Wang Xiuzhen, Xu Zhaoxia, Sun Chuanzhi
School of Civil Engineering and Architecture, Suqian University, Suqian, China.
Jiangsu Prefabricated Building and Intelligent Construction Engineering Research Center, Suqian University, Suqian, China.
Sci Rep. 2025 Mar 11;15(1):8447. doi: 10.1038/s41598-025-93150-x.
To improve the computational efficiency of global sensitivity analysis (GSA) for complex structures, this study proposed a new importance analysis method (IE) based on the low deviation sequences and orthogonal polynomials to study the influence of parameters' uncertainty on three structural seismic demands. A comparative investigation utilizing nonlinear time history analysis for these seismic demands was conducted using OpenSEES. The variance-based importance analysis method and the Tornado graphic sensitivity analysis method were employed to validate the accuracy of the proposed approach. The results regarding the order of importance are nearly consistent across methods, demonstrating the effectiveness of our proposed method. Notably, the sample size required by this new method is only 1024 to achieve reliable results, which is significantly lower than existing sampling methods that necessitate thousands of samples for effective importance analysis; thus, enhancing overall efficiency. Furthermore, the findings indicate that the influence of representative value of gravity load (M) on seismic demands is relatively substantial, whereas the influence of modulus of elasticity of concrete (E) is comparatively minor.
为提高复杂结构全局灵敏度分析（GSA）的计算效率，本研究提出了一种基于低偏差序列和正交多项式的新重要性分析方法（IE），以研究参数不确定性对三种结构地震需求的影响。利用OpenSEES对这些地震需求进行了基于非线性时程分析的对比研究。采用基于方差的重要性分析方法和龙卷风图灵敏度分析方法来验证所提方法的准确性。各方法关于重要性排序的结果几乎一致，证明了所提方法的有效性。值得注意的是，这种新方法只需1024个样本就能获得可靠结果，这比现有需要数千个样本才能进行有效重要性分析的抽样方法要低得多，从而提高了整体效率。此外，研究结果表明，重力荷载代表值（M）对地震需求的影响相对较大，而混凝土弹性模量（E）的影响相对较小。
