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Artificial neural network based method for seismic fragility analysis of steel frames

  • Structural Engineering
  • Published:
KSCE Journal of Civil Engineering Aims and scope

Abstract

Steel frames are widely used in earthquake areas but the fragility analysis of the steel frames is a time consuming process. The fragility curves are generally obtained based on a large number of time history analyses. In order to better simulate steel frames, the material and geometric uncertainties are considered. The moderate earthquake records are selected as the earthquake samples. Then the seismic damages induced by these samples are obtained using Finite Element Analysis (FEA) program. An Artificial Neural Network (ANN) is trained by these seismic damage data. Then the trained ANN is used to predict the seismic damage of the steel frame. When the training data is enough, the method has high prediction precision. The fragility curves based on the ANN prediction are the same as that based on the FEA program.

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Authors and Affiliations

  1. School of Civil Engineering, Dalian University of Technology, Dalian, 116024, China

    Zhen Liu & Zhe Zhang

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  1. Zhen Liu
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  2. Zhe Zhang
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Correspondence to Zhen Liu.

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Liu, Z., Zhang, Z. Artificial neural network based method for seismic fragility analysis of steel frames. KSCE J Civ Eng 22, 708–717 (2018). https://doi.org/10.1007/s12205-017-1329-8

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  • DOI: https://doi.org/10.1007/s12205-017-1329-8

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