Study on Inelastic Attenuation and Site Response in Jiangxi Area
Abstract Based on 86 ML≥2.5 seismic events waveform recorded in Jiangxi since 2009, we use genetic algorithm inversion to obtain the non-elastic damping coefficient in site response of each station, calculating the source parameter on the basis. The results show that the frequency dependent non-elasticity coefficient Q in Jiangxi area is estimated as Q(f)=323.1f0.505 9 and the site response of most stations is flat in frequency domain, consistent with the bedrock property of the stations. We find a linear relationship between ML and these seismic moment M0 in the single-logarithmic coordinates, a negative correlation between seismic moment and corner frequency, a non-significant correlation between seismic stress drop and seismic moment, and a significant double logarithmic relationship between source radius and stress drop.
Key words :
genetic algorithm
site response
quality factor Q coefficient
source parameter
Jiangxi area
Cite this article:
XIAO Mengren,CHEN Hao,LUO Li et al. Study on Inelastic Attenuation and Site Response in Jiangxi Area[J]. jgg, 2020, 40(3): 287-290.
XIAO Mengren,CHEN Hao,LUO Li et al. Study on Inelastic Attenuation and Site Response in Jiangxi Area[J]. jgg, 2020, 40(3): 287-290.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2020/V40/I3/287
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[3]
YIN Hongwei, GAO Dengping, LIANG Lihuan, HAN Wenying, LIU Jing, LI Feng. Research on Focal Parameters and Seismogenic Fault of the 2016 Tangshan M4.1 Earthquake Using Local Waveforms [J]. jgg, 2020, 40(7): 688-691.
[4]
ZHANG Zihao, JIANG Liming, CHEN Yuxing. Preliminary Analysis of InSAR Coseismic and Time Series Deformation of Rongxian Earthquake [J]. jgg, 2020, 40(7): 671-676.
[5]
XIE Shaofeng,SU Yongning,LIU Chunli,LIU Lilong. Short-Impending Prediction of GPS Precipitable Water Vapor Based on Wavelet Decomposition and GA-LSSVM [J]. jgg, 2019, 39(5): 487-491.
[6]
CHEN Chenyue,FENG Guangcai,GAO Hua,YANG Huaining. Earthquake Source Parameter of the Ning’er MS 6.4 Earthquake Inferred fromInSAR Data and Analysis of Coulomb Stress Disturbance [J]. jgg, 2019, 39(3): 295-301.
[7]
MENG Qingxiao, LV Jian,JING Pengxu. Simulation of Near Field Strong Ground Motion of Lushan M7.0 Earthquake Based on Two-Dimensional Finite Element Method [J]. jgg, 2019, 39(2): 131-136.
[8]
ZUO Kezhen,CHEN Jifeng, PU Ju, YIN Xinxin. Study of the Spatial and Temporal Distribution Characteristics of StressDrop before the January 21, 2016 MS6.4 Menyuan Earthquake [J]. jgg, 2018, 38(6): 629-633.
[9]
ZHANG Jinling,ZHU Xinyun,MA Qiyang,JIN Chunhua. Study on the Characteristic of Source Parameters of Ningxia Region [J]. jgg, 2017, 37(8): 808-812.
[10]
DU Sunwen,ZHANG Jin,DENG Zengbing,LI Jingtao. GB-SAR Monitoring Effectiveness Analysis Using Genetic Algorithm Optimized BP Neural Network [J]. jgg, 2017, 37(8): 876-880.
[11]
. [J]. jgg, 2016, 36(增1): 117-.
[12]
WANG Zhaoling,YANG Qian,LIU Zhengping,SUN Keqin. Genetic Algorithms Inversion of Wave Equation in Tunnel Seismic Prediction [J]. jgg, 2016, 36(5): 451-.
[13]
ZHANG Xiuxia. Inversion of Fault Deformation Parameters Considering Observation Precision [J]. jgg, 2016, 36(11): 977-980.
[14]
SHEN Zhehui,HUANG Teng,SHEN Yueqian,ZHENG Hao. Dam Deformation Monitoring Prediction on Support Vector Machine Optimized by Genetic Algorithm [J]. jgg, 2016, 36(10): 927-930.
[15]
WU Haibo,SHEN Xuelin,DU Chengchen,CHEN Junhua,WANG Jie. Study of Small Earthquakes Activity Characteristics before
the Zigui 4.5, 4.7 Earthquake in 2014 [J]. jgg, 2015, 35(5): 751-757.