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An adaptive multiple-kriging-surrogate method for time-dependent reliability analysis. (English) Zbl 1464.62411

Summary: For accurately and efficiently estimating the time-dependent failure probability (TDFP) of the structure, a novel adaptive multiple-kriging-surrogate method is proposed. In the proposed method, the multiple kriging models with different regression trends (i.e., constant, linear and quadratic) are simultaneously constructed with the highest accuracy, on which the TDFP can be obtained. The multiple regression trends are adaptively selected based on the size of sample base, the maximum differences of multiple models and the global accuracy of multiple models. After that, the most suitable multiple regression trends are identified. The proposed method can avoid man-made subjectivity for regression trend in general kriging surrogate method. Furthermore, better accuracy and efficiency will be obtained by the proposed multiple surrogates than just using a fixed regression model for some engineering applications. Five examples involving four applications with explicit performance function and one tone arch bridge under hurricane load example with implicit performance function are introduced to illustrate the effectiveness of the proposed method for estimating TDFP.

MSC:

62N05 Reliability and life testing
62G08 Nonparametric regression and quantile regression
62P30 Applications of statistics in engineering and industry; control charts
60G25 Prediction theory (aspects of stochastic processes)
90B25 Reliability, availability, maintenance, inspection in operations research

Software:

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References:

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