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Risk analysis for consumer-level utility gas and liquefied petroleum gas incidents using probabilistic network modeling: A case study of gas incidents in Japan

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  • LAM, C.Y.
  • CRUZ, A.M.

Abstract

Utility gas and liquefied petroleum gas (LPG) are commonly used in Japan for their convenience as fuels for household and commercial needs. Although several efforts have been made to promote the safe use of gas, more gas accidents occur at the consumer level than in gas production facilities or in the supply chain. Incident investigations can acquire facts about the causes and effects of these accidents. In this paper, we propose a probabilistic network modeling approach in which the inherent characteristics of risk factors for consumer-level gas incidents are considered. In the approach, cause–effect chains are formulated for gas incidents, and network diagrams with probabilistic estimations are constructed to indicate the structure behind the occurrence of such incidents. The investigation shows that most gas incidents are caused by more than one risk factor, and one risk factor tends to cascade into others. These risk factors can be clustered according to their nature and can also be classified as originating causes or intermediate risk factors by analyzing their interdependencies in network diagrams. By identifying significant intermediate effects together with their causes, these risk factors can be reduced, which may reduce the occurrence of serious gas incidents at the consumer level.

Suggested Citation

  • Lam, C.Y. & Cruz, A.M., 2019. "Risk analysis for consumer-level utility gas and liquefied petroleum gas incidents using probabilistic network modeling: A case study of gas incidents in Japan," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 198-212.
  • Handle: RePEc:eee:reensy:v:185:y:2019:i:c:p:198-212
    DOI: 10.1016/j.ress.2018.12.008
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    References listed on IDEAS

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    1. Marcelo Ramos Martins & Adriana Miralles Schleder & Enrique López Droguett, 2014. "A Methodology for Risk Analysis Based on Hybrid Bayesian Networks: Application to the Regasification System of Liquefied Natural Gas Onboard a Floating Storage and Regasification Unit," Risk Analysis, John Wiley & Sons, vol. 34(12), pages 2098-2120, December.
    2. Shital A. Thekdi & James H. Lambert, 2012. "Decision Analysis and Risk Models for Land Development Affecting Infrastructure Systems," Risk Analysis, John Wiley & Sons, vol. 32(7), pages 1253-1269, July.
    3. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    4. Bucci, Paolo & Kirschenbaum, Jason & Mangan, L. Anthony & Aldemir, Tunc & Smith, Curtis & Wood, Ted, 2008. "Construction of event-tree/fault-tree models from a Markov approach to dynamic system reliability," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1616-1627.
    5. Qian Zhou & James H. Lambert & Christopher W. Karvetski & Jeffrey M. Keisler & Igor Linkov, 2012. "Flood Protection Diversification to Reduce Probabilities of Extreme Losses," Risk Analysis, John Wiley & Sons, vol. 32(11), pages 1873-1887, November.
    6. Louis Anthony (Tony) Cox, 2013. "Improving Causal Inferences in Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 33(10), pages 1762-1771, October.
    7. Shahrzad Faghih-Roohi & Yew-Soon Ong & Sobhan Asian & Allan N. Zhang, 2016. "Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks," Annals of Operations Research, Springer, vol. 247(2), pages 715-734, December.
    8. Patrick Hofstetter & James K. Hammitt, 2002. "Selecting Human Health Metrics for Environmental Decision‐Support Tools," Risk Analysis, John Wiley & Sons, vol. 22(5), pages 965-983, October.
    9. Hongyang Yu & Faisal Khan & Brian Veitch, 2017. "A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1668-1682, September.
    10. Skogdalen, Jon Espen & Vinnem, Jan Erik, 2011. "Quantitative risk analysis offshore—Human and organizational factors," Reliability Engineering and System Safety, Elsevier, vol. 96(4), pages 468-479.
    11. Chiara Verbano & Karen Venturini, 2011. "Development paths of risk management: approaches, methods and fields of application," Journal of Risk Research, Taylor & Francis Journals, vol. 14(5), pages 519-550, May.
    12. Junrui Xu & James H. Lambert, 2015. "Risk‐Cost‐Benefit Analysis for Transportation Corridors with Interval Uncertainties of Heterogeneous Data," Risk Analysis, John Wiley & Sons, vol. 35(4), pages 624-641, April.
    13. Atiq Siddiqui & Manish Verma, 2013. "An Expected Consequence Approach to Route Choice in the Maritime Transportation of Crude Oil," Risk Analysis, John Wiley & Sons, vol. 33(11), pages 2041-2055, November.
    14. Ching, Jianye & Leu, Sou-Sen, 2009. "Bayesian updating of reliability of civil infrastructure facilities based on condition-state data and fault-tree model," Reliability Engineering and System Safety, Elsevier, vol. 94(12), pages 1962-1974.
    15. Brito, Anderson J. & de Almeida, Adiel Teixeira & Mota, Caroline M.M., 2010. "A multicriteria model for risk sorting of natural gas pipelines based on ELECTRE TRI integrating Utility Theory," European Journal of Operational Research, Elsevier, vol. 200(3), pages 812-821, February.
    16. Kai Liu & Ming Wang & Yinxue Cao & Weihua Zhu & Jinshan Wu & Xiaoyong Yan, 2018. "A Comprehensive Risk Analysis of Transportation Networks Affected by Rainfall‐Induced Multihazards," Risk Analysis, John Wiley & Sons, vol. 38(8), pages 1618-1633, August.
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    Cited by:

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    3. Lam, C.Y. & Tai, K., 2020. "Network topological approach to modeling accident causations and characteristics: Analysis of railway incidents in Japan," Reliability Engineering and System Safety, Elsevier, vol. 193(C).

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