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.
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.
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:
Download or read book Development of SUBSPACE Based Hybrid Monte Carlo Deterministic Algorithms for Reactor Physics Calculations written by Qiong Zhang and published by . This book was released on 2012 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monte Carlo Criticality Calculations Using a Parallel Processor Computer written by Daniele Ugolini and published by . This book was released on 1987 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Monte Carlo Method for Calculating Initiation Probability written by and published by . This book was released on 2007 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Monte Carlo method for calculating the probability of initiating a self-sustaining neutron chain reaction has been developed. In contrast to deterministic codes which solve a non-linear, adjoint form of the Boltzmann equation to calculate initiation probability, this new method solves the forward (standard) form of the equation using a modified source calculation technique. Results from this new method are compared with results obtained from several deterministic codes for a suite of historical test problems. The level of agreement between these code predictions is quite good, considering the use of different numerical techniques and nuclear data. A set of modifications to the historical test problems has also been developed which reduces the impact of neutron source ambiguities on the calculated probabilities.
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.
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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.
Download or read book Applications of Adjoint Based Techniques in Continuous Energy Monte Carlo Criticality Calculations written by and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Fully Coupled Monte Carlo written by and published by . This book was released on 1990 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: The neutron transport equation is solved by a hybrid method that iteratively couples regions where deterministic (S{sub N}) and stochastic (Monte Carlo) methods are applied. Unlike previous hybrid methods, the Monte Carlo and S{sub N} regions are fully coupled in the sense that no assumption is made about geometrical separation or decoupling. The hybrid method provides a new means of solving problems involving both optically thick and optically thin regions that neither Monte Carlo nor S{sub N} is well suited for by themselves. The fully coupled Monte Carlo/S{sub N} technique consists of defining spatial and/or energy regions of a problem in which either a Monte Carlo calculation or an S{sub N} calculation is to be performed. The Monte Carlo region may comprise the entire spatial region for selected energy groups, or may consist of a rectangular area that is either completely or partially embedded in an arbitrary S{sub N} region. The Monte Carlo and S{sub N} regions are then connected through the common angular boundary fluxes, which are determined iteratively using the response matrix technique, and volumetric sources. The hybrid method has been implemented in the S{sub N} code TWODANT by adding special-purpose Monte Carlo subroutines to calculate the response matrices and volumetric sources, and linkage subrountines to carry out the interface flux iterations. The common angular boundary fluxes are included in the S{sub N} code as interior boundary sources, leaving the logic for the solution of the transport flux unchanged, while, with minor modifications, the diffusion synthetic accelerator remains effective in accelerating S{sub N} calculations. The special-purpose Monte Carlo routines used are essentially analog, with few variance reduction techniques employed. However, the routines have been successfully vectorized, with approximately a factor of five increase in speed over the non-vectorized version.
Download or read book Lectures on Monte Carlo Methods written by Neal Noah Madras and published by Springer Science & Business. This book was released on 2002 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the ``curse of dimensionality'', which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathematical models that arise in diverse areas of application. The book is based on lectures in a graduate course given by the author. It examines theoretical properties of Monte Carlo methods as well as practical issues concerning their computer implementation and statistical analysis. The only formal prerequisite is an undergraduate course in probability. The book is intended to be accessible to students from a wide range of scientific backgrounds. Rather than being a detailed treatise, it covers the key topics of Monte Carlo methods to the depth necessary for a researcher to design, implement, and analyze a full Monte Carlo study of a mathematical or scientific problem. The ideas are illustrated with diverse running examples. There are exercises sprinkled throughout the text. The topics covered include computer generation of random variables, techniques and examples for variance reduction of Monte Carlo estimates, Markov chain Monte Carlo, and statistical analysis of Monte Carlo output.
Download or read book Approximating Integrals Via Monte Carlo and Deterministic Methods written by Michael John Evans and published by Oxford University Press on Demand. This book was released on 2000 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to introduce graduate students and researchers to the primary methods useful for approximating integrals. The emphasis is on those methods that have been found to be of practical use, and although the focus is on approximating higher- dimensional integrals thelower-dimensional case is also covered. Included in the book are asymptotic techniques, multiple quadrature and quasi-random techniques as well as a complete development of Monte Carlo algorithms. For the Monte Carlo section importance sampling methods, variance reduction techniques and the primaryMarkov Chain Monte Carlo algorithms are covered. This book brings these various techniques together for the first time, and hence provides an accessible textbook and reference for researchers in a wide variety of disciplines.
Download or read book Neutronics written by Jean-François Parisot and published by . This book was released on 2015 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Neutronics (or neutron physics) is the study of neutrins travelling through matter, of conditions for a chain reaction, and of changes in matter's composition due to nuclear reactions. It makes it possible to design and operate nuclear reactors and fuel cycle facilities."--Publisher.
Download or read book Criticality Calculations by Monte Carlo Methods written by K. W. Morton and published by . This book was released on 1956 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Verification of the Shift Monte Carlo Code Using the C5G7 and CASL Benchmark Problems written by Nicholas Cameron Sly and published by . This book was released on 2014 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: While Monte Carlo simulation has been recognized as a powerful numerical method for use in radiation transport, it has required a mixture of methods development and hardware advancement to meet these expectations in practical applications. In an effort to continue this advancement for uses of Monte Carlo simulation in ever larger capacities, Oak Ridge National Laboratory is developing the Shift hybrid deterministic/Monte Carlo code to be massively-parallel for use on parallel computing systems of all sizes. As part of this development, verification of the Monte Carlo parts of the code is needed to confirm that the current version of the code is operating properly, by matching the results of similar, currently available codes, as well as allowing for testing of the code in the future, to ensure that subsequent code changes and the implementation of new capabilities don’t adversely affect the results. This research starts that verification using some basic reactor criticality benchmarks. The Shift code has been shown to agree within three standard deviations with MCNP and KENO, two of the most widely used Monte Carlo criticality codes. Also investigated was the efficiency of the Shift code as it currently stands, scaling with the number of processors the code is run on as well as the number of particles being simulated. The code was found to scale well, as long as there are enough particles to make the transport take significantly more time than the inter-cycle communication between compute nodes.
Download or read book Parallel Monte Carlo Synthetic Acceleration Methods for Discrete Transport Problems written by and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This work researches and develops Monte Carlo Synthetic Acceleration (MCSA) methods as a new class of solution techniques for discrete neutron transport and fluid flow problems. Monte Carlo Synthetic Acceleration methods use a traditional Monte Carlo process to approximate the solution to the discrete problem as a means of accelerating traditional fixed-point methods. To apply these methods to neutronics and fluid flow and determine the feasibility of these methods on modern hardware, three complementary research and development exercises are performed. First, solutions to the SPN discretization of the linear Boltzmann neutron transport equation are obtained using MCSA with a difficult criticality calculation for a light water reactor fuel assembly used as the driving problem. To enable MCSA as a solution technique a group of modern preconditioning strategies are researched. MCSA when compared to conventional Krylov methods demonstrated improved iterative performance over GMRES by converging in fewer iterations when using the same preconditioning. Second, solutions to the compressible Navier-Stokes equations were obtained by developing the Forward-Automated Newton-MCSA (FANM) method for nonlinear systems based on Newton's method. Three difficult fluid benchmark problems in both convective and driven flow regimes were used to drive the research and development of the method. For 8 out of 12 benchmark cases, it was found that FANM had better iterative performance than the Newton-Krylov method by converging the nonlinear residual in fewer linear solver iterations with the same preconditioning. Third, a new domain decomposed algorithm to parallelize MCSA aimed at leveraging leadership-class computing facilities was developed by utilizing parallel strategies from the radiation transport community. The new algorithm utilizes the Multiple-Set Overlapping-Domain strategy in an attempt to reduce parallel overhead and add a natural element of replication to the algorithm. It was found that for the current implementation of MCSA, both weak and strong scaling improved on that observed for production implementations of Krylov methods.
