Complex network analysis for accident causes modelling to enhance process safety in chemical enterprises

Abstract Hazardous chemicals often cause catastrophic accidents, and accidents often result from intricate interactions among various causes. Due to the varying risk factors in different areas of chemical enterprises, to achieve more precise prevention, a more detailed study of the accident risk factors in each area is necessary. Therefore, this study focuses on analyzing critical accident causes and their interrelationships in different functional areas of chemical enterprises to enhance process safety by using a complex network model. Based on 90 accident information, complex network models are constructed for hazardous chemical warehouse areas (HCWAs), tank farm areas (TFAs), and production areas (PAs). Subsequently, a topological analysis of the complex network models is conducted. Based on the PageRank algorithm, 13 critical nodes are identified for HCWAs, while 14 for TFAs and 13 for PAs. Node degree analysis with confidence quantifies mutual influences, forming critical accident causal links for each area. The research results offer decision support for precise accident risk control, aiding in reducing future accidents and improving process system safety in chemical enterprises.