[1]邵国良,冀昆,温瑞智,等.基于密集观测数据的强震动参数空间相关性分析[J].地震工程与工程振动,2022,42(06):114-121.[doi:10.13197/j.eeed.2022.0612]
 SHAO Guoliang,JI Kun,WEN Ruizhi,et al.Spatial correlation analysis of strong motion parameters based on high-density observation recordings[J].EARTHQUAKE ENGINEERING AND ENGINEERING DYNAMICS,2022,42(06):114-121.[doi:10.13197/j.eeed.2022.0612]
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基于密集观测数据的强震动参数空间相关性分析
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《地震工程与工程振动》[ISSN:/CN:]

卷:
42
期数:
2022年06期
页码:
114-121
栏目:
第十一届全国地震工程学术会议专题
出版日期:
2022-12-31

文章信息/Info

Title:
Spatial correlation analysis of strong motion parameters based on high-density observation recordings
作者:
邵国良12 冀昆3 温瑞智12 任叶飞12 崔建文4
1. 中国地震局工程力学研究所 地震工程与工程振动重点实验室, 黑龙江 哈尔滨 150080;
2. 地震灾害防治应急管理部重点实验室, 黑龙江 哈尔滨 150080;
3. 河海大学 土木与交通学院, 江苏 南京 210024;
4. 云南省地震局, 云南 昆明 650224
Author(s):
SHAO Guoliang12 JI Kun3 WEN Ruizhi12 REN Yeifei12 CUI Jianwen4
1. Key Laboratory of Earthquake Engineering and Engineering Vibration, Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150080, China;
2. Key Laboratory of Earthquake Disaster Mitigation, Ministry of Emergency Management, Harbin 150080, China;
3. College of Civil and Transportation Engineering, Hohai University, Nanjing 210024, China;
4. Yunnan Earthquake Agency, Kunming 650224, China
关键词:
空间相关性强震动观测漾濞地震半变异函数
Keywords:
spatial correlationstrong motion observationYangbi earthquakesemi-variance
分类号:
P315.9
DOI:
10.13197/j.eeed.2022.0612
摘要:
地震动参数的空间相关模型可以用来有效地开展区域地震动场估计,也可用于后续区域地震风险准确评估。随着我国地震烈度速报与预警工程的全面建设,布设的密集烈度计观测台站大大提高了原有数字强震动台网的观测能力,为研究我国的地震动参数空间相关性模型提供了良好的契机。文中以2021年5月21日的云南漾濞Ms6.4级地震为主要研究对象,利用地质统计学的半变异函数方法,基于密集观测台网捕获的近场强震动记录,分析了地震动峰值加速度(PGA)、地震动峰值速度(PGV)及典型周期点加速度反应谱谱值的空间相关性特征,采用指数模型拟合得到了对应地震动参数的空间相关性函数。将拟合结果与2008年汶川Ms8.0级地震、2014年芦山Ms7.0级地震以及国外其他区域的相关研究进行对比,结果表明:空间相关性函数虽然整体趋势相近,呈现空间相关性随反应谱周期增大而增大的一般特征,但是川滇地区记录拟合得到的地震动参数空间相关性模型具有衰减更慢,有效变程值较大等区域性特征,同时也说明了基于我国密集观测台网进行地震动参数空间相关性分析的可行性。
Abstract:
To effectively estimate the regional ground motion field, it is common practice to use spatial correlation models of intensity measurements(IMs). It also plays the key role in the subsequent regional seismic risk assessment. With the construction of China earthquake intensity quick report and early warning project, a large number of seismic intensity stations were built and greatly improved the density of the original digital strong motion network. This provides a good opportunity to study the spatial correlation model of ground motion IMs in China. The Ms6.4 Yangbi, Yunnan earthquake scenario is studied in this paper. Based on near-field strong motion records captured by dense intensity network, the spatial correlation of peak ground acceleration(PGA), peak ground velocity(PGV) and acceleration response spectrum at different periods were calculated and obtained by using the semi-variance method of geostatistics. The spatial correlation model of corresponding ground motion IMs are fitted using exponential function. At the same time, the fitting results are compared with 2008 Wenchuan Ms8.0 earthquake, 2014 Lushan Ms7.0 earthquake and relevant studies in other regions over the world. The results indicate that although the overall trend is similar, the value of spatial correlation increases with the increase of the vibration period. The spatial correlation model of ground motion parameters fitted by the recordings in Sichuan and Yunnan Province of China show slower attenuation characteristics and have larger value of separation distance. The results prove that the spatial correlation of ground motion IMs could be effectively obtained by China dense strong motion observation network. With the accumulation of recordings, a more comprehensive spatial correlation model of ground motion IMs can be obtained. This provides the foundation for regional seismic resilience evaluation and seismic vulnerability analysis.

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备注/Memo

备注/Memo:
收稿日期:2022-06-27;改回日期:2022-09-13。
基金项目:中国地震局地震工程与工程振动重点实验室重点专项(2021EEEVL0103);国家自然科学基金项目(U2239252)
作者简介:邵国良(1997-),男,硕士研究生,主要从事工程地震方面研究.E-mail:shaohuanning@163.com
通讯作者:温瑞智(1968-),男,研究员,博士,主要从事工程地震与强震动技术研究.E-mail:ruizhi@iem.ac.cn
更新日期/Last Update: 1900-01-01