Open Access
ARTICLE
A Statistical Model for Phase Difference Spectrum of Ground-Motion and Its Application in Generating Non-Stationary Seismic Waves
Dongsheng Du1,*, Sheng Shi1, Weizhi Xu1, Chen Kong2, Shuguang Wang1, Weiwei Li1
1 College of Civil Engineering, Nanjing University of Technology, Nanjing, 210009, China
2 China Jiangsu International Group Architecture Design Institute, Nanjing, 211816, China
* Corresponding Author: Dongsheng Du. Email:
(This article belongs to this Special Issue: Numerical Modeling and Simulation for Structural Safety and Disaster Mitigation)
Computer Modeling in Engineering & Sciences 2020, 124(1), 265-285. https://doi.org/10.32604/cmes.2020.09151
Received 16 November 2019; Accepted 06 February 2020; Issue published 19 June 2020
Abstract
The intensity non-stationarity is one of the most important features of
earthquake records. Modeling of this feature is significant to the generation of arti-
ficial earthquake waves. Based on the theory of phase difference spectrum, an
intensity non-stationary envelope function with log-normal form is proposed.
Through a tremendous amount of earthquake records downloaded on Kik-net, a
parameter fitting procedure using the genetic algorithm is conducted to obtain
the value of model parameters under different magnitudes, epicenter distances
and site conditions. A numerical example is presented to describe the procedure
of generating fully non-stationary ground motions via spectral representation, and
the mean EPSD (evolutionary power spectral density) of simulated waves is
proved to agree well with the target EPSD. The results show that the proposed
model is capable of describing the intensity non-stationary features of ground
motions, and it can be used in structural anti-seismic analysis and ground motion
simulation.
Keywords
Cite This Article
Du, D., Shi, S., Xu, W., Kong, C., Wang, S. et al. (2020). A Statistical Model for Phase Difference Spectrum of Ground-Motion and Its Application in Generating Non-Stationary Seismic Waves.
CMES-Computer Modeling in Engineering & Sciences, 124(1), 265–285. https://doi.org/10.32604/cmes.2020.09151