Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis
The α-k iteration method which searches the fundamental mode alpha-eigenvalue via iterative updates of the fission source distribution has been successfully used for the Monte Carlo (MC) alpha-static calculations of supercritical systems. However, the α-k iteration method for the deep subcritical sy...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Science and Technology of Nuclear Installations |
| Online Access: | http://dx.doi.org/10.1155/2015/859242 |
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| _version_ | 1832549354751131648 |
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| author | Hyung Jin Shim Sang Hoon Jang Soo Min Kang |
| author_facet | Hyung Jin Shim Sang Hoon Jang Soo Min Kang |
| author_sort | Hyung Jin Shim |
| collection | DOAJ |
| description | The α-k iteration method which searches the fundamental mode alpha-eigenvalue via iterative updates of the fission source distribution has been successfully used for the Monte Carlo (MC) alpha-static calculations of supercritical systems. However, the α-k iteration method for the deep subcritical system analysis suffers from a gigantic number of neutron generations or a huge neutron weight, which leads to an abnormal termination of the MC calculations. In order to stably estimate the prompt neutron decay constant (α) of prompt subcritical systems regardless of subcriticality, we propose a new MC alpha-static calculation method named as the α iteration algorithm. The new method is derived by directly applying the power method for the α-mode eigenvalue equation and its calculation stability is achieved by controlling the number of time source neutrons which are generated in proportion to α divided by neutron speed in MC neutron transport simulations. The effectiveness of the α iteration algorithm is demonstrated for two-group homogeneous problems with varying the subcriticality by comparisons with analytic solutions. The applicability of the proposed method is evaluated for an experimental benchmark of the thorium-loaded accelerator-driven system. |
| format | Article |
| id | doaj-art-0eca7541251944ee90fd49a7abc9d569 |
| institution | Kabale University |
| issn | 1687-6075 1687-6083 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Science and Technology of Nuclear Installations |
| spelling | doaj-art-0eca7541251944ee90fd49a7abc9d5692025-02-03T06:11:30ZengWileyScience and Technology of Nuclear Installations1687-60751687-60832015-01-01201510.1155/2015/859242859242Monte Carlo Alpha Iteration Algorithm for a Subcritical System AnalysisHyung Jin Shim0Sang Hoon Jang1Soo Min Kang2Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744, Republic of KoreaSeoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744, Republic of KoreaSeoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744, Republic of KoreaThe α-k iteration method which searches the fundamental mode alpha-eigenvalue via iterative updates of the fission source distribution has been successfully used for the Monte Carlo (MC) alpha-static calculations of supercritical systems. However, the α-k iteration method for the deep subcritical system analysis suffers from a gigantic number of neutron generations or a huge neutron weight, which leads to an abnormal termination of the MC calculations. In order to stably estimate the prompt neutron decay constant (α) of prompt subcritical systems regardless of subcriticality, we propose a new MC alpha-static calculation method named as the α iteration algorithm. The new method is derived by directly applying the power method for the α-mode eigenvalue equation and its calculation stability is achieved by controlling the number of time source neutrons which are generated in proportion to α divided by neutron speed in MC neutron transport simulations. The effectiveness of the α iteration algorithm is demonstrated for two-group homogeneous problems with varying the subcriticality by comparisons with analytic solutions. The applicability of the proposed method is evaluated for an experimental benchmark of the thorium-loaded accelerator-driven system.http://dx.doi.org/10.1155/2015/859242 |
| spellingShingle | Hyung Jin Shim Sang Hoon Jang Soo Min Kang Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis Science and Technology of Nuclear Installations |
| title | Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis |
| title_full | Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis |
| title_fullStr | Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis |
| title_full_unstemmed | Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis |
| title_short | Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis |
| title_sort | monte carlo alpha iteration algorithm for a subcritical system analysis |
| url | http://dx.doi.org/10.1155/2015/859242 |
| work_keys_str_mv | AT hyungjinshim montecarloalphaiterationalgorithmforasubcriticalsystemanalysis AT sanghoonjang montecarloalphaiterationalgorithmforasubcriticalsystemanalysis AT soominkang montecarloalphaiterationalgorithmforasubcriticalsystemanalysis |