This research investigates the problem of performing sensitivity analysis in bridge engineering through the Kriging method, highlighting the role of uncertainty in structural parameters on bridge performance. Understanding the variability of structural responses is critically dependent on sensitivity analysis related to material properties, loading conditions, and environmental factors [1]. The Kriging method, a statistical metamodeling technique, enables efficient prediction of the structural behavior, permitting the analysis of complex bridge systems through a reduced number of simulations [2]. The study uses a combination of finite element simulations and uncertainty quantification techniques to generate models that represent the bridge’s response. Findings show that Kriging is very effective in modeling the uncertainty in the performance of structures with little computational load and yields precise predictions of bridge performance across several condition changes. The study determines that Kriging-based sensitivity analysis can greatly boost the dependability of bridge engineering by facilitating a more organized response to uncertainties.
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