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This analysis identifies key variables affecting displacement in a cantilever beam, suggesting polynomial chaos expansion enhances efficiency over Monte Carlo methods.
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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Cheng et al. (2025) studied this question.
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