Citation

Khakzad N. Risk Anal. 2018; 38(7): 1444-1454.

Copyright

(Copyright © 2018, Society for Risk Analysis, Publisher John Wiley and Sons)

DOI

10.1111/risa.12946

PMID

29193193

Abstract

The performance of fire protection measures plays a key role in the prevention and mitigation of fire escalation (fire domino effect) in process plants. In addition to passive and active safety measures, the intervention of firefighting teams can have a great impact on fire propagation. In the present study, we have demonstrated an application of dynamic Bayesian network to modeling and safety assessment of fire domino effect in oil terminals while considering the effect of safety measures in place. The results of the developed dynamic Bayesian network-prior and posterior probabilities-have been combined with information theory, in the form of mutual information, to identify optimal firefighting strategies, especially when the number of fire trucks is not sufficient to handle all the vessels in danger.

© 2017 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Language: en

Keywords

Domino effect; dynamic Bayesian network; entropy; firefighting; mutual information; oil terminal