Resilience recovery strategy of airport infrastructure network under rainstorm disasters

To improve the resilience of the airport infrastructure network under rainstorm disaster, the airport infrastructure network topology model is established by considering the functional characteristics of airport infrastructure, and the complex network characteristics of airport infrastructure are analyzed. The service efficiency function of the airport network model is constructed by introducing the number of flights, passenger capacity and route distance between the airport nodes. The relevance index of the airport nodes is determined by comparing the network model service effectiveness before and after the airport node failure in order to identify the important airport nodes in the network. The resilience triangle theory serves as the foundation for the resilience recovery model of the airport infrastructure network, which is designed to investigate the best practices and recovery order for airport nodes in the event of failure for major airport nodes, major regional airport nodes, and multi-regional airport nodes during rainstorm disasters. The results show that the established model is presented as a small-world network, which is characterized by high agglomeration. The five key airport nodes that have a greater impact on the network service efficiency are Guangzhou Baiyun Airport, Beijing Capital Airport, Shenzhen Baoan Airport, Hangzhou Xiaoshan Airport and Shanghai Hongqiao Airport. Compared with the recovery strategy based on importance degree and node degree, the recovery strategy based on network resilience has the best recovery effect, such as the network resilience value based on node degree and importance degree under the key airport nodes failure is 0.889, 0.907, while the resilience value based on the network resilience recovery strategy is 0.915. Compared with the airport nodes in North China and Southwest China, the failure of the airport nodes in East China has a greater impact on the operation efficiency of airport infrastructure network.