Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김송현 | - |
dc.date.accessioned | 2016-10-28T02:45:46Z | - |
dc.date.available | 2016-10-28T02:45:46Z | - |
dc.date.issued | 2015-04 | - |
dc.identifier.citation | JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY, Page. 1-7 | en_US |
dc.identifier.issn | 0022-3131 | - |
dc.identifier.issn | 1881-1248 | - |
dc.identifier.uri | http://www.tandfonline.com/doi/full/10.1080/00223131.2015.1038665 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/23978 | - |
dc.description.abstract | The sampling-based uncertainty analysis method is a stochastic approach to estimate response uncertainties caused by the uncertainty in the input parameters. Conventionally, to minimize the effects caused by the Monte Carlo stochastic uncertainty, lots of particle histories have been used for the uncertainty analysis. However, this can cause inefficiencies in the uncertainty analysis. To optimize the calculation efficiency, how the Monte Carlo stochastic uncertainty influences the response uncertainty should be clearly verified. In this study, a method to estimate the accuracy of the response uncertainty is proposed by introducing a standard error and an error propagation theory. Using the proposed method, response uncertainties and standard errors of the multiplication factors for three benchmark problems are evaluated by the Monte Carlo method. Our results show that the proposed method can accurately estimate the accuracy of the response uncertainty caused by the input uncertainty in using the Monte Carlo simulation method. The proposed method can be directly utilized to estimate the accuracy of the sampling-based uncertainty analysis using the Monte Carlo simulation method. Also, it is expected that the proposed method will contribute to an increase in the calculation efficiency in the sampling-based sensitivity and uncertainty analysis. | en_US |
dc.description.sponsorship | This work was supported by National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2014M2A8A1029801, 2012M2A2A6004263), Energy Efficiency & Resources of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by Korea government Ministry of Knowledge Economy (20121620100070), and Innovative Technology Center for Radiation Safety (iTRS). | en_US |
dc.language.iso | en | en_US |
dc.publisher | TAYLOR & FRANCIS LTD | en_US |
dc.subject | sensitivity and uncertainty analysis | en_US |
dc.subject | S/U analysis | en_US |
dc.subject | sampling-based | en_US |
dc.subject | Monte Carlo | en_US |
dc.subject | eigenvalue | en_US |
dc.subject | error propagation | en_US |
dc.subject | stochastic uncertainty | en_US |
dc.subject | cross section uncertainty | en_US |
dc.title | A proposal on accuracy estimation method for the sampling-based uncertainty analysis with Monte Carlo simulation technique | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1080/00223131.2015.1038665 | - |
dc.relation.page | 1-7 | - |
dc.relation.journal | JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY | - |
dc.contributor.googleauthor | Kim, Song Hyun | - |
dc.contributor.googleauthor | Song, Myung Sub | - |
dc.contributor.googleauthor | Sun, Gwang Min | - |
dc.contributor.googleauthor | Shin, Chang Ho | - |
dc.relation.code | 2015002977 | - |
dc.sector.campus | S | - |
dc.sector.daehak | RESEARCH INSTITUTE[S] | - |
dc.sector.department | INNOVATIVE TECHNOLOGY CENTER FOR RADIATION SAFETY | - |
dc.identifier.pid | nucleon | - |
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