Predicting correlation coefficients for Monte Carlo eigenvalue simulations with multitype branching process

© 2017 Elsevier Ltd This paper provides a prediction method of the generation-to-generation correlations as observed when solving large scale eigenvalue problems such as full core nuclear reactor simulations. Knowing the correlations enables correction of the variance underestimation that occurs whe...

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Main Authors: Miao, Jilang, Forget, Benoit, Smith, Kord
Other Authors: Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
Format: Article
Language:English
Published: Elsevier BV 2021
Online Access:https://hdl.handle.net/1721.1/134884
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author Miao, Jilang
Forget, Benoit
Smith, Kord
author2 Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
author_facet Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
Miao, Jilang
Forget, Benoit
Smith, Kord
author_sort Miao, Jilang
collection MIT
description © 2017 Elsevier Ltd This paper provides a prediction method of the generation-to-generation correlations as observed when solving large scale eigenvalue problems such as full core nuclear reactor simulations. Knowing the correlations enables correction of the variance underestimation that occurs when assuming that the active generations are independent. The Monte Carlo power iteration is cast in the Multitype Branching Process (MBP) framework by discretizing the neutron phase space which allows calculation of spatial and temporal moments. These moments can then provide auto-correlation coefficients between the generations of MBP and are shown to accurately predict the auto-correlation coefficients of the original Monte Carlo simulation. This prediction capability was demonstrated on the full core 2D PWR BEAVRS benchmark and compared successfully with variance estimates from independent simulations.
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spelling mit-1721.1/1348842023-09-07T20:38:23Z Predicting correlation coefficients for Monte Carlo eigenvalue simulations with multitype branching process Miao, Jilang Forget, Benoit Smith, Kord Massachusetts Institute of Technology. Department of Nuclear Science and Engineering © 2017 Elsevier Ltd This paper provides a prediction method of the generation-to-generation correlations as observed when solving large scale eigenvalue problems such as full core nuclear reactor simulations. Knowing the correlations enables correction of the variance underestimation that occurs when assuming that the active generations are independent. The Monte Carlo power iteration is cast in the Multitype Branching Process (MBP) framework by discretizing the neutron phase space which allows calculation of spatial and temporal moments. These moments can then provide auto-correlation coefficients between the generations of MBP and are shown to accurately predict the auto-correlation coefficients of the original Monte Carlo simulation. This prediction capability was demonstrated on the full core 2D PWR BEAVRS benchmark and compared successfully with variance estimates from independent simulations. 2021-10-27T20:09:39Z 2021-10-27T20:09:39Z 2018 2019-09-26T13:55:10Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/134884 en 10.1016/J.ANUCENE.2017.10.014 Annals of Nuclear Energy Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier BV Prof. Forget via Chris Sherratt
spellingShingle Miao, Jilang
Forget, Benoit
Smith, Kord
Predicting correlation coefficients for Monte Carlo eigenvalue simulations with multitype branching process
title Predicting correlation coefficients for Monte Carlo eigenvalue simulations with multitype branching process
title_full Predicting correlation coefficients for Monte Carlo eigenvalue simulations with multitype branching process
title_fullStr Predicting correlation coefficients for Monte Carlo eigenvalue simulations with multitype branching process
title_full_unstemmed Predicting correlation coefficients for Monte Carlo eigenvalue simulations with multitype branching process
title_short Predicting correlation coefficients for Monte Carlo eigenvalue simulations with multitype branching process
title_sort predicting correlation coefficients for monte carlo eigenvalue simulations with multitype branching process
url https://hdl.handle.net/1721.1/134884
work_keys_str_mv AT miaojilang predictingcorrelationcoefficientsformontecarloeigenvaluesimulationswithmultitypebranchingprocess
AT forgetbenoit predictingcorrelationcoefficientsformontecarloeigenvaluesimulationswithmultitypebranchingprocess
AT smithkord predictingcorrelationcoefficientsformontecarloeigenvaluesimulationswithmultitypebranchingprocess