Efficient procedure for failure probability function estimation in augmented space
Yuan
X
K
author
Liu
S
L
author
Valdebenito
M
A
author
Gu
J
author
Beer
M
author
2021
An efficient procedure is proposed to estimate the failure probability function (FPF) with respect to design variables, which correspond to distribution parameters of basic structural random variables. The proposed procedure is based on the concept of an augmented reliability problem, which assumes the design variables as uncertain by assigning a prior distribution, transforming the FPF into an expression that includes the posterior distribution of those design variables. The novel contribution of this work consists of expressing this target posterior distribution as an integral, allowing it to be estimated by means of sampling, and no distribution fitting is needed, leading to an efficient estimation of FPF. The proposed procedure is implemented within three different simulation strategies: Monte Carlo simulation, importance sampling and subset simulation; for each of these cases, expressions for the coefficient of variation of the FPF estimate are derived. Numerical examples illustrate performance of the proposed approaches.
RELIABILITY-BASED OPTIMIZATION
NONINTRUSIVE STOCHASTIC-ANALYSIS
STRUCTURAL RELIABILITY
SENSITIVITY ESTIMATION
HIGH DIMENSIONS
DESIGN
SYSTEMS
WOS:000659220400003
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text
10.1016/j.strusafe.2021.102104
Yuan_etal2021
Structural Safety
Struct. Saf.
2021
continuing
periodical
academic journal
92
102104
0167-4730