Dynamic analysis for fire-induced domino effects in chemical process industries

Abstract

Domino effects are typically high-impact low-probability (HILP) accidents, which pose a serious threat to chemical process industries. Previous researches on domino effects in chemical industries focus more on static analysis at the spatial scale. From the perspective of the spatial and temporal characteristics of the accident, this study proposed a model to analyze dynamic evolution process of domino effects by using matrix calculation coupled with Monte Carlo simulation, and the dynamic propagation of pool fire accidents is considered as the evolution of domino effects. The algorithm of the model for dynamic domino probabilities considering the synergistic effects of multiple escalation vectors from different units can be used to analyze the complex scenarios of domino effects with high-level and multiple primary accident units. Moreover, the model can be applied in chemical areas with a large number of installations due to the greatly improved calculation efficiency. The proposed model is tested and validated using earlier studied dynamic Bayesian network method, and the application of the model is demonstrated on a complex multi-unit system. The results show that domino effects have strong temporal correlation, and the scenario with multiple primary accident units is much more serious than that with only one primary accident unit, which provide important support for the implementation of emergency response. The study highlights that the proposed model serves as an important tool to evaluate strategies for prevention and control of domino effects.