Accident Evolution and Causal Analysis in Urban Utility Tunnels Using Bayesian Networks and Fault Tree Models

With the advancement of resilient city construction and urban renewal initiatives, the progress of underground utility tunnels has emerged as a significant trend in urban infrastructure. These tunnels play a crucial role in enhancing the comprehensive load-bearing capacity of underground pipelines while optimizing both above-ground and subterranean urban space. Given the concentration of various municipal pipelines such as water, electricity, gas and heat-alongside numerous ancillary facilities, the systems within these utility tunnels are extensive and intricate, with numerous safety-related factors. In the event of a disaster, these factors can easily trigger a complex cascade of events. A bidirectional analysis of the evolution and causes of incidents within these tunnels not only aids in pre-emptively mitigating potential risks but also facilitates effective post-incident tracing and management. Current evaluation models, including classification statistics and qualitative-quantitative analysis, offer some theoretical support but often emphasize unidirectional analysis, which fails to capture the full complexity and variability of such incidents. To address this limitation, this paper proposes an innovative evaluation approach that integrates Bayesian network and fault tree analysis. By applying boolean operations on the fault tree, this method thoroughly investigates the root causes of accidents, while the Bayesian network model quantitatively assesses the likelihood of primary accidents and secondary derivative disasters within underground utility tunnels. This approach enables a comprehensive and bidirectional analysis of tunnel accidents, offering a novel perspective and methodology for risk assessment, thereby supporting the safe and stable operation of these critical urban infrastructures.