An efficient computational framework for structural system reliability analysis and Updating based on Chain-Structure Bayesian networks(BNs)is present in the paper.The framework combines BNs and structural reliability...An efficient computational framework for structural system reliability analysis and Updating based on Chain-Structure Bayesian networks(BNs)is present in the paper.The framework combines BNs and structural reliability methods(SRMs)for reliability assessment and updating.BNs have advantages in evaluating complex probabilistic dependence structures and reliability updating,while SRMs are employed to assess the conditional probability table.The improved branch-and-bound(B&B)method is integrated with BNs to simplify the whole network.In order to further reduce computational demand,failure(or survival)path events are introduced to create chain-structure BNs.Considering the correlations between failure modes,the system reliability is obtained through the Probability Network Estimation Technology(PNET).Finally,the reliability updating is carried out through BNs inference.Results show that computational efficiency is improved by the Chain-Structure BNs.System reliability problems with both continuous and discrete random variables can be better resolved by combining BNs and SRMs.This approach is also able to update system reliability when new information available.展开更多
文摘An efficient computational framework for structural system reliability analysis and Updating based on Chain-Structure Bayesian networks(BNs)is present in the paper.The framework combines BNs and structural reliability methods(SRMs)for reliability assessment and updating.BNs have advantages in evaluating complex probabilistic dependence structures and reliability updating,while SRMs are employed to assess the conditional probability table.The improved branch-and-bound(B&B)method is integrated with BNs to simplify the whole network.In order to further reduce computational demand,failure(or survival)path events are introduced to create chain-structure BNs.Considering the correlations between failure modes,the system reliability is obtained through the Probability Network Estimation Technology(PNET).Finally,the reliability updating is carried out through BNs inference.Results show that computational efficiency is improved by the Chain-Structure BNs.System reliability problems with both continuous and discrete random variables can be better resolved by combining BNs and SRMs.This approach is also able to update system reliability when new information available.
