拉普拉斯变换
数学
应用数学
高斯分布
极限(数学)
拉普拉斯逆变换
混合模型
数学优化
可靠性(半导体)
算法
数学分析
统计
量子力学
物理
功率(物理)
作者
Jun Xu,Long Li,Zhao‐Hui Lu
出处
期刊:Journal of Engineering Mechanics-asce
[American Society of Civil Engineers]
日期:2022-03-01
卷期号:148 (3)
被引量:5
标识
DOI:10.1061/(asce)em.1943-7889.0002088
摘要
Recovering the probability distribution of the limit state function is an effective method of structural reliability analysis, in which it still is challenging to balance the precision and computational efforts. This paper proposes an adaptive mixture of normal-inverse Gaussian distributions which exhibits high flexibility to deal with this issue. First, the mixture distributions with two components were revisited briefly, and the limitations are pointed out. Then the proposed mixture distribution was established. According to the limit condition, one or two components are employed in the proposed mixture distribution to represent the unknown distribution of the limit state function (LSF), which makes the mixture distribution adaptive. To specify the unknown parameters effectively, the Laplace transform at some discrete values is utilized, in which a set of nonlinear equations can be solved easily. An effective cubature rule is utilized to assess numerically the Laplace transform and the involved moments, which can guarantee the efficiency and precision for structural reliability computation. After the LSF’s distribution is attained, the failure probability can be evaluated readily via an integral over the distribution. Five numerical examples were provided to indicate the result of the proposed method.
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