01762nas a2200193   4500000000100000000000100001008004100002100001500043700001500058700001600073700002600089700001600115700001700131245009600148300001400244490000800258520128800266022001401554       2015                            d1 aWu Xianguo1 aLiu Huitao1 aZhang Limao1 aMirosław Skibniewski1 aDeng Qianli1 aTeng Jiaying00aA dynamic Bayesian network based approach to safety decision support in tunnel construction  a157–1680 v1343 aThis paper presents a systemic decision approach with step-by-step procedures based on dynamic Bayesian network (DBN), aiming to provide guidelines for dynamic safety analysis of the tunnel-induced road surface damage over time. The proposed DBN-based approach can accurately illustrate the dynamic and updated feature of geological, design and mechanical variables as the construction progress evolves,in order to overcome deficenciesof traditional fault analysis method. Adopting the predictive, sensitivity and diagnostic analysis techniques in the DBN inference, this this approach is able to perform feed-forward, concurrent and back-forward control respectively on a quantitative basis, and provide real-time support before and after an accident. A case study in relating to dynamic safety analysis in the construction of Wuhan Yangtze Metro Tunel in China is used to verify the feasibility of the proposed approach, as well as its application potential. The relationships between the DBN-based and BN-based approaches are further discussed according to analysis results. The proposed aproach can be used as a decision tool to provide support for safety analysis in tunnel construction, and thus increase the likelihood of a successful project in a dynamic project environment.  a0951-8320