Phase similarity model between element waves of adjacent element faults for simulated ground motion based on the stochastic green's function method

Haruka Yokoyama, Hajime Iwai, Masayuki Kohiyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a quantitative phase model to predict element waves of adjacent element faults to simulate ground motion using the stochastic Green's function method. We paired seismic records under the specified conditions of near-identical magnitude and hypocenter depth. To model the acceleration waveform similarities of the seismic record pair, a relationship between the mean value of Fourier amplitudes and an absolute value of Fourier phase difference was represented using a beta distribution. We then derived a regression formula of beta-distribution shape parameters with respect to the distance between the two hypocenters of each pair. Based on the proposed model, a seismic wave was synthesized, along with a calculated RMS error in acceleration response spectra between the synthesized wave and the observed record of the 2016 Kumamoto earthquake. It was confirmed that the proposed model decreased the error successfully.

Original languageEnglish
Title of host publicationProceedings of the 29th European Safety and Reliability Conference, ESREL 2019
EditorsMichael Beer, Enrico Zio
PublisherResearch Publishing Services
Pages3217-3223
Number of pages7
ISBN (Electronic)9789811127243
DOIs
Publication statusPublished - 2020
Event29th European Safety and Reliability Conference, ESREL 2019 - Hannover, Germany
Duration: 2019 Sep 222019 Sep 26

Publication series

NameProceedings of the 29th European Safety and Reliability Conference, ESREL 2019

Conference

Conference29th European Safety and Reliability Conference, ESREL 2019
CountryGermany
CityHannover
Period19/9/2219/9/26

Keywords

  • Element fault
  • Element wave
  • Fourier spectrum
  • Phase
  • Simulated ground motion
  • Stochastic Green's function method

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Safety Research

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