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Fault propagation behavior study and root cause reasoning with dynamic Bayesian network based framework
Institution:1. College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China;2. CNOOC Zhong Jie Petrochemical Co., Ltd, Cang Zhou 061101, China;1. College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China;2. CNOOC Zhong Jie Petrochemical Co., Ltd., Cang Zhou 061101, China;1. School of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China;2. Department of Civil & Environmental Engineering, University of Maryland, College Park, MD 20742-3021, USA;3. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice, Poland
Abstract:The Bhopal disaster was a gas leak incident in India, considered the world's worst industrial disaster happened around process facilities. Nowadays the process facilities in petrochemical industries have becoming increasingly large and automatic. There are many risk factors with complex relationships among them. Unfortunately, some operators have poor access to abnormal situation management experience due to the lack of knowledge. However these interdependencies are seldom accounted for in current risk and safety analyses, which also belonged to the main factor causing Bhopal tragedy. Fault propagation behavior of process system is studied in this paper, and a dynamic Bayesian network based framework for root cause reasoning is proposed to deal with abnormal situation. It will help operators to fully understand the relationships among all the risk factors, identify the causes that lead to the abnormal situations, and consider all available safety measures to cope with the situation. Examples from a case study for process facilities are included to illustrate the effectiveness of the proposed approach. It also provides a method to help us do things better in the future and to make sure that another such terrible accident never happens again.
Keywords:Process safety  Root cause reasoning  HAZOP  Dynamic Bayesian network  ASM"}  {"#name":"keyword"  "$":{"id":"kw0030"}  "$$":[{"#name":"text"  "_":"abnormal situation management  DBN"}  {"#name":"keyword"  "$":{"id":"kw0040"}  "$$":[{"#name":"text"  "_":"dynamic Bayesian network  HAZOP"}  {"#name":"keyword"  "$":{"id":"kw0050"}  "$$":[{"#name":"text"  "_":"hazard and operability study  FCCU"}  {"#name":"keyword"  "$":{"id":"kw0060"}  "$$":[{"#name":"text"  "_":"fluid catalytic cracking unit  CPTs"}  {"#name":"keyword"  "$":{"id":"kw0070"}  "$$":[{"#name":"text"  "_":"conditional probability tables  2TBN"}  {"#name":"keyword"  "$":{"id":"kw0080"}  "$$":[{"#name":"text"  "_":"two-slice temporal Bayesian net
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