TY - CHAP
T1 - Dynamic Risk Assessment of Fire-Induced Domino Effects
AU - Chen, Chao
AU - Reniers, Genserik
AU - Yang, Ming
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2022
Y1 - 2022
N2 - Fires are the most common scenarios in domino effect accidents, responsible for most of the domino effects that occurred in the process and chemical industry. The escalation induced by fire is delayed since the build-up of heat radiation needs time. As a result, a fire-induced domino effect is a spatial–temporal evolution process of fires. To address the dynamic characteristics, a Domino Evolution Graph (DEG) model based on dynamic graphs is developed in this chapter. The DEG model considers synergistic effects, parallel effects, and superimposed effects and overcomes the limitations of “probit models” in the second and higher-level propagations. Compared with past risk assessment methods for domino effects, the DEG model can rapidly deliver the evolution graphs (paths), the evolution time, the likelihood of domino effects, and the damage probability of installations. Therefore, the DEG model can be applied to domino risk assessment at the chemical cluster level and support the allocation of safety and security resources for preventing and mitigating fire-induced domino effects.
AB - Fires are the most common scenarios in domino effect accidents, responsible for most of the domino effects that occurred in the process and chemical industry. The escalation induced by fire is delayed since the build-up of heat radiation needs time. As a result, a fire-induced domino effect is a spatial–temporal evolution process of fires. To address the dynamic characteristics, a Domino Evolution Graph (DEG) model based on dynamic graphs is developed in this chapter. The DEG model considers synergistic effects, parallel effects, and superimposed effects and overcomes the limitations of “probit models” in the second and higher-level propagations. Compared with past risk assessment methods for domino effects, the DEG model can rapidly deliver the evolution graphs (paths), the evolution time, the likelihood of domino effects, and the damage probability of installations. Therefore, the DEG model can be applied to domino risk assessment at the chemical cluster level and support the allocation of safety and security resources for preventing and mitigating fire-induced domino effects.
UR - http://www.scopus.com/inward/record.url?scp=85118472013&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-88911-1_2
DO - 10.1007/978-3-030-88911-1_2
M3 - Chapter
AN - SCOPUS:85118472013
T3 - Springer Series in Reliability Engineering
SP - 49
EP - 68
BT - Integrating Safety and Security Management to Protect Chemical Industrial Areas from Domino Effects
PB - Springer
ER -