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Kriging Metamodel-Based Seismic Fragility Analysis of Single-Bent Reinforced Concrete Highway Bridges

Author(s): ORCID
ORCID


Medium: journal article
Language(s): English
Published in: Buildings, , n. 6, v. 11
Page(s): 238
DOI: 10.3390/buildings11060238
Abstract:

Uncertainty quantification is an important issue in the seismic fragility analysis of bridge type structures. However, the influence of different sources of uncertainty on the seismic fragility of the system is commonly overlooked due to the costly re-evaluation of numerical model simulations. This paper aims to present a framework for the seismic fragility analysis of reinforced concrete highway bridges, where a data-driven metamodel is developed to approximate the structural response to structural and ground motion uncertainties. The proposed framework to generate fragility curves shows its efficiency while using a few finite element simulations and accounting for various modeling uncertainties influencing the bridge seismic fragility. In this respect, a class of single-bent bridges available in the literature is taken as a case study, whose three-dimensional finite element model is established by the OpenSees software framework. Twenty near-source records from different sources are selected and the Latin hypercube method is applied for generating the random samples of modeling and ground motion parameters. The Kriging metamodel is then driven on the structural response obtained from nonlinear time history analyses. Component fragility curves of the reinforced concrete pier column are derived for different damage states using the Kriging metamodel whose parameters are established considering different modeling parameters generated by Monte Carlo simulations. The results demonstrate the efficiency of the proposed framework in interpolating the structural response and deriving the fragility curve of the case study with any input conditions of the random variables.

Copyright: © 2021 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10610086
  • Published on:
    08/06/2021
  • Last updated on:
    10/06/2021
 
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