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  • 标题:Risk and reliability evaluation of gas connector systems using fuzzy theory and expert elicitation
  • 本地全文:下载
  • 作者:Richard Olawoyin ; Amir H. Alavi ; Reviewing Editor
  • 期刊名称:Cogent Engineering
  • 电子版ISSN:2331-1916
  • 出版年度:2017
  • 卷号:4
  • 期号:1
  • 页码:1372731
  • DOI:10.1080/23311916.2017.1372731
  • 语种:English
  • 出版社:Taylor and Francis Ltd
  • 摘要:Abstract Gas connectors are installed in almost every home in the United States and around the world. The reliability of these connectors is quintessential in protecting people, property and the environment. The critical heuristic analysis model presented in this study assessed the reliability of fuel gas connectors (FGC), the likelihood of FGC failure, potential hazards, causes and consequences in a common perspective. The “Bow-tie” method was introduced to integrate the fault tree analysis (FTA) and the event tree analysis (ETA). 31 minimal cut sets and 33 basic events (BEs) of the FTA were determined from qualitative analysis, while the important measures analyses of BEs and the failure probability of the top event Pr T E were analyzed quantitatively. Traditional risk assessment techniques (RAT) considered the probabilities of basic events (BEs) as accurate values without accounting for uncertainty and impression with some BEs. This study improved on the traditional RAT by integrating expert elicitation technique and fuzzy set theories (FST) for the evaluation of these events. FST minimized the uncertainty and fuzziness of the events, the Pr TE = 5.138 × 10 - 2 and flexible gas connectors were determined to be safer for use and have the lowest failure risk compared to black iron pipe. The approach used in this study considered multi-dimensional approach for effectively analyzing fuzzy events and the outcomes are helpful to professionals in making decisions on the preventive, protective and corrective actions necessary in the risk management process.
  • 关键词:fuel gas connectors ; fault tree analysis ; failure probability ; fussy theory ; expert elicitation ; risk index
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