Risk causation analysis and prevention strategy of working fluid systems based on accident data and complex network theory

Working fluid systems (WFS) in industrial processes are often accompanied by hazardous gases, which lead to various hazardous accidents. This paper, based on accident data and complex network theory, develops a framework for risk causation analysis and prevention strategies for WFS. The accident components at WFS are identified with emphasis. In the case study, a set of risk event nodes, including system, equipment, personnel, environment, and accident types, are selected based on the characteristics of systems. A complex network model according to accident chains is constructed to represent the complex interactions and relationships between various factors. This model evaluates the structural characteristics of the network and elucidates the relationship between accident causes and system risks. The comprehensive importance of different nodes is analyzed in order to rank the risk factors and determine three types of critical causative paths for the risks of the accident chain. This method has been verified to help identify critical factors in accidents when combined with robustness analysis. The risk prevention strategies are proposed to reduce the risk of accident evolution. The method can help identify the accident risk characteristics of WFS, providing valuable information for safe application and accident prevention.