An event-driven probabilistic methodology for modeling the spatial-temporal evolution of natural hazard-induced domino chain in chemical industrial parks

An event-driven probabilistic methodology for modeling the spatial-temporal evolution of natural hazard-induced domino chain in chemical industrial parks

Men, Jinkun (South China University of Technology; Guangdong Provincial Science and Technology Collaborative Innovation Center for Work Safety)
Chen, Guohua (South China University of Technology; Guangdong Provincial Science and Technology Collaborative Innovation Center for Work Safety)
Yang, Yunfeng (South China University of Technology; Guangdong Provincial Science and Technology Collaborative Innovation Center for Work Safety)
Reniers, G.L.L.M.E. (TU Delft Safety and Security Science; Katholieke Universiteit Leuven; Universiteit Antwerpen)

2022

Natural hazards may rapidly lead to a massive domino chain in chemical industrial parks (CIPs). This work develops a high-efficiency and systematic analytical framework that is applicable to a broad range of uncertain and time-varying factors related to the evolution process of natural hazard-induced domino chain (NHDC). Specifically, the evolution mechanism of NHDC is revealed from a macro-systemic perspective. An event-driven disaster chain evolution system is developed, of which the system state transition is formulated by a Markov decision process and a temporal-difference learning algorithm. A system dynamic risk model is proposed to analyze the dynamic risk associated with NHDC. An earthquake-induced Na-tech scenario is adopted to demonstrate the methodology. Computational results indicate that the proposed methodology is competitive in simulating large-scale system state transition spaces. The involvement of natural hazards would lead to a more complex and severe evolution pattern. Five distinctive stages of the whole NHDC were identified. We found that the value of system dynamic risk is likely to surge in the deterioration stage. Our methodology can dynamically identify the critical system temporal intervals and units at each evolution stage, which has the potential to support the prevention and mitigation of such catastrophic chain events.

Chemical industrial park
Disaster chain evolution system
Dynamic risk analysis
Event-driven probabilistic methodology
Natural hazard-induced domino chain

http://resolver.tudelft.nl/uuid:93e995b5-c5bf-4efb-96e3-2170c456b943

https://doi.org/10.1016/j.ress.2022.108723

2023-07-01

0951-8320

Reliability Engineering & System Safety, 226

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.

Institutional Repository

journal article

© 2022 Jinkun Men, Guohua Chen, Yunfeng Yang, G.L.L.M.E. Reniers