For engineering products with uncertain input variables and distribution parameters, a sampling-based sensitivity analysis methodology was investigated to efficiently determine the influences of these uncertainties. In the calculation of the sensitivity indices, the nonlinear degrees of the performance function in the subintervals were greatly reduced by using the integral whole domain segmentation method, while the mean and variance of the performance function were calculated using the unscented transformation method. Compared with the traditional Monte Carlo simulation method, the loop number and sampling number in every loop were decreased by using the multiplication approximation and Gaussian integration methods. The proposed algorithm also reduced the calculation complexity by reusing the sample points in the calculation of two sensitivity indices to measure the influence of input variables and their distribution parameters. The accuracy and efficiency of the proposed algorithm were verified with three numerical examples and one engineering example.

中文翻译：

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考虑输入变量及其分布参数不确定性的基于采样的灵敏度分析方法

对于具有不确定输入变量和分布参数的工程产品，研究了一种基于采样的敏感性分析方法，以有效地确定这些不确定性的影响。在灵敏度指标的计算中，使用整数整体域分割方法可大大降低子区间中性能函数的非线性程度，而使用无味变换方法可计算性能函数的均值和方差。与传统的蒙特卡洛模拟方法相比，采用乘法逼近和高斯积分方法减少了每个循环中的循环数和采样数。该算法还通过在两个敏感度指标的计算中重用采样点来测量输入变量及其分布参数的影响，从而降低了计算复杂度。通过三个数值实例和一个工程实例验证了所提算法的准确性和有效性。