Abstract
The fourth-moment method can accurately perform a reliability analysis when it is challenging to determine the distribution of the random variable due to limited available samples. This method only utilizes the first four moments of the random variable and constructs the fourth-moment reliability index. However, it cannot be applied in engineering cases where the state function cannot be expressed explicitly, as it becomes difficult to establish a correlation between the first four moments of the random variable and the state function. Simplifying the state function forcefully may result in significant reliability prediction errors. To address this limitation, this study proposes an adaptive Kriging-based fourth-moment method for reliability analysis under complex state equations. The proposed method demonstrates better applicability and efficiency compared to existing methods. Several numerical examples are provided to validate the effectiveness and accuracy of the proposed method.
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