Global Sensitivity Analysis of Structural Random Response Based on Polynomial Chaotic Expansion

With the growing significance of stochastic uncertainties in structural design, the quantification of uncertainty and sensitivity analysis of static displacement responses have gained considerable attention. This study employs polynomial chaos expansion (PC) to perform a global sensitivity analysis of the tip deflection of a cantilever beam, aiming to identify the random variable that contributes most significantly to the output variance. Compared with the Monte Carlo simulation approach, the PC method demonstrates superior computational accuracy and efficiency. The results indicate that PC not only accurately captures the sensitivity ranking of the variables but also substantially reduces computational cost, thus offering an effective tool for stochastic analysis and optimization in structural engineering.

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Publication Details

Journal
Academic Journal of Science and Technology
Published
2025-09-27
DOI
https://doi.org/10.54097/1shtxn12
Citations
1
Primary Topic
Structural Response to Dynamic Loads
Type
article
Field-Weighted Citation Impact
0.95
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article

Global Sensitivity Analysis of Structural Random Response Based on Polynomial Chaotic Expansion

Qi Cheng, Cheng Zhen
1 citations
Academic Journal of Science and Technology
Structural Response to Dynamic Loads
0.95
article

Global Sensitivity Analysis of Structural Random Response Based on Polynomial Chaotic Expansion

Qi Cheng, Cheng Zhen
article en
1 citations

Abstract

With the growing significance of stochastic uncertainties in structural design, the quantification of uncertainty and sensitivity analysis of static displacement responses have gained considerable attention. This study employs polynomial chaos expansion (PC) to perform a global sensitivity analysis of the tip deflection of a cantilever beam, aiming to identify the random variable that contributes most significantly to the output variance. Compared with the Monte Carlo simulation approach, the PC method demonstrates superior computational accuracy and efficiency. The results indicate that PC not only accurately captures the sensitivity ranking of the variables but also substantially reduces computational cost, thus offering an effective tool for stochastic analysis and optimization in structural engineering.

Academic Journal of Science and TechnologyVol. 16(3)
Openalex Percentile: Top 21%
Structural Response to Dynamic Loads
0.95
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