期刊
COMPUTERS & STRUCTURES
卷 239, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compstruc.2020.106320
关键词
Stochastic loading; First excursion probability; Linear structure; Imprecise probabilities; Interval analysis
资金
- Research Foundation Flanders [12P3519N]
- ANID (National Agency for Research and Development, Chile) under its program FONDECYT [1180271]
- Universidad Tecnica Federico Santa Maria under its program PAC (Programa Asistente Cientifico 2017)
- Alexander von Humboldt Foundation through its program Humboldt Research Fellowship for Experienced Researchers
This paper presents a highly efficient and accurate approach to determine the bounds on the first excursion probability of a linear structure that is subjected to an imprecise stochastic load. Traditionally, determining these bounds involves solving a double loop problem, where the aleatory uncertainty has to be fully propagated for each realization of the epistemic uncertainty or vice versa. When considering realistic structures such as buildings, whose numerical models often contain thousands of degrees of freedom, such approach becomes quickly computationally intractable. In this paper, we introduce an approach to decouple this propagation by applying operator norm theory. In practice, the method determines those epistemic parameter values that yield the bounds on the probability of failure, given the epistemic uncertainty. The probability of failure, conditional on those epistemic parameters, is then computed using the recently introduced framework of Directional Importance Sampling. Two case studies involving a modulated Clough-Penzien spectrum are included to illustrate the efficiency and exactness of the proposed approach. (C) 2020 Elsevier Ltd. All rights reserved.
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