Volume 39 Issue 3
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HU Jin-jun, JIN Chao-yue, ZHANG Hui, HU Lei, WANG Zhong-wei. A GROUND MOTION SYNTHESIS METHOD FOR MATCHING MULTI-OBJECTIVE PARAMETERS[J]. Engineering Mechanics, 2022, 39(3): 126-136. DOI: 10.6052/j.issn.1000-4750.2021.01.0095
Citation: HU Jin-jun, JIN Chao-yue, ZHANG Hui, HU Lei, WANG Zhong-wei. A GROUND MOTION SYNTHESIS METHOD FOR MATCHING MULTI-OBJECTIVE PARAMETERS[J]. Engineering Mechanics, 2022, 39(3): 126-136. DOI: 10.6052/j.issn.1000-4750.2021.01.0095
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A GROUND MOTION SYNTHESIS METHOD FOR MATCHING MULTI-OBJECTIVE PARAMETERS

  • Key Laboratory of Earthquake Engineering Vibration, Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150080, China

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  • Received Date: January 25, 2021
  • Revised Date: June 04, 2021
  • Available Online: June 28, 2021
    Abstract
  • Ground motion synthesis methods provide input time histories for structural seismic design and performance evaluation. The existing synthesis methods can only match the target spectrum to consider the frequency spectrum and amplitude of the ground motion, but cannot consider the duration characteristics. To synthesize ground motions which matches the three elements of ground motions for a specific area, a method that incorporates machine learning is proposed. In this method, the data-driven principal component analysis is used to extract the characteristic mother waves from the actual ground motion database of the target area. The target response spectrum and duration are obtained by the ground motion prediction equation of the region. The multi-objective genetic algorithm is applied to solve the linear combination coefficient of the mother waves, so that the combined ground motion can match the preset error standard and the multi-objective parameters of the regional ground motion. The method is verified for the 2019 Ms 6.0 Changning earthquake in Sichuan Province. The results show that, because the proposed method is driven by the actual ground motion data in the target area, the synthetic ground motion matches the demand of the target spectrum and the duration characteristics of regional ground motions, which can provide more reasonable ground motion inputs for seismic analyses considering regional seismic characteristics.
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    • References (38)
  • [1]
    Housner G W. Characteristics of strong motion earthquake [J]. Bulletin of the Seismological Society of Ameriea, 1947, 37(l): 19 − 31.
    [2]
    Irikura K. Semi-emirical estimation of strong ground motions during large earthquake [J]. Bulletin of the Disaster Prevention Research Institude, 1983, 33: 63 − 104.
    [3]
    Kanamori H, Anderson D L. Theoretical basis of some empirical relations in seismology [J]. Bulletin of the Seismological Society of America, 1975, 65: 1073 − 1095.
    [4]
    Boore D M. Stochastic simulation of high-frequency ground motions based on seismological models of the radiated [J]. Bulletin of the Seismological Society of America, 1983, 73(6): 1865 − 1894.
    [5]
    Motazedian D. Stochastic finite-fault modeling based on a dynamic corner frequency [J]. Bulletin of the Seismological Society of America, 2005, 95(3): 995 − 1010. doi: 10.1785/0120030207
    [6]
    Wang G, Ding Y, Borcherdt R. Simulation of acceleration field of the Lushan earthquake (Ms7.0, April 20, 2013, China) [J]. Engineering Geology, 2015, 189: 84 − 97. doi: 10.1016/j.enggeo.2015.02.003
    [7]
    Scanlan R H, Sachs K. Earthquake time histories and response spectra [J]. Journal of the Engineering Mechanics Division, 1974, 100(4): 635 − 655.
    [8]
    Beaudet P R. Synthesis of nonstationary seismic signals [J]. Bulletin of the Seismological Society of America, 1970, 60(5): 1615 − 1624.
    [9]
    Liang J, Chaudhuri S R, Shinozuka M. Simulation of nonstationary stochastic processes by spectral representation [J]. Journal of Engineering Mechanics, 2007, 133(6): 616 − 627. doi: 10.1061/(ASCE)0733-9399(2007)133:6(616)
    [10]
    Wang Ding, Fan Zenglei, Hao Shengwang, et al. An evolutionary power spectrum model of fully nonstationary seismic ground motion [J]. Soil Dynamics & Earthquake Engineering, 2017, 105: 1 − 10.
    [11]
    Cacciola P, Deodatis G. A method for generating fully non-stationary and spectrum-compatible ground motion vector processes [J]. Soil Dynamics & Earthquake Engineering, 2011, 31(3): 351 − 360.
    [12]
    李文博, 刘铁林, 王宇. 地震动加速度、速度和位移时程的构成[J]. 工程力学, 2020, 37(增刊): 164 − 167. doi: 10.6052/j.issn.1000-4750.2019.04.S029

    Li Wenbo, Liu Tielin, Wang Yu. Compositions of time histories of acceleration and velocity and displacement of ground motion [J]. Engineering Mechanics, 2020, 37(Suppl): 164 − 167. (in Chinese) doi: 10.6052/j.issn.1000-4750.2019.04.S029
    [13]
    孙小云, 韩建平, 党育, 等. 地震动持时对考虑梁柱节点区不同破坏模式RC框架的地震易损性影响[J]. 工程力学, 2018, 35(5): 193 − 203. doi: 10.6052/j.issn.1000-4750.2017.01.0089

    Sun Xiaoyun, Han Jianping, Dang Yu, et al. Effect of ground motion duration on seismic fragility of RC frames with different beam-column joint failure modes [J]. Engineering Mechanics, 2018, 35(5): 193 − 203. (in Chinese) doi: 10.6052/j.issn.1000-4750.2017.01.0089
    [14]
    朱瑞广, 吕大刚. 基于Copula函数的主余震地震动强度参数相关性分析[J]. 工程力学, 2019, 36(2): 114 − 123. doi: 10.6052/j.issn.1000-4750.2017.12.0921

    Zhu Ruiguang, Lü Dagang. Copula-based correlation analysis of intensity measures of mainshock-aftershock ground motion [J]. Engineering Mechanics, 2019, 36(2): 114 − 123. (in Chinese) doi: 10.6052/j.issn.1000-4750.2017.12.0921
    [15]
    Bommer J J, Martínez-Pereira A. The effective duration of earthquake strong motion [J]. Journal of Earthquake Engineering, 1999, 3(2): 127 − 172.
    [16]
    Mahin S A. Effects of duration and aftershocks on inelastic design earthquakes [C]. Istanbul: Seventh World Conference on Earthquake Engineering, 1980.
    [17]
    Cabanias L, Benito B, Herraiz M. An approach to the measurement of the potential structural damage of earthquake ground motions [J]. Earthquake Engineering and Structural Dynamics, 2015, 26(1): 79 − 92.
    [18]
    张齐. 地震动衰减关系区域性差异研究[D]. 哈尔滨: 中国地震局工程力学研究所, 2016.

    Zhang Qi. Study on regional differentiation of ground motion attenuation relationship [D]. Harbin: Institute of Engineering Mechanics, China Earthquake Administration, 2016. (in Chinese)
    [19]
    Murphy K P. Machine learning: A probabilistic perspective [M]. Cambridge: MIT Press, 2012.
    [20]
    Jordan M I, Mitchell T M. Machine learning: Trends, perspectives, and prospects [J]. Science, 2015, 349(6245): 255 − 260. doi: 10.1126/science.aaa8415
    [21]
    Witten I H, Frank E, Hall M A, et al. Data mining: Practical machine learning tools and techniques [M]. Burlington: Morgan Kaufmann, 2016.
    [22]
    Kong Q, Trugman D T, Ross Z E, et al. Machine learning in seismology: Turning data into insights [J]. Seismological Research Letters, 2019, 90(1): 3 − 14. doi: 10.1785/0220180259
    [23]
    Bergen K J, Chen T, Li Z. Preface to the focus section on machine learning in seismology [J]. Seismological Research Letters, 2019, 90(2A): 477 − 480. doi: 10.1785/0220190018
    [24]
    Sagiroglu S, Sinanc D. Big data: A review [C]// 2013 International Conference on Collaboration Technologies and Systems (CTS). San Diego, Institute of Electrical and Electronics Engineers, 2013: 42 − 47.
    [25]
    Khosravikia F, Clayton P, Nagy Z. Artificial neural network‐based framework for developing ground‐motion models for natural and induced earthquakes in oklahoma, kansas, and texas [J]. Seismological Research Letters, 2019, 90(2A): 604 − 613. doi: 10.1785/0220180218
    [26]
    Kotha S R, Cotton F, Bindi D. A new approach to site classification: Mixed-effects ground motion prediction equation with spectral clustering of site amplification functions [J]. Soil Dynamics and Earthquake Engineering, 2018, 110: 318 − 329. doi: 10.1016/j.soildyn.2018.01.051
    [27]
    Alimoradi A, Beck J L. Machine-learning methods for earthquake ground motion analysis and simulation [J]. Journal of Engineering Mechanics, 2015, 141(4): 04014147. doi: 10.1061/(ASCE)EM.1943-7889.0000869
    [28]
    Boore D M. Stochastic simulation of high-frequency ground motions based on seismological models of the radiated spectra [J]. Bulletin of the Seismological Society of America, 1983, 73(6A): 1865 − 1894.
    [29]
    Jolliffe I T. Principal component analysis [J]. Journal of Marketing Research, 2002, 87(4): 513 − 516.
    [30]
    胡进军, 张辉, 靳超越, 等. 基于PCA及PSO智能算法的地震动合成方法—以中国西部中强地震为例[J]. 工程力学, 2021, 38(3): 159 − 168. doi: 10.6052/j.issn.1000-4750.2020.05.0293

    Hu Jinjun, Zhang Hui, Jin Chaoyue, et al. A method to simulate ground motion based on PCA and PSO intelligent algorithms—a case study of moderate magnitude earthquakes in western China [J]. Engineering Mechanics, 2021, 38(3): 159 − 168. (in Chinese) doi: 10.6052/j.issn.1000-4750.2020.05.0293
    [31]
    刘亭亭, 于晓辉, 吕大刚. 地震动多元强度参数主成分与结构损伤的相关性分析[J]. 工程力学, 2018, 35(8): 122 − 129, 137. doi: 10.6052/j.issn.1000-4750.2017.04.0289

    Liu Tingting, Yu Xiaohui, Lü Dagang. Analysis of correlation between principal components of multivariate earthquake intensity measures and structural damage [J]. Engineering Mechanics, 2018, 35(8): 122 − 129, 137. (in Chinese) doi: 10.6052/j.issn.1000-4750.2017.04.0289
    [32]
    张敏政. 地震工程的概念和应用[M]. 北京: 地震出版社, 2015.

    Zhang Minzheng. Concepts and applications of earthquake engineering [M]. Beijing: Seismological Press, 2015. (in Chinese)
    [33]
    Deb K, Pratap A, Agarwal S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-II [J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182 − 197. doi: 10.1109/4235.996017
    [34]
    易桂喜, 龙锋, 梁明剑, 等. 2019年6月17日四川长宁Ms6.0地震序列震源机制解与发震构造分析0地震序列震源机制解与发震构造分析[J]. 地球物理学报, 2019, 62(9): 3432 − 3447.

    Yi Guixi, Long Feng, Liang Mingjian, et al. Focal mechanism solutions and seismogenic structure of the 17 June 2019 Ms6.0 Sichuan Changning earthquake sequence [J]. Chinese Journal of Geophysics, 2019, 62(9): 3432 − 3447. (in Chinese)
    [35]
    Boore D M, Lamprey J W, Abrahamson N A. Orientation-independent measures of ground motion [J]. Bulletin of the Seismological Society of America, 2006, 96: 1502 − 1511. doi: 10.1785/0120050209
    [36]
    俞言祥, 汪素云. 中国东部和西部地区水平向基岩加速度反应谱衰减关系[J]. 震灾防御技术, 2006(3): 206 − 217. doi: 10.3969/j.issn.1673-5722.2006.03.005

    Yu Yanxiang, Wang Suyun. Attenuation relations for horizontal peak ground acceleration and response spectrum in Eastern and Western China [J]. Technology for Earthquake Disaster Prevention, 2006(3): 206 − 217. (in Chinese) doi: 10.3969/j.issn.1673-5722.2006.03.005
    [37]
    徐培彬, 温瑞智. 基于我国强震动数据的地震 动持时预测方程[J]. 地震学报, 2018, 40(6): 809 − 819, 832.

    Xu Peibin, Wen Ruizhi. The prediction equations for the significant duration of strong motion in Chinese mainland [J]. Acta Seismologica Sinica, 2018, 40(6): 809 − 819, 832. (in Chinese)
    [38]
    霍俊荣. 近场强地面运动的衰减规律[D]. 哈尔滨: 国家地震局工程力学研究所, 1989.

    Huo Junrong. Near-field strong ground motion attenuation law [D]. Harbin: The State Bureau of Seismology, 1989. (in Chinese)
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