Author(s)

Quan Wang

Corresponding Author

Quan Wang

Abstract

With the continuous expansion of city scale, the complexity of underground pipe network system also increases, and the single system independent operation mode can no longer meet the needs of smart cities. In this paper, a multi-objective collaborative scheduling and risk assessment method of urban underground pipe network integrated with "modeling-evaluation-optimization" is proposed to solve the problems of low resource utilization efficiency and difficulty in coping with extreme weather events and compound disasters in traditional models. Firstly, based on the complex network theory, a multi-pipe network coupling model is constructed to describe the physical and functional relationship between systems. Then the dynamic load-capacity model is used to simulate the fault cascade process, quantify the risk propagation path and evaluate the system resilience. Then, a four-dimensional collaborative optimization model of "efficiency-safety-economy-environment" is established, and the adaptive optimization of scheduling strategy is realized by combining with deep reinforcement learning (DRL). Finally, BIM+GIS and digital twin technology are combined to construct virtual mapping of pipe network, and realize three-dimensional visualization, real-time data mapping and simulation decision verification of pipe network system. Through case analysis, it is verified that this method can effectively curb the expansion of faults, improve the overall toughness of urban lifeline system, and provide scientific basis for decision makers.

Keywords

Urban underground pipe network, multi-objective collaborative scheduling, risk assessment