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Fuzzy Bayesian Network-Bow-Tie Analysis of Gas Leakage during Biomass Gasification

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  • Fang Yan
  • Kaili Xu
  • Xiwen Yao
  • Yang Li

Abstract

Biomass gasification technology has been rapidly developed recently. But fire and poisoning accidents caused by gas leakage restrict the development and promotion of biomass gasification. Therefore, probabilistic safety assessment (PSA) is necessary for biomass gasification system. Subsequently, Bayesian network-bow-tie (BN-bow-tie) analysis was proposed by mapping bow-tie analysis into Bayesian network (BN). Causes of gas leakage and the accidents triggered by gas leakage can be obtained by bow-tie analysis, and BN was used to confirm the critical nodes of accidents by introducing corresponding three importance measures. Meanwhile, certain occurrence probability of failure was needed in PSA. In view of the insufficient failure data of biomass gasification, the occurrence probability of failure which cannot be obtained from standard reliability data sources was confirmed by fuzzy methods based on expert judgment. An improved approach considered expert weighting to aggregate fuzzy numbers included triangular and trapezoidal numbers was proposed, and the occurrence probability of failure was obtained. Finally, safety measures were indicated based on the obtained critical nodes. The theoretical occurrence probabilities in one year of gas leakage and the accidents caused by it were reduced to 1/10.3 of the original values by these safety measures.

Suggested Citation

  • Fang Yan & Kaili Xu & Xiwen Yao & Yang Li, 2016. "Fuzzy Bayesian Network-Bow-Tie Analysis of Gas Leakage during Biomass Gasification," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-21, July.
    • Handle: RePEc:plo:pone00:0160045
    DOI: 10.1371/journal.pone.0160045
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    References listed on IDEAS

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    Cited by:

    1. Luis Serrano-Gomez & Jose Ignacio Munoz-Hernandez, 2019. "Monte Carlo approach to fuzzy AHP risk analysis in renewable energy construction projects," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-20, June.
    2. Mohammad Yazdi, 2019. "A review paper to examine the validity of Bayesian network to build rational consensus in subjective probabilistic failure analysis," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(1), pages 1-18, February.
    3. Tan, Jiawei & Chen, Xingyu & Bu, Yang & Wang, Feng & Wang, Jialing & Huang, Xianan & Hu, Zhenda & Liu, Lin & Lin, Changzhui & Meng, Chao & Lin, Jian & Xie, Shan & Xu, Jinmei & Jing, Rui & Zhao, Yingru, 2024. "Incorporating FFTA based safety assessment of lithium-ion battery energy storage systems in multi-objective optimization for integrated energy systems," Applied Energy, Elsevier, vol. 367(C).
    4. Luis Serrano-Gomez & Jose Ignacio Muñoz-Hernandez, 2020. "Risk Influence Analysis Assessing the Profitability of Large Photovoltaic Plant Construction Projects," Sustainability, MDPI, vol. 12(21), pages 1-16, November.

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