Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel‐Induced Pipeline Damage

TLDR

Tunneling excavation inevitably disturbs surrounding environments, making tunnel‑induced damage to adjacent buried pipelines a critical concern in geotechnical practice. This study develops a fuzzy Bayesian network (FBN) approach for safety risk analysis of tunnel‑induced pipeline damage, outlining detailed step‑by‑step procedures. The approach constructs a tunnel‑induced pipeline damage model that maps cause‑effect relationships, incorporates an expert confidence indicator for fuzzification, and uses fuzzy Bayesian inference to compute risk probability distributions and identify likely accident causes, illustrated by a case study of the Wuhan Yangtze River Tunnel. Results demonstrate the feasibility of the FBN approach and its potential as a decision tool to support safety assurance and management, thereby increasing project success likelihood in complex tunnel construction environments.

Abstract

Tunneling excavation is bound to produce significant disturbances to surrounding environments, and the tunnel‐induced damage to adjacent underground buried pipelines is of considerable importance for geotechnical practice. A fuzzy Bayesian networks (FBNs) based approach for safety risk analysis is developed in this article with detailed step‐by‐step procedures, consisting of risk mechanism analysis, the FBN model establishment, fuzzification, FBN‐based inference, defuzzification, and decision making. In accordance with the failure mechanism analysis, a tunnel‐induced pipeline damage model is proposed to reveal the cause‐effect relationships between the pipeline damage and its influential variables. In terms of the fuzzification process, an expert confidence indicator is proposed to reveal the reliability of the data when determining the fuzzy probability of occurrence of basic events, with both the judgment ability level and the subjectivity reliability level taken into account. By means of the fuzzy Bayesian inference, the approach proposed in this article is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of underground buried pipelines adjacent to the construction of the Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment.