Semi-Empirical Estimation of Strong Ground Motions During Large Earthquakes

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A synthesis method is developed for estimating deterministically strong motions during the mainshock, using the records of small events such as foreshocks and aftershocks which occurred within the area of the mainshock fault. This synthesis formulation is based on the kinematic source model of Haskell type and the similarity law of earthquakes. The parameters for this synthesis are determined to be consistent with the scaling relations between the moments and the fault parameters such as fault length, width and dislocation rise time. If the ratio of the mainshock moment Mo to the small event one Mo_e is assumed to be N^3, then the mainshock fault can be divided into N×N elements, each dimension of which is consistent with that of the small event and N events at each element may be superposed with a specific time delay to correct the difference in the rise time between the mainshock and the small event and to keep a constant slip velocity between them. By means of this method, the mainshock velocity motions are synthesized using the small event records obtained by velocity-type-strong-motion-seismographs for 1980 Izu-Hanto-Toho-Oki Earthquake (M=6.7). The resultant synthesized motions show a good agreement with the observed ones in the frequency range lower than 1 Hz. Further, the synthesis formulation is improved to be applicable to the higher frequency motions, especially acceleration motions. This revised synthesis for the higher frequency motions is effective when we use the records from the small event having the fault length L_e=V_γ・τ(V_γ: rupture velocity and τ: rise time of mainshock). The synthesized accelerograms by this revised method are in good agreement with the observed ones in the frequency range up to 5 Hz.

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詳細情報 詳細情報について

  • CRID
    1050001335685584000
  • NII論文ID
    120002398874
  • NII書誌ID
    AA00581033
  • ISSN
    04547675
  • HANDLE
    2433/124917
  • 本文言語コード
    en
  • 資料種別
    departmental bulletin paper
  • データソース種別
    • IRDB
    • CiNii Articles

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