Probabilistic structural model updating using approximate Bayesian computing

摘要：

　　A new probabilistic model updating approach based on approximate Bayesian computation with subset simulation(ABC-SubSim)is proposed for parameter identification of structural models using modal data.The ABC-SubSim is a likelihood-free Bayesian approach,in which the explicit formulation of the likelihood function is avoided,and the posterior samples of the model parameters are obtained using the technique of subset simulation.The novel contributions of this paper lie in three aspects: one is the introduction of new stopping criteria to find an appropriate tolerance level for the metric used in the ABCSubSim,the second one is the employment of a hybrid optimization scheme to find a more fine optimal value of the model parameters vector,the last one is the adoption of an iteration approach to determine the optimal weighting factors relating to the residuals of modal frequencies and mode shapes in the metric.The effectiveness of this approach is demonstrated using a numerical example.

关键词： model updating modal parameter approximate Bayesian computation subset simulation

作者: Z.Feng B.Zhao G.Liu Z.Chen

作者单位: College of Civil Engineering,Hunan University,Changsha,China

会议类型: 国际会议

会议名称: The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)

会议地点: 青岛

会议语种:英文

页码: 1823-1824

在线出版日期: 2018-07-22（万方平台首次上网日期，不代表论文的发表时间）