ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULA
An analysis of the uncertainty quantification related to LBLOCA using the Monte-Carlo calculation has been performed and compared with the tolerance level determined by the Wilks’ formula. The uncertainty range and distribution of each input parameter associated with the LOCA phenomena were determin...
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doaj-6b07ef5acef04e40b07a933e53e710232020-11-24T20:54:11ZengElsevierNuclear Engineering and Technology1738-57332014-08-0146448148810.5516/NET.02.2013.047ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULASEUNG WOOK LEE0BUB DONG CHUNG1YOUNG-SEOK BANG2SUNG WON BAE3Thermal Hydraulics Safety Research Division, Korea Atomic Energy Research Institute 1045 Daedeok-daero, Yuseong-gu, Daejeon, 305-353, Republic of KoreaThermal Hydraulics Safety Research Division, Korea Atomic Energy Research Institute 1045 Daedeok-daero, Yuseong-gu, Daejeon, 305-353, Republic of KoreaKorea Institute of Nuclear Safety, 62 Guahak-ro, Yuseong-gu, Daejeon, 305-338, Republic of KoreaThermal Hydraulics Safety Research Division, Korea Atomic Energy Research Institute 1045 Daedeok-daero, Yuseong-gu, Daejeon, 305-353, Republic of KoreaAn analysis of the uncertainty quantification related to LBLOCA using the Monte-Carlo calculation has been performed and compared with the tolerance level determined by the Wilks’ formula. The uncertainty range and distribution of each input parameter associated with the LOCA phenomena were determined based on previous PIRT results and documentation during the BEMUSE project. Calulations were conducted on 3,500 cases within a 2-week CPU time on a 14-PC cluster system. The Monte-Carlo exercise shows that the 95% upper limit PCT value can be obtained well, with a 95% confidence level using the Wilks’ formula, although we have to endure a 5% risk of PCT under-prediction. The results also show that the statistical fluctuation of the limit value using Wilks’ first-order is as large as the uncertainty value itself. It is therefore desirable to increase the order of the Wilks’ formula to be higher than the second-order to estimate the reliable safety margin of the design features. It is also shown that, with its ever increasing computational capability, the Monte-Carlo method is accessible for a nuclear power plant safety analysis within a realistic time frame.http://www.sciencedirect.com/science/article/pii/S1738573315301169Uncertainty QuantificationWilks’ FormulaMonte-Carlo MethodMARS-KS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
SEUNG WOOK LEE BUB DONG CHUNG YOUNG-SEOK BANG SUNG WON BAE |
spellingShingle |
SEUNG WOOK LEE BUB DONG CHUNG YOUNG-SEOK BANG SUNG WON BAE ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULA Nuclear Engineering and Technology Uncertainty Quantification Wilks’ Formula Monte-Carlo Method MARS-KS |
author_facet |
SEUNG WOOK LEE BUB DONG CHUNG YOUNG-SEOK BANG SUNG WON BAE |
author_sort |
SEUNG WOOK LEE |
title |
ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULA |
title_short |
ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULA |
title_full |
ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULA |
title_fullStr |
ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULA |
title_full_unstemmed |
ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULA |
title_sort |
analysis of uncertainty quantification method by comparing monte-carlo method and wilks’ formula |
publisher |
Elsevier |
series |
Nuclear Engineering and Technology |
issn |
1738-5733 |
publishDate |
2014-08-01 |
description |
An analysis of the uncertainty quantification related to LBLOCA using the Monte-Carlo calculation has been performed and compared with the tolerance level determined by the Wilks’ formula. The uncertainty range and distribution of each input parameter associated with the LOCA phenomena were determined based on previous PIRT results and documentation during the BEMUSE project. Calulations were conducted on 3,500 cases within a 2-week CPU time on a 14-PC cluster system. The Monte-Carlo exercise shows that the 95% upper limit PCT value can be obtained well, with a 95% confidence level using the Wilks’ formula, although we have to endure a 5% risk of PCT under-prediction. The results also show that the statistical fluctuation of the limit value using Wilks’ first-order is as large as the uncertainty value itself. It is therefore desirable to increase the order of the Wilks’ formula to be higher than the second-order to estimate the reliable safety margin of the design features. It is also shown that, with its ever increasing computational capability, the Monte-Carlo method is accessible for a nuclear power plant safety analysis within a realistic time frame. |
topic |
Uncertainty Quantification Wilks’ Formula Monte-Carlo Method MARS-KS |
url |
http://www.sciencedirect.com/science/article/pii/S1738573315301169 |
work_keys_str_mv |
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1716795305419079680 |