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The Generation of the Target Aftershock Spectrum Based on the Conditional Mean Spectrum of Aftershocks

Author(s): ORCID

ORCID

Medium: journal article
Language(s): English
Published in: Buildings, , n. 10, v. 13
Page(s): 2660
DOI: 10.3390/buildings13102660
Abstract:

Numerous studies have examined the responses of various structures to the mainshock–aftershock (MS–AS) ground motion, and the MS–AS ground motions are very important as the input. Therefore, in the absence of aftershock information, it is particularly critical to construct a reasonable MS–AS seismic sequence. This paper aims to provide a new reasonable method for generating the target aftershock response spectrum, which can be used to select or artificially simulate aftershock ground motion, given the seismic information of the main shock. Firstly, the magnitude, fault size, and location of the aftershock are determined. Then, other parameters required for the aftershock ground motion prediction equation (GMPE) are calculated. Subsequently, the correlation of the spectral shape to the MS–AS ground motion is used to modify the response spectrum predicted using the GMPE to obtain the conditional mean spectrum of aftershocks (CMSA). Finally, the relative errors of the predicted spectrum via the ASK14 model and CMSA are compared for four different assumptions. The results show that the simulated aftershock parameters and the actual ones accord well, and the relative errors of the CMSA can be controlled within 20%. Meanwhile, the discrete property of the target aftershock response spectrum is closer to the real recorded response spectrum.

Copyright: © 2023 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
    10744363
  • Published on:
    28/10/2023
  • Last updated on:
    07/02/2024
 
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