Dynamic Risk Assessment in Construction Projects Using Bayesian Networks

Abstract

This paper presents a systemic Bayesian network (BN) based approach for dynamic risk assessment for adjacent buildings in tunnel construction. This approach consists of four steps in detail, namely, hazard analysis, BN learning and BN-based risk analysis. In the dynamic risk analysis framework, the predictive, sensitivity and diagnostic analysis techniques in the Bayesian inference are used to conduct the feed-forward control in the preconstruction stage, intermediate control in the construction stage and back-forward control in the post-accident stage, respectively. A case relating to dynamic safety risk analysis of some existing buildings adjacent to construction of the Wuhan Yangtze Metro Tunnel in China is presented. Results demonstrate the feasibility of the proposed approach, as well as its application potential. The proposed approach can be used by practitioners in the industry as a decision support tool to provide guidelines on the conservation of adjacent buildings against tunnel-induced damages, and thus increase the likelihood of a successful project in a dynamic project environment.