Application of Bayesian network to domino effect assessment

2021 ◽  
pp. 49-71
Author(s):  
Nima Khakzad ◽  
Faisal Khan
Keyword(s):  
Bayesian Network ◽  
Domino Effect ◽  
Effect Assessment

scholarly journals A Tutorial on Fire Domino Effect Modeling Using Bayesian Networks

Modelling ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 240-258
Author(s):  
Nima Khakzad
Keyword(s):  
Risk Assessment ◽  
Bayesian Networks ◽  
Bayesian Network ◽  
Synergistic Effects ◽  
Dynamic Bayesian Network ◽  
Event Tree ◽  
Domino Effect ◽  
Reasoning Under Uncertainty ◽  
Event Tree Analysis ◽  
Probabilistic Network

High complexity and growing interdependencies of chemical and process facilities have made them increasingly vulnerable to domino effects. Domino effects, particularly fire dominoes, are spatial-temporal phenomena where not only the location of involved units, but also their temporal entailment in the accident chain matter. Spatial-temporal dependencies and uncertainties prevailing during domino effects, arising mainly from possible synergistic effects and randomness of potential events, restrict the use of conventional risk assessment techniques such as fault tree and event tree. Bayesian networks—a type of probabilistic network for reasoning under uncertainty—have proven to be a reliable and robust technique for the modeling and risk assessment of domino effects. In the present study, applications of Bayesian networks to modeling and safety assessment of domino effects in petroleum tank terminals has been demonstrated via some examples. The tutorial starts by illustrating the inefficacy of event tree analysis in domino effect modeling and then discusses the capabilities of Bayesian network and its derivatives such as dynamic Bayesian network and influence diagram. It is also discussed how noisy OR can be used to significantly reduce the complexity and number of conditional probabilities required for model establishment.

Domino effect assessment in the framework of industry 4.0

2021 ◽  
pp. 495-517
Author(s):  
Faisal Khan ◽  
Md Tanjin Amin ◽  
Valerio Cozzani ◽  
Genserik Reniers
Keyword(s):  
Industry 4.0 ◽  
Domino Effect ◽  
Effect Assessment

Risk Analysis for FPSO Vapor Cloud Explosion Considering Domino Effect

2018 ◽  
Author(s):  
Mian Wang ◽  
Liping Sun ◽  
Mingxin Li
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Production System ◽  
Gas Production ◽  
Domino Effect ◽  
Gas Leakage ◽  
Combustible Gas ◽  
Vapor Cloud ◽  
Offshore Oil ◽  
Oil Gas

Floating Production Storage and Offloading (FPSO), a significant offshore oil-gas production system, faces a variety of risks in the process of operation. Vapor cloud explosion (VCE) caused by combustible gas leakage is likely to occur on the topside of FPSO. As an initial accident, VCE has an effect on surrounding devices, leading to subsequent consequences and ampliative scale of the accident. The process, known as the domino effect, can result in severe consequences, indicating that it is necessary to analyze characteristics and impacts of the domino effect on FPSO. In this study, the most risky equipment is determined. VCE overpressure on device surfaces caused by gas leakage of this most risky equipment is calculated, and the results are used for analyzing the domino effect based on Bayesian network.

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