A data-driven and physics-based approach to exploring interdependency of interconnected infrastructures

Abstract

Interdependency of interconnected infrastructure is a critical and daunting issue. While existing research is still limited to single physical mechanism-based methods or data-driven statistics approaches; there is a predicament that certain target infrastructure may only have limited knowledge on physical operation mechanisms or lack enough associated data. To fill the gap, the study proposes an integrated data-driven (DD) and physics-based (PB) approach to explore the interdependency of interconnected infrastructure. The approach consists of three components: (i) “motivations”—to understand the targeted infrastructure, availability of data, and physical knowledge related to different infrastructure systems; (ii) “methods”—to select suitable DD or PB methods for individual infrastructure; and (iii) “modes”—to design the connection for bridging DD and PB methods. A case study is conducted to explore the interdependency of the water supply pipe system and road transport networks of a district in Hong Kong. The preliminary findings reveal that the framework can help identify the hot spots of water pipe bursts and predict their cascading effects on the road transport networks, despite certain limitations need to be overcome in future research.