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Probabilistic analysis of a pedestrian bridge using a generalised polynomial chaos expansion surrogate model
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DOI：10.1080/15732479.2026.2691746.png)
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Abstract
En 中文
A probabilistic structural analysis framework employing a generalised polynomial chaos expansion (gPCE) surrogate model is presented. The framework reduces computational cost and enables efficient global sensitivity analysis, Bayesian finite element (FE) model updating and uncertainty quantification (UQ). The case study under consideration is a pedestrian and cycling bridge with twin steel arches and a suspended steel-concrete deck. The ambient vibration measurements provided fifteen vibration modes whose natural frequencies were used for Bayesian FE model updating. This allowed the identification of parameters predominantly influencing higher frequencies. The model updating resulted in a reduction of uncertainties related to material parameters, deck mass and support stiffnesses. The study demonstrates the effectiveness of the gPCE surrogate model for probabilistic analysis of a real-world bridge.
Keywords:
Global sensitivity analysis
Bayesian model updating
uncertainty quantification
steel arch bridge
operational modal analysis
finite element model
gPCE surrogate model
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2.6
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