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A novel and efficient stochastic collocation method for estimating failure probability function in one-dimensional reduced space
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DOI：10.1016/j.compstruc.2024.107365.png)
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Failure probability function (FPF) is an important index when measuring the effect of random input distribution parameters on the safety of structures. It can decouple reliability-based design optimization. However, efficient estimation of the FPF is challenging. This study proposes a novel stochastic collocation method for estimating the FPF. The novelty of the proposed method lies in three aspects: First, an equivalent integral expression is proposed for the FPF in one-dimensional reduced space, enabling FPF estimation using an efficient stochastic collocation method. Secondly, a unified sampling density function is constructed to remove the coupling between the computational cost of FPF estimation and the number of distribution parameter realizations. Thirdly, a stochastic collocation point set is derived and shared to estimate the whole FPF using arbitrary distribution parameter realization. The proposed method is particularly suitable for the strength-stress and resistance-load models used in the field of engineering. The efficiency and accuracy of the proposed method are verified by several examples.
Keyword:
Structural reliability
Failure probability function
Stochastic collocation method
Mixed -degree cubature formula
Strength-stress model
Resistance-load model
期刊
C
IF:
4.8
论文数:
6.2K
被引数:
1.7W
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