A risk assessment model of a sewer pipeline in an underground utility tunnel based on a Bayesian network
Rui Zhou, Weipeng Fang, Jiansong Wu
Abstract
A utility tunnel typically houses various types of urban lifelines. As one of the assembled pipelines in a utility tunnel, the sewer pipeline is of great importance for city life. For example, leakage of toxic and combustible gases and a subsequent explosion can result in severe accidents. The potential hazards in the sewer pipeline compartment of a utility tunnel are greatly different from those in traditional directly buried sewer pipelines. In this study, a risk assessment method based on a Bayesian network (BN) and Dempster-Shafer (D-S) Evidence theory was developed to evaluate complicated sewer pipeline accidents in a utility tunnel. First, potential hazards and typical accident scenarios were identified based on case studies of sewer pipeline accidents and evaluated by experts. Then, a BN-based risk assessment framework for the sewer pipeline in a utility tunnel was established. Using the proposed model, BN inferences of sewer pipeline accident scenarios were conducted. Furthermore, sensitivity analysis (SA) was conducted to identify the critical threats of the sewer pipeline in a utility tunnel. The proposed risk assessment framework can help to prevent and mitigate sewer pipeline accidents in utility tunnels.