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作 者:Ji Kun Cao Xuyang Wang Suyang Wen Ruizhi
机构地区:[1]College of Civil and Transportation Engineering,Hohai University,Nanjing 210098,China [2]The Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education,Beijing University of Technology,Beijing 100022,China [3]Key Laboratory of Earthquake Engineering and Engineering Vibration,Institute of Engineering Mechanics,China Earthquake Administration,Harbin 150080,China [4]Key Laboratory of Earthquake Disaster Mitigation,Ministry of Emergency Management,Harbin 150080,China
出 处:《Earthquake Engineering and Engineering Vibration》2024年第4期799-814,共16页地震工程与工程振动(英文刊)
基 金:National Key Research and Development Program of China under Grant No.2023YFE0102900;National Natural Science Foundation of China under Grant Nos.52378506 and 52208164。
摘 要:Although the classical spectral representation method(SRM)has been widely used in the generation of spatially varying ground motions,there are still challenges in efficient simulation of the non-stationary stochastic vector process in practice.The first problem is the inherent limitation and inflexibility of the deterministic time/frequency modulation function.Another difficulty is the estimation of evolutionary power spectral density(EPSD)with quite a few samples.To tackle these problems,the wavelet packet transform(WPT)algorithm is utilized to build a time-varying spectrum of seed recording which describes the energy distribution in the time-frequency domain.The time-varying spectrum is proven to preserve the time and frequency marginal property as theoretical EPSD will do for the stationary process.For the simulation of spatially varying ground motions,the auto-EPSD for all locations is directly estimated using the time-varying spectrum of seed recording rather than matching predefined EPSD models.Then the constructed spectral matrix is incorporated in SRM to simulate spatially varying non-stationary ground motions using efficient Cholesky decomposition techniques.In addition to a good match with the target coherency model,two numerical examples indicate that the generated time histories retain the physical properties of the prescribed seed recording,including waveform,temporal/spectral non-stationarity,normalized energy buildup,and significant duration.
关 键 词:non-stationarity time-varying spectrum wavelet packet transform(WPT) spectral representation method(SRM) response spectrum spatially varying recordings
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