990 resultados para MONTE CARLOS METHOD
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We study the critical behavior of the one-dimensional pair contact process (PCP), using the Monte Carlo method for several lattice sizes and three different updating: random, sequential and parallel. We also added a small modification to the model, called Monte Carlo com Ressucitamento" (MCR), which consists of resuscitating one particle when the order parameter goes to zero. This was done because it is difficult to accurately determine the critical point of the model, since the order parameter(particle pair density) rapidly goes to zero using the traditional approach. With the MCR, the order parameter becomes null in a softer way, allowing us to use finite-size scaling to determine the critical point and the critical exponents β, ν and z. Our results are consistent with the ones already found in literature for this model, showing that not only the process of resuscitating one particle does not change the critical behavior of the system, it also makes it easier to determine the critical point and critical exponents of the model. This extension to the Monte Carlo method has already been used in other contact process models, leading us to believe its usefulness to study several others non-equilibrium models
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Existem vários métodos de simulação para calcular as propriedades críticas de sistemas; neste trabalho utilizamos a dinâmica de tempos curtos, com o intuito de testar a eficiência desta técnica aplicando-a ao modelo de Ising com diluição de sítios. A Dinâmica de tempos curtos em combinação com o método de Monte Carlos verificou que mesmo longe do equilíbrio termodinâmico o sistema já se mostra insensível aos detalhes microscópicos das interações locais e portanto, o seu comportamento universal pode ser estudado ainda no regime de não-equilíbrio, evitando-se o problema do alentecimento crítico ( critical slowing down ) a que sistema em equilíbrio fica submetido quando está na temperatura crítica. O trabalho de Huse e Janssen mostrou um comportamento universal e uma lei de escala nos sistemas críticos fora do equilíbrio e identificou a existência de um novo expoente crítico dinâmico θ, associado ao comportamento anômalo da magnetização. Fazemos uima breve revisão das transições de fase e fenômeno críticos. Descrevemos o modelo de Ising, a técnica de Monte Carlo e por final, a dinâmica de tempos curtos. Aplicamos a dinâmica de tempos curtos para o modelo de Insing ferromagnéticos em uma rede quadrada com diluição de sítios. Calculamos o expoente dinâmicos θ e z, onde verificamos que existe quebra de classe de universilidade com relação às diferentes concentrações de sítios (p=0.70,0.75,0.80,0.85,0.90,0.95,1.00). calculamos também os expoentes estáticos β e v, onde encontramos pequenas variações com a desordem. Finalmente, apresentamos nossas conclusões e possíveis extensões deste trabalho
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The behavior of plasma and sheath characteristics under the action of an applied magnetic field is important in many applications including plasma probes and material processing. Plasma immersion ion implantation (PIII) has been developed as a fast and efficient surface modification technique of complex shaped three-dimensional objects. The PIII process relies on the acceleration of ions across a high-voltage plasma sheath that develops around the target. Recent studies have shown that the sheath dynamics is significantly affected by an external magnetic field. In this work we describe a two-dimensional computer simulation of magnetic field enhanced plasma immersion implantation system. Negative bias voltage is applied to a cylindrical target located on the axis of a grounded cylindrical vacuum chamber filled with uniform nitrogen plasma. An axial magnetic field is created by a solenoid installed inside the cylindrical target. The computer code employs the Monte Carlo method for collision of electrons and neutrals in the plasma and a particle-in-cell (PIC) algorithm for simulating the movement of charged particles in the electromagnetic field. Secondary electron emission from the target subjected to ion bombardment is also included. It is found that a high-density plasma region is formed around the cylindrical target due to the intense background gas ionization by the magnetized electrons drifting in the crossed ExB fields. An increase of implantation current density in front of high density plasma region is observed. (C) 2007 Elsevier B.V. All rights reserved.
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In this paper an efficient algorithm for probabilistic analysis of unbalanced three-phase weakly-meshed distribution systems is presented. This algorithm uses the technique of Two-Point Estimate Method for calculating the probabilistic behavior of the system random variables. Additionally, the deterministic analysis of the state variables is performed by means of a Compensation-Based Radial Load Flow (CBRLF). Such load flow efficiently exploits the topological characteristics of the network. To deal with distributed generation, a strategy to incorporate a simplified model of a generator in the CBRLF is proposed. Thus, depending on the type of control and generator operation conditions, the node with distributed generation can be modeled either as a PV or PQ node. To validate the efficiency of the proposed algorithm, the IEEE 37 bus test system is used. The probabilistic results are compared with those obtained using the Monte Carlo method.
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Peng was the first to work with the Technical DFA (Detrended Fluctuation Analysis), a tool capable of detecting auto-long-range correlation in time series with non-stationary. In this study, the technique of DFA is used to obtain the Hurst exponent (H) profile of the electric neutron porosity of the 52 oil wells in Namorado Field, located in the Campos Basin -Brazil. The purpose is to know if the Hurst exponent can be used to characterize spatial distribution of wells. Thus, we verify that the wells that have close values of H are spatially close together. In this work we used the method of hierarchical clustering and non-hierarchical clustering method (the k-mean method). Then compare the two methods to see which of the two provides the best result. From this, was the parameter � (index neighborhood) which checks whether a data set generated by the k- average method, or at random, so in fact spatial patterns. High values of � indicate that the data are aggregated, while low values of � indicate that the data are scattered (no spatial correlation). Using the Monte Carlo method showed that combined data show a random distribution of � below the empirical value. So the empirical evidence of H obtained from 52 wells are grouped geographically. By passing the data of standard curves with the results obtained by the k-mean, confirming that it is effective to correlate well in spatial distribution
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The diffusive epidemic process (PED) is a nonequilibrium stochastic model which, exhibits a phase trnasition to an absorbing state. In the model, healthy (A) and sick (B) individuals diffuse on a lattice with diffusion constants DA and DB, respectively. According to a Wilson renormalization calculation, the system presents a first-order phase transition, for the case DA > DB. Several researches performed simulation works for test this is conjecture, but it was not possible to observe this first-order phase transition. The explanation given was that we needed to perform simulation to higher dimensions. In this work had the motivation to investigate the critical behavior of a diffusive epidemic propagation with Lévy interaction(PEDL), in one-dimension. The Lévy distribution has the interaction of diffusion of all sizes taking the one-dimensional system for a higher-dimensional. We try to explain this is controversy that remains unresolved, for the case DA > DB. For this work, we use the Monte Carlo Method with resuscitation. This is method is to add a sick individual in the system when the order parameter (sick density) go to zero. We apply a finite size scalling for estimates the critical point and the exponent critical =, e z, for the case DA > DB
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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In this paper, we analyze the rural-urban migration phenomenon as it is usually observed in economies which are in the early stages of industrialization. The analysis is conducted by means of a statistical mechanics approach which builds a computational agent-based model. Agents are placed on a lattice and the connections among them are described via an Ising-like model. Simulations on this computational model show some emergent properties that are common in developing economies, such as a transitional dynamics characterized by continuous growth of urban population, followed by the equalization of expected wages between rural and urban sectors (Harris-Todaro equilibrium condition), urban concentration and increasing of per capita income. (c) 2005 Elsevier B.V. All rights reserved.
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Monte Carlo simulations have been performed to investigate the structure and hydrogen bonds formation in liquid acetaldehyde. An all atom model for the acetaldehyde have been optimized in the present work. Theoretical values obtained for heat of vaporisation and density of the liquid are in good agreement with experimental data. Graphics of radial distribution function indicate a well structured liquid compared to other similar dipolar organic liquids. Molecular mechanics minimization in gas phase leads to a trimer of very stable structure. The geometry of this complex is in very good agreement with the rdf. The shortest site-site correlation is between oxygen and the carbonyl hydrogen, suggesting that this correlation play a important role in the liquid structure and properties. The O⋯H average distance and the C-H⋯O angle obtained are characteristic of weak hydrogen bonds.
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Traditionally, ancillary services are supplied by large conventional generators. However, with the huge penetration of distributed generators (DGs) as a result of the growing interest in satisfying energy requirements, and considering the benefits that they can bring along to the electrical system and to the environment, it appears reasonable to assume that ancillary services could also be provided by DGs in an economical and efficient way. In this paper, a settlement procedure for a reactive power market for DGs in distribution systems is proposed. Attention is directed to wind turbines connected to the network through synchronous generators with permanent magnets and doubly-fed induction generators. The generation uncertainty of this kind of DG is reduced by running a multi-objective optimization algorithm in multiple probabilistic scenarios through the Monte Carlo method and by representing the active power generated by the DGs through Markov models. The objectives to be minimized are the payments of the distribution system operator to the DGs for reactive power, the curtailment of transactions committed in an active power market previously settled, the losses in the lines of the network, and a voltage profile index. The proposed methodology was tested using a modified IEEE 37-bus distribution test system. © 1969-2012 IEEE.
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The transcription process is crucial to life and the enzyme RNA polymerase (RNAP) is the major component of the transcription machinery. The development of single-molecule techniques, such as magnetic and optical tweezers, atomic-force microscopy and single-molecule fluorescence, increased our understanding of the transcription process and complements traditional biochemical studies. Based on these studies, theoretical models have been proposed to explain and predict the kinetics of the RNAP during the polymerization, highlighting the results achieved by models based on the thermodynamic stability of the transcription elongation complex. However, experiments showed that if more than one RNAP initiates from the same promoter, the transcription behavior slightly changes and new phenomenona are observed. We proposed and implemented a theoretical model that considers collisions between RNAPs and predicts their cooperative behavior during multi-round transcription generalizing the Bai et al. stochastic sequence-dependent model. In our approach, collisions between elongating enzymes modify their transcription rate values. We performed the simulations in Mathematica® and compared the results of the single and the multiple-molecule transcription with experimental results and other theoretical models. Our multi-round approach can recover several expected behaviors, showing that the transcription process for the studied sequences can be accelerated up to 48% when collisions are allowed: the dwell times on pause sites are reduced as well as the distance that the RNAPs backtracked from backtracking sites. © 2013 Costa et al.
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Based on the literature data from HT-29 cell monolayers, we develop a model for its growth, analogous to an epidemic model, mixing local and global interactions. First, we propose and solve a deterministic equation for the progress of these colonies. Thus, we add a stochastic (local) interaction and simulate the evolution of an Eden-like aggregate by using dynamical Monte Carlo methods. The growth curves of both deterministic and stochastic models are in excellent agreement with the experimental observations. The waiting times distributions, generated via our stochastic model, allowed us to analyze the role of mesoscopic events. We obtain log-normal distributions in the initial stages of the growth and Gaussians at long times. We interpret these outcomes in the light of cellular division events: in the early stages, the phenomena are dependent each other in a multiplicative geometric-based process, and they are independent at long times. We conclude that the main ingredients for a good minimalist model of tumor growth, at mesoscopic level, are intrinsic cooperative mechanisms and competitive search for space. © 2013 Elsevier Ltd.
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)