关键词: 结构可靠性, 自适应集成策略, Kriging模型, 主动学习函数

Abstract:  The reliability analysis results of complex structures based on the Kriging model were highly dependent on the fitting accuracy of the Kriging model. In the constructing processes of the Kriging model, the selection of different correlation and regression functions affected the accuracy of the model. In order to solve the impacts of model uncertainty on the reliability analysis results, while considering computational efficiency and accuracy, based on the Kriging model and Monte Carlo simulation(MCS) method, a structural reliability calculation method combining adaptive ensemble strategy and active learning function was proposed. Considering the modeling uncertainty of Kriging models, combined with multiple Kriging models, this methed constructed an active learning function that comprehensively considered sample point contribution and sample point distance. The ensemble Kriging model was iteratively updated through the active learning function until the convergence conditions were satisfied. Finally the structural reliability analysis was carried out by the constructed ensemble Kriging model and MCS method. The validity of the proposed method was verified by numerical and engineering examples, and the results show that the proposed method is more robust than other major methods, and the computational efficiency is higher while ensuring the computational accuracy.

Key words:  , structural reliability, adaptive ensemble strategy, Kriging model, active learning function