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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Format: | Article |
Language: | English |
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Elsevier BV
2021
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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. |
first_indexed | 2024-09-23T10:00:40Z |
format | Article |
id | mit-1721.1/134884 |
institution | Massachusetts Institute of Technology |
language | English |
last_indexed | 2024-09-23T10:00:40Z |
publishDate | 2021 |
publisher | Elsevier BV |
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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 |