Determining the key urban infrastructures in disaster scenarios based on complex network theory

The rising frequency of disasters is causing infrastructure failures, compromising urban safety and disrupting residents’ daily lives. During natural disasters, damage to key infrastructure can worsen the overall disruption of the network. To determine key infrastructures after natural disasters, a topological model of the key infrastructure network of Ya’an City was built using complex network theory. The network’s structural characteristics were analyzed, and through calculations, high-ranking nodes and edges were identified as important nodes and important connections. K-means clustering was also applied to categorize the nodes within the network. Furthermore, considering the characteristics of earthquake disasters, three failure modes under various scenarios were introduced: single node failure, same-region node failure, and consecutive failure of regional important nodes. The network’s performance under these failure scenarios was analyzed to evaluate its variations. The results show that the key infrastructure network of Ya’an City is a complex network. The power network’s clustering coefficient is notably higher than the overall average, marking it as a key sub-network. Fifteen important nodes were identified, each distinguished by elevated values across four centrality metrics, highlighting their crucial roles. Moreover, five core nodes stood out not only for excelling in individual centrality assessments but also for triggering substantial declines in three indicators upon failure. Nineteen important connecting edges were pinpointed, underscoring their paramount significance. The network is divided into five clusters, demonstrating differences in overall influence, network position, and information transmission capacity. This reasearch identified key urban infrastructures that influence the operation of the key infrastructure network of Ya’an City and proposed strategic recommendations based on the characteristics of various node clusters. These can serve as a reference for daily maintenance and disaster prevention and mitigation of urban infrastructure systems.