Prevention and Treatment of Natural Disasters

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Optimized Cauchy-Gaussian Blend Model for Stochastic-Parametric Simulation of Seismic Ground Motions

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https://doi.org/10.54963/ptnd.v1i1.62
Sharbati, R., Amindavar, H., Ramazi, H. R., Foti, S., & Farzanegan, B. (2022). Optimized Cauchy-Gaussian Blend Model for Stochastic-Parametric Simulation of Seismic Ground Motions. Prevention and Treatment of Natural Disasters, 1(1), 38–49. https://doi.org/10.54963/ptnd.v1i1.62
Volume 1 Issue 1: June 2022
Copyright (c) 2022 Hamidreza Amindavar, R. Sharbati, H. R. Ramazi, B. Farzanegan
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Authors

  • R. Sharbati Dep. of Civil and Environmental Eng., Amirkabir University of Technology, Tehran, Iran
  • Hamidreza Amindavar
    Dep. of Electrical Eng., Amirkabir University of Technology, Tehran, Iran
  • H. R. Ramazi Dep. of Mining & Metallurgical Eng., Amirkabir University of Technology, Tehran, Iran
  • S. Foti Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino, Torino, Italy
  • B. Farzanegan Dep. of Electrical Eng., Amirkabir University of Technology, Tehran, Iran

This article proposes a stochastic model for generation of synthetic seismic ground motions. In the first step, the wavelet coefficients of a record are extracted by the dual-tree complex discrete wavelet transform (DT-CDWT) and then they are simulated by an optimized Cauchy-Gaussian blend (CGB) model. This model predicts well the energy distribution of seismic ground motions, because in this model, the Gaussian distribution simulates smooth peaks and the Cauchy distribution is used to simulate impulsive peaks. Also, this model simulates several ascending-descending cycles in the time domain, predicts multiple frequency peaks each time, and simulates sequence-type records.

Keywords:

Seismic ground motions Cauchy-Gaussian blend model Complex discrete wavelet transform Genetic algorithm Spectral and temporal nonstationarity

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