摘要
建立了一种可根据地震场景预测和模拟随机地震动加速度过程的降维模型。首先,挑选了1 766条实测强震记录,根据断层类型和场地类别进行了分组,并识别了各组地震动的演变功率谱参数;然后,基于地震场景参数和演变功率谱参数,训练了两者的高斯过程回归模型(GPRM),并采用K-fold交叉验证法,验证GPRM预测的有效性和精确性;最后,基于非平稳随机过程的谱表示法,通过引入随机函数的降维思想,实现了在给定地震场景下的随机地震动降维模拟。数值算例表明,预测的样本在频谱、峰值、强震持时等方面均与实测记录保持一致,体现了本文方法良好的工程适用性。这为地震动目标地区提供较为合理的人工地震动数据以及工程结构的随机地震反应分析与可靠性评价奠定了基础。
Based on the earthquake scenarios,a dimension-reduction model capable of predicting and simulating the stochastic ground motion acceleration process was developed.Firstly,1766 strong mo-tion records were selected and grouped according to fault types and site classification.Parameters of evolutionary power spectrum(EPS)for each group were identified.Secondly,based on the parameters for earthquake scenarios and the EPS,a Gaussian process regression model(GPRM)was trained.Meanwhile,the K-fold cross-validation method was adopted to verify its prediction effectiveness and accuracy.Finally,using the spectral representation method of non-stationary random processes and in-corporating the concept of dimension reduction for random functions,the dimension reduction simula-tion of stochastic ground motion was achieved under predefined earthquake scenarios.Numerical ex-amples showed that the predicted samples were consistent with the measured records in terms of fre-quency spectrum,peak values,and duration of strong motion,which verified the suitability of the pro-posed methodology in engineering applications.The research provides reasonable artificial ground mo-tion data for target areas,and lays a foundation for random seismic response analysis and reliability evaluations of engineering structures.
作者
阮鑫鑫
范颖霏
刘章军
姜云木
RUAN Xinxin;FAN Yingfei;LIU Zhangjun;JIANG Yunmu(College of Architecture and Civil Engineering,Xinyang Normal University,Xinyang 464000 China;School of Civil Engineering and Architecture,Wuhan Institute of Technology,Wuhan 430074 China;State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technology,Dalian 116024 China)
出处
《防灾减灾工程学报》
CSCD
北大核心
2024年第2期353-361,共9页
Journal of Disaster Prevention and Mitigation Engineering
基金
国家自然科学基金项目(51978543,51778343)
湖北省高等学校优秀中青年科技创新团队计划项目(T2020010)资助。
关键词
实测地震动记录
地震场景
参数识别
高斯过程回归
非平稳地震动过程
降维模拟
measured ground motion records
earthquake scenario
parameter identification
Gaussian process regression
nonstationary ground motion process
dimension-reduction simulation
