Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 배석주 | - |
dc.date.accessioned | 2020-04-16T02:21:23Z | - |
dc.date.available | 2020-04-16T02:21:23Z | - |
dc.date.issued | 2019-09 | - |
dc.identifier.citation | RELIABILITY ENGINEERING & SYSTEM SAFETY, v. 189, Page. 157-164 | en_US |
dc.identifier.issn | 0951-8320 | - |
dc.identifier.issn | 1879-0836 | - |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S0951832018311992?via%3Dihub | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/151035 | - |
dc.description.abstract | A polymer electrolyte membrane fuel cell (PEMFC) stack is a multi-component system composed of continuously degrading fuel cells. The voltage degradation of the fuel cells causes the degradation of the stack system, which has two system-level degradation measures; the overall stack output voltage and the minimum voltage of individual cells. This paper develops a hierarchical Bayesian modeling and data analysis method to predict the reliability of a PEMFC stack system using the voltage degradation data collected from its fuel cell components. We introduce a two-term exponential model to describe the nonlinear voltage degradation paths of the fuel cell components, then builds a hierarchical Bayesian degradation model to predict the stack system reliability by taking a k-out-of-m:F system into account. Possible alternative modeling approaches are discussed with an in-depth comparison. This paper will contribute to the modeling and data analysis methods for continuous-state systems composed of continuous-state components. | en_US |
dc.description.sponsorship | The authors would like to thank anonymous reviewers for their constructive comments and valuable suggestions, which have helped in improving this paper significantly. This work was supported in part by the National Natural Science Foundation of China under grant NSFC#71571178. Bae's work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2018R1D1A1A09083149). | en_US |
dc.language.iso | en | en_US |
dc.publisher | ELSEVIER SCI LTD | en_US |
dc.subject | Continuous-state systems | en_US |
dc.subject | Degradation analysis | en_US |
dc.subject | Failure-time distribution | en_US |
dc.subject | Gibbs sampling | en_US |
dc.subject | Hierarchical Bayesian modeling | en_US |
dc.subject | k-out-of-m:Fsystem | en_US |
dc.title | Reliability assessment of a continuous-state fuel cell stack system with multiple degrading components | en_US |
dc.type | Article | en_US |
dc.relation.volume | 189 | - |
dc.identifier.doi | 10.1016/j.ress.2019.04.021 | - |
dc.relation.page | 157-164 | - |
dc.relation.journal | RELIABILITY ENGINEERING & SYSTEM SAFETY | - |
dc.contributor.googleauthor | Yuan, Tao | - |
dc.contributor.googleauthor | Wu, Xinying | - |
dc.contributor.googleauthor | Bae, Suk Joo | - |
dc.contributor.googleauthor | Zhu, Xiaoyan | - |
dc.relation.code | 2019001970 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF INDUSTRIAL ENGINEERING | - |
dc.identifier.pid | sjbae | - |
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