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Acceleration methods for Monte Carlo particle transport simulations

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dc.contributor.advisor Kord S. Smith and Benoit Forget. en_US Li, Lulu, Ph. D. Massachusetts Institute of Technology en_US
dc.contributor.other Massachusetts Institute of Technology. Department of Nuclear Science and Engineering. en_US 2017-12-05T19:16:35Z 2017-12-05T19:16:35Z 2017 en_US 2017 en_US
dc.description Thesis: Ph. D., Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, 2017. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (pages 166-175). en_US
dc.description.abstract Performing nuclear reactor core physics analysis is a crucial step in the process of both designing and understanding nuclear power reactors. Advancements in the nuclear industry demand more accurate and detailed results from reactor analysis. Monte Carlo (MC) eigenvalue neutron transport methods are uniquely qualified to provide these results, due to their accurate treatment of space, angle, and energy dependencies of neutron distributions. Monte Carlo eigenvalue simulations are, however, challenging, because they must resolve the fission source distribution and accumulate sufficient tally statistics, resulting in prohibitive run times. This thesis proposes the Low Order Operator (LOO) acceleration method to reduce the run time challenge, and provides analyses to support its use for full-scale reactor simulations. LOO is implemented in the continuous energy Monte Carlo code, OpenMC, and tested in 2D PWR benchmarks. The Low Order Operator (LOO) acceleration method is a deterministic transport method based on the Method of Characteristics. Similar to Coarse Mesh Finite Difference (CMFD), the other acceleration method evaluated in this thesis, LOO parameters are constructed from Monte Carlo tallies. The solutions to the LOO equations are then used to update Monte Carlo fission sources. This thesis deploys independent simulations to rigorously assess LOO, CMFD, and unaccelerated Monte Carlo, simulating up to a quarter of a trillion neutron histories for each simulation. Analysis and performance models are developed to address two aspects of the Monte Carlo run time challenge. First, this thesis demonstrates that acceleration methods can reduce the vast number of neutron histories required to converge the fission source distribution before tallies can be accumulated. Second, the slow convergence of tally statistics is improved with the acceleration methods for the earlier active cycles. A theoretical model is developed to explain the observed behaviors and predict convergence rates. Finally, numerical results and theoretical models shed light on the selection of optimal simulation parameters such that a desired statistical uncertainty can be achieved with minimum neutron histories. This thesis demonstrates that the conventional wisdom (e.g., maximizing the number of cycles rather than the number of neutrons per cycle) in performing unaccelerated MC simulations can be improved simply by using more optimal parameters. LOO acceleration provides reduction of a factor of at least 2.2 in neutron histories, compared to the unaccelerated Monte Carlo scheme, and the CPU time and memory overhead associated with LOO are small. en_US
dc.description.statementofresponsibility by Lulu Li. en_US
dc.format.extent 175 pages en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. en_US
dc.rights.uri en_US
dc.subject Nuclear Science and Engineering. en_US
dc.title Acceleration methods for Monte Carlo particle transport simulations en_US
dc.type Thesis en_US Ph. D. en_US
dc.contributor.department Massachusetts Institute of Technology. Department of Nuclear Science and Engineering. en_US
dc.identifier.oclc 1012938659 en_US

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