Multivariate seismic vulnerability analysis of bridges based on Gaussian process regression

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Journal of Vibration and Shock ›› 2022, Vol. 41 ›› Issue (23) : 27-35.

YAN Yexiang1, SUN Limin1,2,3

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Abstract

This paper establishes a multivariate seismic fragility analysis method based on Gaussian process regression, which presents fragility as a multivariate function of vector-valued input composed of ground motion intensity indicators and structural parameters. Based on this, the mean fragility curve and envelope fragility curve are developed, quantitatively analyzing the impact of all uncertain parameters on fragility. A three-span reinforced concrete continuous box girder bridge is used as an example to analyze and verify. The results show that the proposed method is comparatively satisfactory in accuracy compared with the Monte Carlo simulation (by hundreds of thousands of dynamic analyses) with hundreds of dynamic analyses. The impact of different seismic intensity indicators on fragility is identified, and the fact is found that any single parameter will cause inaccurate and discrete presentation of fragility. For the case in this paper, the average spectral acceleration is an optimal index to generate the mean and envelope fragility curve with the minimum dispersion.
Key words: multivariate seismic fragility analysis; mean fragility curve; envelope fragility curve; Gaussian process regression; reinforced concrete continuous girder bridge.

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multivariate seismic fragility analysis / mean fragility curve / envelope fragility curve / Gaussian process regression / reinforced concrete continuous girder bridge.

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YAN Yexiang1, SUN Limin1,2,3. Multivariate seismic vulnerability analysis of bridges based on Gaussian process regression[J]. Journal of Vibration and Shock, 2022, 41(23): 27-35

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