Abstract
In Chapter 3, Bayesian network (BN) was shown to be a robust technique for modeling complicated dependencies and calculating the escalation probabilities during domino effects. However, application of BN to large process plants where tens and even hundreds of units can potentially get involved in domino effects would be too time-consuming and error prone due to the emergence of large and intractable conditional probability tables.
Original language | English |
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Title of host publication | Dynamic Risk Assessment and Management of Domino Effects and Cascading Events in the Process Industry |
Publisher | Elsevier |
Pages | 133-153 |
Number of pages | 21 |
ISBN (Electronic) | 9780081028384 |
DOIs | |
Publication status | Published - 2021 |
Keywords
- Centrality metrics
- Domino effect
- Graph theory
- Process plants
- Vulnerability