There are no files associated with this item.
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.citation.conferencePlace | US | - |
dc.citation.conferencePlace | Hyatt Regency San FranciscoSan Francisco | - |
dc.citation.endPage | 805 | - |
dc.citation.startPage | 796 | - |
dc.citation.title | 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017 | - |
dc.contributor.author | Kang, Hyun Gook | - |
dc.contributor.author | Lee, Sang Hun | - |
dc.contributor.author | Lee, Seung Jun | - |
dc.contributor.author | Chu, Tsong-Lun | - |
dc.contributor.author | Varuttamaseni, Athi | - |
dc.contributor.author | Yue, Meng | - |
dc.contributor.author | Yang, Steve | - |
dc.contributor.author | Eom, Heung Seop | - |
dc.contributor.author | Cho, Jaehyun | - |
dc.contributor.author | Li, Ming | - |
dc.date.accessioned | 2023-12-19T18:40:56Z | - |
dc.date.available | 2023-12-19T18:40:56Z | - |
dc.date.created | 2018-01-08 | - |
dc.date.issued | 2017-06-13 | - |
dc.description.abstract | Since the digital instrumentation and control systems are expected to play an important role for the safety systems in nuclear power plants (NPPs), the need has emerged to not only establish a basis for incorporating software behavior into digital I&C system reliability models, but also to quantify the failure probability of the software used in NPP digital protection systems. In this study, a Bayesian belief network (BBN) model is developed to quantitatively assess software reliability by estimating the number of faults in a software program considering its software development life cycle (SDLC). The model structure and parameters are established based on the information applicable to NPP safety-related systems and the evidence used to construct and quantify the BBN model was collected from three stages of expert elicitation. The software failure probability is estimated from the number of residual defects in a software program at the end of SDLC phase. As case study, the BBN model was applied to quantify the software reliability of a typical digital protection software having the size of 50 function points and having the Medium development and validation and verification (V&V) qualities. The developed model can be applied to estimate the failure probability for both developing and deployed safety-related NPP software, and such results can be used to evaluate the quality of the digital I&C systems in addition to estimating potential reactor risk due to software failure. | - |
dc.identifier.bibliographicCitation | 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017, pp.796 - 805 | - |
dc.identifier.scopusid | 2-s2.0-85047833174 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/35307 | - |
dc.language | 영어 | - |
dc.publisher | 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017 | - |
dc.title | Development of a Bayesian Belief Network Model for the Software Reliability Assessment of Nuclear Digital I&C Safety Systems | - |
dc.type | Conference Paper | - |
dc.date.conferenceDate | 2017-06-11 | - |
Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Tel : 052-217-1404 / Email : scholarworks@unist.ac.kr
Copyright (c) 2023 by UNIST LIBRARY. All rights reserved.
ScholarWorks@UNIST was established as an OAK Project for the National Library of Korea.