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Development And Implementation Of Convergence Diagnostics And Acceleration Methodologies In Monte Carlo Criticality Simulations
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Book Synopsis Development and Implementation of Convergence Diagnostics and Acceleration Methodologies in Monte Carlo Criticality Simulations by : Bo Shi
Download or read book Development and Implementation of Convergence Diagnostics and Acceleration Methodologies in Monte Carlo Criticality Simulations written by Bo Shi and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of the accuracy and ease of implementation, the Monte Carlo methodology is widely used in the analysis of nuclear systems. The estimated effective multiplication factor (keff) and flux distribution are statistical by their natures. In eigenvalue problems, however, neutron histories are not independent but are correlated through subsequent generations. Therefore, it is necessary to ensure that only the converged data are used for further analysis. Discarding a larger amount of initial histories would reduce the risk of contaminating the results by non-converged data, but increase the computational expense. This issue is amplified for large nuclear systems with slow convergence. One solution would be to use the convergence of keff or the flux distribution as the criterion for initiating accumulation of data. Although several approaches have been developed aimed at identifying convergence, these methods are not always reliable, especially for slow converging problems. This dissertation has attacked this difficulty by developing two independent but related methodologies. One aims to find a more reliable and robust way to assess convergence by statistically analyzing the local flux change. The other forms a basis to increase the convergence rate and thus reduce the computational expense. Eventually, these two topics will contribute to the ultimate goal of improving the reliability and efficiency of the Monte Carlo criticality calculations.
Book Synopsis Entropy-based Diagnostics of Criticality Monte Carlo Simulation and Higher Eigenmode Acceleration Methodology by : Bo Shi
Download or read book Entropy-based Diagnostics of Criticality Monte Carlo Simulation and Higher Eigenmode Acceleration Methodology written by Bo Shi and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of the accuracy and ease of implementation, Monte Carlo methodology is widely used in analysis of nuclear systems. The obtained estimate of the multiplication factor (keff) or flux distribution is statistical by its nature. In criticality simulation of a nuclear critical system, whose basis is the power iteration method, the guessed source distribution initially is generally away from the converged fundamental one. Therefore, it is necessary to ensure that the convergence is achieved before data are accumulated. Discarding a larger amount of initial histories could reduce the risk of contaminating the results by non-converged data but increases the computational expense. This issue is amplified for large loosely coupled nuclear systems with low convergence rate. Since keff is a generation-based global value, frequently no explicit criterion is applied to the diagnostic of keff directly. As an alternative, a flux-based entropy check available in MCNP5 works well in many cases. However, when applied to a difficult storage fuel pool benchmark problem, it could not always detect the non-convergence of flux distribution. Preliminary evaluation indicates that it is due to collapsing local information into a single number. This thesis addresses this problem by two new developments. First, it aims to find a more reliable way to assess convergence by analyzing the local flux change. Second, it introduces an approach to simultaneously compute both the first and second eigenmodes. At the same time, by computing these eigenmodes, this approach could increase the convergence rate. Improvement in these two areas could have a significant impact on practicality of Monte Carlo criticality simulations.
Book Synopsis Iterative Acceleration Methods for Monte Carlo and Deterministic Criticality Calculations by :
Download or read book Iterative Acceleration Methods for Monte Carlo and Deterministic Criticality Calculations written by and published by . This book was released on 1995 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.
Book Synopsis Theory, Application, and Implementation of Monte Carlo Method in Science and Technology by : Pooneh Saidi Bidokhti
Download or read book Theory, Application, and Implementation of Monte Carlo Method in Science and Technology written by Pooneh Saidi Bidokhti and published by BoD – Books on Demand. This book was released on 2019-12-18 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Monte Carlo method is a numerical technique to model the probability of all possible outcomes in a process that cannot easily be predicted due to the interference of random variables. It is a technique used to understand the impact of risk, uncertainty, and ambiguity in forecasting models. However, this technique is complicated by the amount of computer time required to achieve sufficient precision in the simulations and evaluate their accuracy. This book discusses the general principles of the Monte Carlo method with an emphasis on techniques to decrease simulation time and increase accuracy.
Book Synopsis Iterative Acceleration Methods for Monte Carlo and Deterministic Criticality Calculations by : Todd James Urbatsch
Download or read book Iterative Acceleration Methods for Monte Carlo and Deterministic Criticality Calculations written by Todd James Urbatsch and published by . This book was released on 1995 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advanced Modeling and Simulation of Nuclear Reactors by : Jingang Liang
Download or read book Advanced Modeling and Simulation of Nuclear Reactors written by Jingang Liang and published by Frontiers Media SA. This book was released on 2023-04-10 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Monte Carlo Methods in Statistical Physics by : Kurt Binder
Download or read book Monte Carlo Methods in Statistical Physics written by Kurt Binder and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the seven years since this volume first appeared. there has been an enormous expansion of the range of problems to which Monte Carlo computer simulation methods have been applied. This fact has already led to the addition of a companion volume ("Applications of the Monte Carlo Method in Statistical Physics", Topics in Current Physics. Vol . 36), edited in 1984, to this book. But the field continues to develop further; rapid progress is being made with respect to the implementation of Monte Carlo algorithms, the construction of special-purpose computers dedicated to exe cute Monte Carlo programs, and new methods to analyze the "data" generated by these programs. Brief descriptions of these and other developments, together with numerous addi tional references, are included in a new chapter , "Recent Trends in Monte Carlo Simulations" , which has been written for this second edition. Typographical correc tions have been made and fuller references given where appropriate, but otherwise the layout and contents of the other chapters are left unchanged. Thus this book, together with its companion volume mentioned above, gives a fairly complete and up to-date review of the field. It is hoped that the reduced price of this paperback edition will make it accessible to a wide range of scientists and students in the fields to which it is relevant: theoretical phYSics and physical chemistry , con densed-matter physics and materials science, computational physics and applied mathematics, etc.
Book Synopsis Acceleration of Monte Carlo Criticality Calculations Using Deterministic-Based Starting Sources by :
Download or read book Acceleration of Monte Carlo Criticality Calculations Using Deterministic-Based Starting Sources written by and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A new automatic approach that uses approximate deterministic solutions for providing the starting fission source for Monte Carlo eigenvalue calculations was evaluated in this analysis. By accelerating the Monte Carlo source convergence and decreasing the number of cycles that has to be skipped before the tallies estimation, this approach was found to increase the efficiency of the overall simulation, even with the inclusion of the extra computational time required by the deterministic calculation. This approach was also found to increase the reliability of the Monte Carlo criticality calculations of loosely coupled systems because the use of the better starting source reduces the likelihood of producing an undersampled k{sub eff} due to the inadequate source convergence. The efficiency improvement was demonstrated using two of the standard test problems devised by the OECD/NEA Expert Group on Source Convergence in Criticality-Safety Analysis to measure the source convergence in Monte Carlo criticality calculations. For a fixed uncertainty objective, this approach increased the efficiency of the overall simulation by factors between 1.2 and 3 depending on the difficulty of the source convergence in these problems. The reliability improvement was demonstrated in a modified version of the 'k{sub eff} of the world' problem that was specifically designed to demonstrate the limitations of the current Monte Carlo power iteration techniques. For this problem, the probability of obtaining a clearly undersampled k{sub eff} decreased from 5% with a uniform starting source to zero with a deterministic starting source when batch sizes with more than 15,000 neutron/cycle were used.
Book Synopsis Development, Implementation and Efficiency Optimization of Novel Methods to Accelerate Kinetic Monte Carlo Simulations of Reactive Systems by : Giannis Savva
Download or read book Development, Implementation and Efficiency Optimization of Novel Methods to Accelerate Kinetic Monte Carlo Simulations of Reactive Systems written by Giannis Savva and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Guide to Monte Carlo Simulations in Statistical Physics by : David Landau
Download or read book A Guide to Monte Carlo Simulations in Statistical Physics written by David Landau and published by Cambridge University Press. This book was released on 2021-07-29 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. The 5th edition contains extensive new material describing numerous powerful algorithms and methods that represent recent developments in the field. New topics such as active matter and machine learning are also introduced. Throughout, there are many applications, examples, recipes, case studies, and exercises to help the reader fully comprehend the material. This book is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.
Book Synopsis Quantum Monte Carlo Methods by : James Gubernatis
Download or read book Quantum Monte Carlo Methods written by James Gubernatis and published by Cambridge University Press. This book was released on 2016-06-02 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first textbook to provide a pedagogical examination of the major algorithms used in quantum Monte Carlo simulations.
Book Synopsis Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications by : Andreas Kling
Download or read book Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications written by Andreas Kling and published by Springer Science & Business Media. This book was released on 2014-02-22 with total page 1200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications. Special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields.
Book Synopsis Monte Carlo Methods for Applied Scientists by : Ivan Dimov
Download or read book Monte Carlo Methods for Applied Scientists written by Ivan Dimov and published by World Scientific. This book was released on 2008 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Monte Carlo method is inherently parallel and the extensive and rapid development in parallel computers, computational clusters and grids has resulted in renewed and increasing interest in this method. At the same time there has been an expansion in the application areas and the method is now widely used in many important areas of science including nuclear and semiconductor physics, statistical mechanics and heat and mass transfer. This book attempts to bridge the gap between theory and practice concentrating on modern algorithmic implementation on parallel architecture machines. Although a suitable text for final year postgraduate mathematicians and computational scientists it is principally aimed at the applied scientists: only a small amount of mathematical knowledge is assumed and theorem proving is kept to a minimum, with the main focus being on parallel algorithms development often to applied industrial problems. A selection of algorithms developed both for serial and parallel machines are provided. Sample Chapter(s). Chapter 1: Introduction (231 KB). Contents: Basic Results of Monte Carlo Integration; Optimal Monte Carlo Method for Multidimensional Integrals of Smooth Functions; Iterative Monte Carlo Methods for Linear Equations; Markov Chain Monte Carlo Methods for Eigenvalue Problems; Monte Carlo Methods for Boundary-Value Problems (BVP); Superconvergent Monte Carlo for Density Function Simulation by B-Splines; Solving Non-Linear Equations; Algorithmic Effciency for Different Computer Models; Applications for Transport Modeling in Semiconductors and Nanowires. Readership: Applied scientists and mathematicians.
Book Synopsis Monte Carlo Methods by : Neal Noah Madras
Download or read book Monte Carlo Methods written by Neal Noah Madras and published by American Mathematical Soc.. This book was released on 2000 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the proceedings of the Workshop on Monte Carlo Methods held at The Fields Institute for Research in Mathematical Sciences (Toronto, 1998). The workshop brought together researchers in physics, statistics, and probability. The papers in this volume - of the invited speakers and contributors to the poster session - represent the interdisciplinary emphasis of the conference. Monte Carlo methods have been used intensively in many branches of scientific inquiry. Markov chain methods have been at the forefront of much of this work, serving as the basis of many numerical studies in statistical physics and related areas since the Metropolis algorithm was introduced in 1953. Statisticians and theoretical computer scientists have used these methods in recent years, working on different fundamental research questions, yet using similar Monte Carlo methodology. This volume focuses on Monte Carlo methods that appear to have wide applicability and emphasizes new methods, practical applications and theoretical analysis. It will be of interest to researchers and graduate students who study and/or use Monte Carlo methods in areas of probability, statistics, theoretical physics, or computer science.
Book Synopsis An Introduction to Sequential Monte Carlo by : Nicolas Chopin
Download or read book An Introduction to Sequential Monte Carlo written by Nicolas Chopin and published by Springer Nature. This book was released on 2020-10-01 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics. The coverage is comprehensive, ranging from the underlying theory to computational implementation, methodology, and diverse applications in various areas of science. This is achieved by describing SMC algorithms as particular cases of a general framework, which involves concepts such as Feynman-Kac distributions, and tools such as importance sampling and resampling. This general framework is used consistently throughout the book. Extensive coverage is provided on sequential learning (filtering, smoothing) of state-space (hidden Markov) models, as this remains an important application of SMC methods. More recent applications, such as parameter estimation of these models (through e.g. particle Markov chain Monte Carlo techniques) and the simulation of challenging probability distributions (in e.g. Bayesian inference or rare-event problems), are also discussed. The book may be used either as a graduate text on Sequential Monte Carlo methods and state-space modeling, or as a general reference work on the area. Each chapter includes a set of exercises for self-study, a comprehensive bibliography, and a “Python corner,” which discusses the practical implementation of the methods covered. In addition, the book comes with an open source Python library, which implements all the algorithms described in the book, and contains all the programs that were used to perform the numerical experiments.
Book Synopsis A Guide to Monte Carlo Simulations in Statistical Physics by : David P. Landau
Download or read book A Guide to Monte Carlo Simulations in Statistical Physics written by David P. Landau and published by Cambridge University Press. This book was released on 2000-08-17 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, as well as in related fields, such as polymer science and lattice gauge theory. The authors give a succinct overview of simple sampling methods and develop the importance sampling method. In addition they introduce quantum Monte Carlo methods, aspects of simulations of growth phenomena and other systems far from equilibrium, and the Monte Carlo Renormalization Group approach to critical phenomena. The book includes many applications, examples, and current references, and exercises to help the reader.
Book Synopsis Quantum Monte Carlo Methods in Condensed Matter Physics by : Masuo Suzuki
Download or read book Quantum Monte Carlo Methods in Condensed Matter Physics written by Masuo Suzuki and published by World Scientific. This book was released on 1993 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews recent developments of quantum Monte Carlo methods and some remarkable applications to interacting quantum spin systems and strongly correlated electron systems. It contains twenty-two papers by thirty authors. Some of the features are as follows. The first paper gives the foundations of the standard quantum Monte Carlo method, including some recent results on higher-order decompositions of exponential operators and ordered exponentials. The second paper presents a general review of quantum Monte Carlo methods used in the present book. One of the most challenging problems in the field of quantum Monte Carlo techniques, the negative-sign problem, is also discussed and new methods proposed to partially overcome it. In addition, low-dimensional quantum spin systems are studied. Some interesting applications of quantum Monte Carlo methods to fermion systems are also presented to investigate the role of strong correlations and fluctuations of electrons and to clarify the mechanism of high-c superconductivity. Not only thermal properties but also quantum-mechanical ground-state properties have been studied by the projection technique using auxiliary fields. Further, the Haldane gap is confirmed by numerical calculations. Active researchers in the forefront of condensed matter physics as well as young graduate students who want to start learning the quantum Monte Carlo methods will find this book useful.
