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https://doi.org/10.21256/zhaw-24475| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database |
| Autor/-in: | Mignan, Arnaud Spada, Matteo Burgherr, Peter Wang, Ziqi Sornette, Didier |
| et. al: | No |
| DOI: | 10.1371/journal.pone.0263962 10.21256/zhaw-24475 |
| Erschienen in: | PLOS ONE |
| Band(Heft): | 17 |
| Heft: | 2 |
| Seite(n): | e0263962 |
| Erscheinungsdatum: | 2022 |
| Verlag / Hrsg. Institution: | Public Library of Science |
| ISSN: | 1932-6203 |
| Sprache: | Englisch |
| Fachgebiet (DDC): | 363: Umwelt- und Sicherheitsprobleme |
| Zusammenfassung: | Organized into a global network of critical infrastructures, the oil & gas industry remains to this day the main energy contributor to the world's economy. Severe accidents occasionally occur resulting in fatalities and disruption. We build an oil & gas accident graph based on more than a thousand severe accidents for the period 1970-2016 recorded for refineries, tankers, and gas networks in the authoritative ENergy-related Severe Accident Database (ENSAD). We explore the distribution of potential chains-of-events leading to severe accidents by combining graph theory, Markov analysis and catastrophe dynamics. Using centrality measures, we first verify that human error is consistently the main source of accidents and that explosion, fire, toxic release, and element rupture are the principal sinks, but also the main catalysts for accident amplification. Second, we quantify the space of possible chains-of-events using the concept of fundamental matrix and rank them by defining a likelihood-based importance measure γ. We find that chains of up to five events can play a significant role in severe accidents, consisting of feedback loops of the aforementioned events but also of secondary events not directly identifiable from graph topology and yet participating in the most likely chains-of-events. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/24475 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Nachhaltige Entwicklung (INE) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2022_Mignan-etal_Dynamics-severe-accidents-oil-gas-energy-sector.pdf | 2.31 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Mignan, A., Spada, M., Burgherr, P., Wang, Z., & Sornette, D. (2022). Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database. Plos One, 17(2), e0263962. https://doi.org/10.1371/journal.pone.0263962
Mignan, A. et al. (2022) ‘Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database’, PLOS ONE, 17(2), p. e0263962. Available at: https://doi.org/10.1371/journal.pone.0263962.
A. Mignan, M. Spada, P. Burgherr, Z. Wang, and D. Sornette, “Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database,” PLOS ONE, vol. 17, no. 2, p. e0263962, 2022, doi: 10.1371/journal.pone.0263962.
MIGNAN, Arnaud, Matteo SPADA, Peter BURGHERR, Ziqi WANG und Didier SORNETTE, 2022. Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database. PLOS ONE. 2022. Bd. 17, Nr. 2, S. e0263962. DOI 10.1371/journal.pone.0263962
Mignan, Arnaud, Matteo Spada, Peter Burgherr, Ziqi Wang, and Didier Sornette. 2022. “Dynamics of Severe Accidents in the Oil & Gas Energy Sector Derived from the Authoritative ENergy-Related Severe Accident Database.” Plos One 17 (2): e0263962. https://doi.org/10.1371/journal.pone.0263962.
Mignan, Arnaud, et al. “Dynamics of Severe Accidents in the Oil & Gas Energy Sector Derived from the Authoritative ENergy-Related Severe Accident Database.” Plos One, vol. 17, no. 2, 2022, p. e0263962, https://doi.org/10.1371/journal.pone.0263962.
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