Open Access
 Issue JNWPU Volume 41, Number 1, February 2023 105 - 114 https://doi.org/10.1051/jnwpu/20234110105 02 June 2023

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## 3 算例

### 3.1 算例1:十杆算例

Ni0由公式(25)中F1=F3=0和F2=1条件下得到。

 图1十杆铝桁架

#### 3.1.1 所提方法结果

 图2所提出方法的二维失效概率函数结果(算例1)
 图3每次迭代中失效概率函数的变异系数结果(算例1)

#### 3.1.2 与其他方法的比较

 图4不同方法的失效概率函数结果对比(算例1)

#### 3.1.3 参数敏感性分析

 图5不同样本点设置下所提方法的迭代次数与计算代价(算例1)

### 3.2 算例2:喷气发动机涡轮叶片

 图6涡轮叶片的几何形状和von Mises应力(算例2)

 图7所提出方法的二维失效概率函数结果(算例2)
 图8不同方法的失效概率函数结果对比(算例2)

## 4 结论

1) 所提出的自适应策略能够有效地识别出, 能使下一个失效概率函数估计得到最大改善的位置;

2) 提出的最小化失效概率函数估计的变异系数的最优组合算法能够很好地融合各个局部失效概率估计;

3) 所提方法能够克服原有增强线抽样方法的局部性, 且使得失效概率函数的求解能够保证全局上的效率和精度最优。

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## All Figures

 图1十杆铝桁架 In the text
 图2所提出方法的二维失效概率函数结果(算例1) In the text
 图3每次迭代中失效概率函数的变异系数结果(算例1) In the text
 图4不同方法的失效概率函数结果对比(算例1) In the text
 图5不同样本点设置下所提方法的迭代次数与计算代价(算例1) In the text
 图6涡轮叶片的几何形状和von Mises应力(算例2) In the text
 图7所提出方法的二维失效概率函数结果(算例2) In the text
 图8不同方法的失效概率函数结果对比(算例2) In the text

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