2016年熊本M_J7.3地震的工程地震动参数模拟及分布特征分析
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摘要
本文选取2016年4月16日日本熊本县MJ7.3 (MW7.0)地震近场区域内K-net地震台网的47个强震台站所记录的加速度数据,运用经验格林函数法模拟分析此次地震主要的工程地震参数并给出了各工程参数的空间分布。通过对比分析得到结论如下:(1)地震动时程的基本频谱的模拟结果较好,尤其是1—15 Hz的高频段内;(2)在震源距小于50 km范围内,峰值加速度和阿里亚斯强度的观测值与模拟值拟合较好,二者在近场区域均以椭圆形向周围扩散衰减,且阿里亚斯强度的模拟值整体大于观测值;(3)卓越周期拟合整体较好,但在局部区域存在较大差异,模拟结果难以表征场地环境的复杂性。
In this paper,the empirical Green's function method is used to simulate and analyze the main engineering seismic parameters of 47 strong stations from K-net of the M_J7.3(MW7.0) earthquake in Kumamoto county,Japan. The main conclusions are as follows:(1) The basic spectrum simulation results fitted better,especially in the high frequency band 1–15 Hz;(2) The simulated values of both peak ground acceleration and Arias intensity at the focal distance less than 50 km have the better fitting with observed values,they are diffused attenuating around the ellipse in the near field,and the simulated values of Arias intensity are greater than the observed values;(3) The predominant period fitting is good,as a whole,but there are larger differences in the local area. The simulated results cannot indicate the complexity of site condition.
In this paper,the empirical Green's function method is used to simulate and analyze the main engineering seismic parameters of 47 strong stations from K-net of the M_J7.3(MW7.0) earthquake in Kumamoto county,Japan. The main conclusions are as follows:(1) The basic spectrum simulation results fitted better,especially in the high frequency band 1–15 Hz;(2) The simulated values of both peak ground acceleration and Arias intensity at the focal distance less than 50 km have the better fitting with observed values,they are diffused attenuating around the ellipse in the near field,and the simulated values of Arias intensity are greater than the observed values;(3) The predominant period fitting is good,as a whole,but there are larger differences in the local area. The simulated results cannot indicate the complexity of site condition.
引文
李宗超,陈学良,高孟潭,王建龙,鄢兆伦,李铁飞.2016.经验格林函数方法模拟强地面运动的研究进展[J].世界地震工程,32(2):209-216.Li Z C,Chen X L,Gao M T,Wang J L,Yan Z L,Li T F.2016.Research progress of empirical Green function method simulation strong ground motion[J].World Earthquake Engineering,32(2):209-216(in Chinese).
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王秀英,聂高众,张玲.2010.汶川地震触发崩滑与Arias强度关系研究[J].应用基础与工程科学学报,18(4):645-656.Wang X Y,Nie G Z,Zhang L.2010.Relationship between landslides induced by the Wenchuan earthquake and Arias intensity[J].Journal of Basic Science and Engineering,18(4):645-656(in Chinese).
李启成.2010.经验格林函数方法模拟地震动研究[D].哈尔滨:中国地震局工程力学研究所:1-119.Li Q C.2010.Research on Ground Motion Simulation with Empirical Green Function Method[D].Harbin:Institute of Engineering Mechanics,China Earthquake Administration:1-119(in Chinese).
王海云.2004.近场强地震动预测的有限断层震源模型[D].哈尔滨:中国地震局工程力学研究所:1-135.Wang H Y.2004.Finite Fault Source Model for Predicating Near-Field Strong Ground Motion[D].Harbin:Institute of Engineering Mechanics,China Earthquake Administration:1-135(in Chinese).
Arias A.1970.A measure of earthquake intensity[G]//Seismic Design for Nuclear Power Plants.Cambridge:MIT Press:438-483.
Dai Z J,Li X J,Hou C L.2014.An optimization method for the generation of ground motions compatible with multi-damping design spectra[J].Soil Dynamics and Earthquake Engineering,66:199-205.
Dan K,Watanabe T,Tanaka T.1989.A semi-empirical method to synthesize earthquake ground motions based on approximate far-field shear-wave displacement[G]//Journal of Structural and Construction Engineering(Transactions of AIJ).Tokyo:Structural and Construction Engineering:27-36.
Del Gaudio V,Wasowski J.2004.Time probabilistic evaluation of seismically induced landslide hazard in Irpinia(Southern Italy)[J].Soil Dyn Earthq Eng,24(12):915-928.
Disaster Prevention Research Institute,Kyoto University.2016.Kumamoto earthquake[EB/OL].[2017-12-18].http://www.dpri.kyoto-u.ac.jp/disaster_report/#6806.
Irikura K.1983.Semi-empirical estimation of strong ground motion during large earthquake[J].Bull Disas Prev Res,33:151-156.
Irikura K.1986.Prediction of strong acceleration motion using empirical Green’s function[C]//Proceedings of the 7th Japan Earthquake Engineering Symposium.Tokyo:Architectural Institute of Japan:151-156.
Irikura K,Kamae K.1994.Estimation of strong ground motion in broad-frequency band based on a seismic source scaling model and an empirical Green’s function technique[J].Ann Geophys,37(6):1721-1743.
Irikura K,Miyake H.2011.Recipe for predicting strong ground motion from crustal earthquake scenarios[J].Pure Appl Geophys,168(1/2):85-104.
Irikura K,Miyakoshi K,Kamae K,Yoshida K,Somei K,Kurahashi S,Miyake H.2017.Applicability of source scaling relations for crustal earthquakes to estimation of the ground motions of the 2016 Kumamoto earthquake[J].Earth Planets Space,69:10.
Kanamori H.1979.A semi-empirical approach to prediction of long-period ground motions from great earthquake[J].Bull Seismol Soc Am,69(6):1654-1670.
Li Z C,Chen X L,Gao M T,Jiang H,Li T F.2017.Simulating and analyzing engineering parameters of Kyushu Earthquake,Japan,1997,by empirical Green function method[J].J Seismol,21(2):367-384.
Li Z C,Gao M T,Jiang H,Chen X L,Li T F,Zhao X F.2018.Sensitivity analysis study of the source parameter uncertainty factors for predicting near-field strong ground motion[J].Acta Geophys,66(4):523-540.
Miyake H,Iwata T,Irikura K.2003.Source characterization for broadband ground-motion simulation:Kinematic heterogeneous source model and strong motion generation area[J].Bull Seismol Soc Am,93(6):2531-2545.
National Research Institute for Earth Science and Disaster Resilience.2016.Strong-motion seismograph networks(K-NET,KIK-NET)[EB/OL].[2017-12-18].http://www.kyoshin.bosai.go.jp/kyoshin/data/index_en.html.
Somerville P,Irikura K,Graves R,Sawada S,Wald D,Abrahamson N,Iwasaki Y,Kagawa T,Smith N,Kowada A.1999.Characterizing crustal earthquake slip models for the prediction of strong ground motion[J].Seismol Res Lett,70(1):59-80.
李宗超.2017.大震近场地震动数值模拟不确定性研究[D].北京:中国地震局地球物理研究所:1-126.Li Z C.2017.The Uncertainty Factors Research of Near-Field Ground Motion Numerical Simulation[D].Beijing:Institute of Geophysics,China Earthquake Administration:1-126(in Chinese).
王秀英,聂高众,张玲.2010.汶川地震触发崩滑与Arias强度关系研究[J].应用基础与工程科学学报,18(4):645-656.Wang X Y,Nie G Z,Zhang L.2010.Relationship between landslides induced by the Wenchuan earthquake and Arias intensity[J].Journal of Basic Science and Engineering,18(4):645-656(in Chinese).
李启成.2010.经验格林函数方法模拟地震动研究[D].哈尔滨:中国地震局工程力学研究所:1-119.Li Q C.2010.Research on Ground Motion Simulation with Empirical Green Function Method[D].Harbin:Institute of Engineering Mechanics,China Earthquake Administration:1-119(in Chinese).
王海云.2004.近场强地震动预测的有限断层震源模型[D].哈尔滨:中国地震局工程力学研究所:1-135.Wang H Y.2004.Finite Fault Source Model for Predicating Near-Field Strong Ground Motion[D].Harbin:Institute of Engineering Mechanics,China Earthquake Administration:1-135(in Chinese).
Arias A.1970.A measure of earthquake intensity[G]//Seismic Design for Nuclear Power Plants.Cambridge:MIT Press:438-483.
Dai Z J,Li X J,Hou C L.2014.An optimization method for the generation of ground motions compatible with multi-damping design spectra[J].Soil Dynamics and Earthquake Engineering,66:199-205.
Dan K,Watanabe T,Tanaka T.1989.A semi-empirical method to synthesize earthquake ground motions based on approximate far-field shear-wave displacement[G]//Journal of Structural and Construction Engineering(Transactions of AIJ).Tokyo:Structural and Construction Engineering:27-36.
Del Gaudio V,Wasowski J.2004.Time probabilistic evaluation of seismically induced landslide hazard in Irpinia(Southern Italy)[J].Soil Dyn Earthq Eng,24(12):915-928.
Disaster Prevention Research Institute,Kyoto University.2016.Kumamoto earthquake[EB/OL].[2017-12-18].http://www.dpri.kyoto-u.ac.jp/disaster_report/#6806.
Irikura K.1983.Semi-empirical estimation of strong ground motion during large earthquake[J].Bull Disas Prev Res,33:151-156.
Irikura K.1986.Prediction of strong acceleration motion using empirical Green’s function[C]//Proceedings of the 7th Japan Earthquake Engineering Symposium.Tokyo:Architectural Institute of Japan:151-156.
Irikura K,Kamae K.1994.Estimation of strong ground motion in broad-frequency band based on a seismic source scaling model and an empirical Green’s function technique[J].Ann Geophys,37(6):1721-1743.
Irikura K,Miyake H.2011.Recipe for predicting strong ground motion from crustal earthquake scenarios[J].Pure Appl Geophys,168(1/2):85-104.
Irikura K,Miyakoshi K,Kamae K,Yoshida K,Somei K,Kurahashi S,Miyake H.2017.Applicability of source scaling relations for crustal earthquakes to estimation of the ground motions of the 2016 Kumamoto earthquake[J].Earth Planets Space,69:10.
Kanamori H.1979.A semi-empirical approach to prediction of long-period ground motions from great earthquake[J].Bull Seismol Soc Am,69(6):1654-1670.
Li Z C,Chen X L,Gao M T,Jiang H,Li T F.2017.Simulating and analyzing engineering parameters of Kyushu Earthquake,Japan,1997,by empirical Green function method[J].J Seismol,21(2):367-384.
Li Z C,Gao M T,Jiang H,Chen X L,Li T F,Zhao X F.2018.Sensitivity analysis study of the source parameter uncertainty factors for predicting near-field strong ground motion[J].Acta Geophys,66(4):523-540.
Miyake H,Iwata T,Irikura K.2003.Source characterization for broadband ground-motion simulation:Kinematic heterogeneous source model and strong motion generation area[J].Bull Seismol Soc Am,93(6):2531-2545.
National Research Institute for Earth Science and Disaster Resilience.2016.Strong-motion seismograph networks(K-NET,KIK-NET)[EB/OL].[2017-12-18].http://www.kyoshin.bosai.go.jp/kyoshin/data/index_en.html.
Somerville P,Irikura K,Graves R,Sawada S,Wald D,Abrahamson N,Iwasaki Y,Kagawa T,Smith N,Kowada A.1999.Characterizing crustal earthquake slip models for the prediction of strong ground motion[J].Seismol Res Lett,70(1):59-80.