Topic
Dynamic Monte Carlo method
About: Dynamic Monte Carlo method is a research topic. Over the lifetime, 13294 publications have been published within this topic receiving 371256 citations.
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TL;DR: The results open a framework of quantitative description to close the gap between the mesoscopic capillary wave theory and the sharpest level of resolution for the intrinsic density distribution, relative to the first atomic layer in the liquid surface, as done in the interpretation of experimental x-ray reflectivity.
Abstract: We develop and test an operational definition of the intrinsic surface for liquid-vapor interfaces. The application to the microscopic configurations along Monte Carlo computer simulations gives the statistical properties of the intrinsic surfaces and the intrinsic density profiles for simple fluid models. The results open a framework of quantitative description to close the gap between the mesoscopic capillary wave theory and the sharpest level of resolution for the intrinsic density distribution, relative to the first atomic layer in the liquid surface, as done in the interpretation of experimental x-ray reflectivity.
169 citations
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TL;DR: The statistical distribution of capture times is obtained from Monte Carlo calculations and shows a crossover from power-law to exponential behavior, and predicts the distribution function for a lattice with perfect mixing.
168 citations
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168 citations
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TL;DR: In this paper, the weighted integral method and the Monte Carlo simulation are used together with innovative solution strategies based on the Preconditioned Conjugate Gradient method (PCG) to produce robust and efficient solutions for the stochastic finite element analysis of space frames.
168 citations
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TL;DR: A methodology for convergence analysis of Monte Carlo simulations and therefore for the reliability assessment of the inferred statistical moments is proposed, based on simple rules of statistical inference, which can be extended to different application fields.
Abstract: [1] Numerical Monte Carlo simulation is considered to be one of the main tools to be used in groundwater hydrology (1) to quantify the uncertainty in the flow predictions due to imperfect knowledge of aquifer architecture, hydraulic parameters, and forcing terms or (2) to assess the reliability of approximated moment-based equations for flow and/or transport. While the Monte Carlo framework is conceptually straightforward and very flexible, it is recognized as lacking well-established convergence criteria. Here we propose a methodology for convergence analysis of Monte Carlo simulations and therefore for the reliability assessment of the inferred statistical moments. The methodology, based on simple rules of statistical inference, is described with reference to a typical groundwater flow problem and can be extended to different application fields.
168 citations