防灾减灾工程学报2024，Vol.44Issue(2)：353-361,9.DOI:10.13409/j.cnki.jdpme.20221102005
给定地震场景下的随机地震动降维模拟
Dimension-reduction Simulation of Stochastic Ground Motion under Predefined Earthquake Scenarios
摘要
Abstract
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.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Key words
measured ground motion records/earthquake scenario/parameter identification/Gaussian process regression/nonstationary ground motion process/dimension-reduction simulation分类
天文与地球科学引用本文复制引用
阮鑫鑫,范颖霏,刘章军,姜云木..给定地震场景下的随机地震动降维模拟[J].防灾减灾工程学报,2024,44(2):353-361,9.基金项目
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 （51978543,51778343）
