Safety Assurance of Existing Pipelines in Tunneling Construction

Abstract

A novel decision support approach based on fuzzy Bayesian networks (FBN) is developed for safety risk analysis in this paper with detailed step-by-step procedures, including risk mechanism analysis, FBN model establishment, fuzzification and defuzzification, and fuzzy Bayesian inference. A conceptual causal framework is proposed to investigate the causal relationships between tunnel-induced pipeline damage and its influential variables on a basis of failure mechanism analysis. The probability inference model is then built by combining the conceptual causal framework with FBN to implement fuzzy Bayesian inference. The approach proposed in this paper 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 the underground buried pipelines adjacent to the construction of 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.