Bayesian networks for system reliability reassessment

This paper proposes a methodology to apply Bayesian networks to structural system reliability reassessment, with the incorporation of two important features of large structures: (1) multiple failure sequences, and (2) correlations between component-level limit states. The proposed method is validated by analytical comparison with the traditional reliability analysis methods for series and parallel systems. The Bayesian network approach is combined with the branch-and-bound method to improve its efficiency and to facilitate its application to large structures. A framed structure with multiple potential locations of plastic hinges and multiple failure sequences is analyzed to illustrate the proposed method.