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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: In this article, the Serpent 2 Monte Carlo code is used for the calculation of adjoint-weighted reactor point kinetics parameters: effective generation time and delayed neutron fractions, and the results are validated by comparison to experimental data and MCNP5 calculations in 31 critical configurations.
83 citations
01 Jan 1997
TL;DR: The Markov chain Monte Carlo method is modified so as to remove all bias in the output resulting from the biased choice of an initial state for the chain, and this method is called Coupling From The Past (CFTP).
Abstract: The Markov chain Monte Carlo method is a general technique for obtaining samples from a probability distribution. In earlier work, we showed that for many applications one can modify the Markov chain Monte Carlo method so as to remove all bias in the output resulting from the biased choice of an initial state for the chain; we have called this method Coupling From The Past (CFTP). Here we describe this method in a fashion that should make our ideas accessible to researchers from diverse areas. Our expository strategy is to avoid proofs and focus on sample applications.
83 citations
TL;DR: The Monte Carlo method is implemented to solve the direct bioheat transfer problems, which are often encountered in the treatment planning of cancer hyperthermia, and heat transfer in several three-dimensional cases was particularly studied.
Abstract: The Monte Carlo method is implemented to solve the direct bioheat transfer problems, which are often encountered in the treatment planning of cancer hyperthermia. Several algorithms were developed to solve for the temperature transients inside the biological bodies with various time or space-dependent boundary conditions, blood perfusion, metabolic rate, and volumetric heat source for the tissues. The computer code thus compiled was validated through comparison with a theoretical solution. To illustrate the applications of the present numerical strategy, heat transfer in several three-dimensional cases was particularly studied. Parametric calculations were performed to test the technical adaptability of the present Monte Carlo algorithms. Some mathematical issues thus raised are discussed.
83 citations
TL;DR: In this article, a Monte Carlo simulation is used to calculate the backscattering intensities in single and double alignment geometries, where shadowing and blocking are no longer treated separately.
83 citations
TL;DR: In this article, a series of simulations of pancreatic trypsin inhibitor were run using temperature-rescaled molecular dynamics and hybrid Monte Carlo, and it was found that simulations run using hybrid Monte-Carlo equilibrated an order of magnitude faster than those run using the same molecular dynamics.
Abstract: A formal partially dynamical approach to ergodic sampling, hybrid Monte Carlo, has been adapted for the first time from its proven application in quantum chromodynamics to realistic molecular systems. A series of simulations of pancreatic trypsin inhibitor were run using temperature-rescaled molecular dynamics and hybrid Monte Carlo. It was found that simulations run using hybrid Monte Carlo equilibrated an order of magnitude faster than those run using temperature-rescaled molecular dynamics. Certain aspects of improved performance obtained using hybrid Monte Carlo are probably due to the increased efficiency with which this algorithm explores phase space. To discuss this we introduce the notion of “trajectory stiffness”. © 1993 John Wiley & Sons, Inc.
83 citations