton with the follow materials: Polimethyl Mehacralate (PMMA), MS20 Tissue Substitute and water. This work employed energies in range of 50 MeV and 250 MeV, that is the range of clinical interest. The energy loss of proton after cross a material layer, the decreasing of its intensity, the angular and lateral de ection of incident beam, including and excluding nuclear interactions. This work is related with Medical Physics and Material Physics, like interaction of radiation with matter, particle transport phenomena, and the experimental methods in Nuclear Physics like simulation and computational by Monte Carlo method

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The sources of betatherapy for clinical use in Brazil are, the vast majority of strontium-90, radioactive element that is not produced in the country, and therefore requires importation of international laboratories accredited by the International Atomic Energy Agency (IAEA).The use of these resources is always limited the crediting of characteristic values supplied by the manufacturer tables that provide the nominal value of activity and dose distribution to determine the irradiation time of the injury. The Institute of Nuclear Energy Research (IPEN / CNEN-SP) has recently researching the emission profile of these types of radiation sources, and some jobs are being developed with ionization chambers extrapolation for the purpose of standardizing a systematic calibration sources betatherapy. Other studies using parallel measures dosimeters (TLD's) and simulations with the Monte Carlo method. Radiological films have also been used in studies of applicators dosimetric analysis of strontium-90. This paper seeks to analyze the different methods for calibration of applicators betatherapy, already consolidated in studies by examining the advantages and disadvantages of each procedure

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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We introduce a new kind of likelihood function based on the sequence of moments of the data distribution. Both binned and unbinned data samples are discussed, and the multivariate case is also derived. Building on this approach we lay out the formalism of shape analysis for signal searches. In addition to moment-based likelihoods, standard likelihoods and approximate statistical tests are provided. Enough material is included to make the paper self-contained from the perspective of shape analysis. We argue that the moment-based likelihoods can advantageously replace unbinned standard likelihoods for the search of nonlocal signals, by avoiding the step of fitting Monte Carlo generated distributions. This benefit increases with the number of variables simultaneously analyzed. The moment-based signal search is exemplified and tested in various 1D toy models mimicking typical high-energy signal-background configurations. Moment-based techniques should be particularly appropriate for the searches for effective operators at the LHC.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Monte Carlo simulation methods were used in order to study the conformational properties of partially ionized polyelectrolyte chains with Debye-Hückel screening in 1:1 electrolyte solution at room temperature. Configurational properties such as the distributions of probability for the square end to end distances, for the square radii of gyration and for the angles between polyion bonds were investigated as a function of the chain ionization and the salt concentration. © 1993.