The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Dynamic risk analysis using bow-tie approach
Open accessAbstract
Accident probability estimation is a common and central step to all quantitative risk assessment methods. Among many techniques available, bow-tie model (BT) is very popular because it represent the accident scenario altogether including causes and consequences. However, it suffers a static structure limiting its application in real-time monitoring and probability updating which are key factors in dynamic risk analysis. The present work is focused on using BT approach in a dynamic environment in which the occurrence probability of accident consequences changes. In this method, on one hand, failure probability of primary events of BT, leading to the top event, are developed using physical reliability models, and constantly revised as physical parameters (e.g., pressure, velocity, dimension, etc) change. And, on the other hand, the failure probability of safety barriers of the BT are periodically updated using Bayes’ theorem as new information becomes available over time. Finally, the resulting, updated BT is used to estimate the posterior probability of the consequences which in turn results in an updated risk profile.
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Metadata
- Authors
- Khakzad, N., Khan, F., & Amyotte, P.
- Venue
- Reliability Engineering & System Safety
- Publisher
- Elsevier BV
- Published
- 2012-08
- Volume
- 104
- Pages
- 36-44
- ISSN
- 0951-8320 (ISSN-L)
- OpenAlex
- W2085731719
- Cited by
- 373
- References
- 19
- FWCI
- 13.44
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
