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A conceptual risk modelling for cargo tank fire/explosion in chemical tanker by using Evidential Reasoning -SLIM and Bayesian belief network approach

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References

2001Improving the analysis of dependable systems by mapping fault trees into Bayesian networks936 cited
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2012Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network607 cited
2012Dynamic risk analysis using bow-tie approach376 cited
2018Safety analysis of process systems using Fuzzy Bayesian Network (FBN)248 cited
2020Bayesian network modeling of accident investigation reports for aviation safety assessment216 cited
2016A hybrid human and organizational analysis method for railway accidents based on HFACS-Railway Accidents (HFACS-RAs)183 cited
2013Fuzzy fault tree analysis for fire and explosion of crude oil tanks168 cited
2019Application of Fuzzy Fault Tree Analysis (FFTA) to maritime industry: A risk analysing of ship mooring operation151 cited
2020Application of fuzzy bow-tie risk analysis to maritime transportation: The case of ship collision during the STS operation125 cited
2016Quantitative human error assessment during abandon ship procedures in maritime transportation121 cited
2007A new method for estimating human error probabilities: AHP–SLIM110 cited
2020Application of fuzzy logic to fault tree and event tree analysis of the risk for cargo liquefaction on board ship97 cited

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2005

HEPI: A new tool for human error probability calculation for offshore operation

92 cited

2021Process system failure evaluation method based on a Noisy-OR gate intuitionistic fuzzy Bayesian network in an uncertain environment81 cited

2022Operational risk assessment of ballasting and de-ballasting on-board tanker ship under FMECA extended Evidential Reasoning (ER) and Rule-based Bayesian Network (RBN) approach77 cited

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2024A large-scale group SLIM considering expert credibility under social network to estimate human error probabilities in the railway driving process14 cited
2025Human reliability analysis in inert gas operations with fuzzy CREAM-based Bayesian networks11 cited