Securing heat-supply against seismic risks: A two-staged framework for assessing vulnerability and economic impacts in district heating networks

Urban infrastructure, particularly district heating networks (DHNs), faces a significant threat from natural disasters such as earthquakes, which can result in extensive damage and disruptions. This study focuses on DHNs' vulnerability assessment to seismic hazards, considering both their physical integrity and operational resilience. Our proposed two-staged vulnerability analysis framework provides a comprehensive evaluation of the seismic impact on DHNs, identifying critical factors that contribute to the seismic resilience of these networks. The first phase of the framework generates customized failure scenarios for seismic zones using two methods: the Two-Tier Random Sampling Method (TTRS) and the Integrated Failure Probability Method (IPRS). IPRS directly calculates the integrated failure probability for heating pipes in known seismic zones, thereby reducing the need for extensive random sampling required by TTRS. The second stage of the analysis assesses DHNs' vulnerability using an advanced stochastic repair time model. This model incorporates factors such as repair-crew productivity, lifeline interactions, and resource constraints, enabling an assessment of economic losses resulting from earthquake-induced heating failures. It also examines topological and functional losses, providing a holistic understanding of DHNs' vulnerability. Validation of the proposed framework using a real-case DHN in China, located near a seismic zone, underscores its efficacy. Seismic magnitude is a key factor affecting DHNs' vulnerability, especially when it's <6.0, while the seismic epicenter's impact is relatively modest. In addition to understanding DHNs' vulnerability, our findings offer insights into enhancing seismic resilience. Protecting mainlines between heat sources can reduce topological vulnerability by up to 98.21%, functional vulnerability by up to 70.63%, and economic loss by up to 82.74%.