title: Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel-Induced Pipeline Damage.
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.
authors.affiliation: School of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan Hubei, China.
authors.forename: Limao
authors.initials: L
authors.lastname: Zhang
authors.affiliation: School of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan Hubei, China.
authors.forename: Xianguo
authors.initials: X
authors.lastname: Wu
authors.affiliation: School of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan Hubei, China.
authors.forename: Yawei
authors.initials: Y
authors.lastname: Qin
authors.affiliation: Department of Civil & Environmental Engineering, University of Maryland, College Park, MD, USA.|Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Poland.
authors.forename: Miroslaw J
authors.initials: MJ
authors.lastname: Skibniewski
authors.affiliation: School of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan Hubei, China.
authors.forename: Wenli
authors.initials: W
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002681:China; D003657:Decision Making; D004738:Engineering / Q000379:methods*; D004777:Environment; D005160:Facility Design and Construction; D017143:Fuzzy Logic; D015233:Models, Statistical; D011336:Probability; D018570:Risk Assessment / Q000379:methods*; D045483:Rivers; D012449:Safety
keywords: Fuzzy Bayesian networks; safety risk analysis; tunnel construction