Risk Coupling Analysis of Metro Deep Foundation Pit Construction Based on Complex Networks

Abstract

The exacerbation of safety risk levels in metro deep foundation pit construction is attributed to the interactive coupling of numerous risk factors. To comprehensively explore the underlying mechanisms of safety incidents, complex network theory is applied to analyze interactions among risk factors systemically. Initially, through the identification of safety risk factors, a risk factor system comprising six primary risk factors and 35 secondary risk factors is established. Subsequently, by utilizing coupling mechanism analysis and complex network theory, a coupling network model of safety risks in metro deep foundation pit construction with 42 nodes and 184 directed edges is constructed, with network topology indicators analysis revealing the evolutionary law of risk coupling. Finally, Python software is employed to simulate the network with single-node, random, and targeted immunization. Key risk factor nodes are identified using network efficiency measurement methods. The results indicate that all risk factors positively influence the connectivity of the coupling network, and the risk-coupling network presents small-world and scale-free characteristics. In comparison with different immunization strategies, targeted immunization is found to be more effective than random immunization, and prioritizing the control of risk factors with a high degree of centrality, such as “violation of operating regulations” and “inadequate safety supervision and hidden danger inspection”, proves more effective in alleviating risk coupling, underscoring the importance of prioritizing control of key risk nodes in the network. These findings provide a scientific basis for risk management and optimization in metro deep foundation pit construction.