Dynamic hazard identification and scenario mapping using Bayesian network

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• 作者：Peiwei Xin ; Faisal Khan ; ^{fikhan@mun.ca} ; Salim Ahmed
• 关键词：Hazard identification ; Hazard scenarios ; Bayesian network ; Risk assessment ; Dynamic hazards ; Fire and explosion hazard
• 刊名：Process Safety and Environmental Protection
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：105
• 期：Complete
• 页码：143-155
• 全文大小：3703 K
• 卷排序：105

文摘

Hazard identification is of vital importance in risk management. It is the first step of undertaking accident likelihood and associated consequence analysis. The traditional hazard identification techniques suffer from being static. New information or evolving conditions cannot be easily incorporated in already identified hazards. To overcome this, the Bayesian network is used to bring dynamics to the hazard identification step. The present work develops a new methodology to map hazard scenarios into the Bayesian network model, which enables real time hazard identification. The model presents a probability ranking for hazards using given input observations. It helps to identify the most credible hazard scenarios for further analysis. Sensitivity analyses are also conducted to investigate the influence of the input parameters on identified hazards.