scholarly journals Simulation of Spatially Correlated Multipoint Ground Motions in a Saturated Alluvial Valley

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ying He ◽  
Xueling Chen ◽  
Zhongxian Liu ◽  
Dejian Yang ◽  
Hai Zhang
Keyword(s):  
Seismic Analysis ◽  
Ground Motions ◽  
Coherence Function ◽  
Simulation Method ◽  
Spectral Density Function ◽  
Period Range ◽  
Spatially Correlated ◽  
Local Site ◽  
Spectral Representation Method ◽  
Representation Method

Based on Biot’s theory, the boundary element method, and spectral representation method, an effective simulation method for multiple-station spatially correlated ground motions on both bedrock and surface is developed, incorporating the spectral density function, coherence function, and site transfer function that consider both the wave scattering effect and the medium saturation. The accuracy and feasibility of the present method are validated by a typical numerical example. Our results indicate that the local site conditions and the saturation property of the medium significantly affect the multipoint spatially correlated earthquake ground motions, especially in the long-period range. It is necessary to use spatially varying ground motions with the rational consideration of local site effects and medium saturation as input during the seismic analysis of large-span structures.

scholarly journals An Improved Hilbert Spectral Representation Method for Synthesizing Spatially Correlated Earthquake Ground Motions and Its Error Assessment

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Luhua Zhu ◽  
Erlei Yao
Keyword(s):  
Closed Form ◽  
Ground Motions ◽  
Random Phase ◽  
Matrix Decomposition ◽  
Closed Form Solutions ◽  
Spatially Correlated ◽  
Spectral Representation Method ◽  
Stochastic Errors ◽  
Different Types ◽  
Representation Method

This paper is an extension of the random amplitude-based improved Hilbert spectral representation method (IHSRM) that the authors developed previously for the simulation of spatially correlated earthquake ground motions (SCEGMs) possessing the nonstationary characteristics of the natural earthquake record. In fact, depending on the fundamental types (random phase method and random amplitude method) and matrix decomposition methods (Cholesky decomposition, root decomposition, and eigendecomposition), the IHSRM possesses various types. To evaluate the influence of different types of this method on the statistic errors, i.e., bias errors and stochastic errors, an error assessment for this method was conducted. First, the random phase-based IHSRM was derived, and its reliability was proven by theoretical deduction. Unified formulas were given for random phase- and random amplitude-based IHSRMs, respectively. Then, the closed-form solutions of statistic errors of simulated seismic motions were derived. The validness of the proposed closed-form solutions was proven by comparing the closed-form solutions with estimated values. At last, the stochastic errors of covariance (i.e., variance and cross-covariance) for different types of IHSRMs were compared, and the results showed that (1) the proposed IHSRM is not ergodic; (2) the random amplitude-based IHSRMs possessed higher stochastic errors of covariance than the random phase-based IHSRMs; and (3) the value of the stochastic error of covariance for the random phase-based IHSRM is dependent on the matrix decomposition method, while that for the random amplitude-based one is not.

Comparison of the Spectral Representation Method to Simulate Spatially Variable Ground Motions

2013 ◽  
Vol 18 (3) ◽  
pp. 458-475 ◽  
Author(s):  
Yongxin Wu ◽  
Yufeng Gao ◽  
Dayong Li ◽  
Tugen Feng ◽  
Ali H. Mahfouz
Keyword(s):  
Spectral Representation ◽  
Ground Motions ◽  
Spectral Representation Method ◽  
Representation Method

scholarly journals Simulation of response spectrum-compatible ground motions using wavelet-based multi-resolution analysis

2021 ◽  
pp. 002029402110130
Author(s):  
Guan Chen ◽  
Zhiren Zhu ◽  
Jun Hu
Keyword(s):  
Ground Motion ◽  
Response Spectrum ◽  
Ground Motions ◽  
Power Spectra ◽  
Simulation Method ◽  
Eurocode 8 ◽  
Effective Response ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Simulated Ground Motions

This study proposed a simple and effective response spectrum-compatible ground motions simulation method to mitigate the scarcity of ground motions on seismic hazard analysis base on wavelet-based multi-resolution analysis. The feasibility of the proposed method is illustrated with two recorded ground motions in El Mayor-Cucapah earthquake. The results show that the proposed method enriches the ground motions exponentially. The simulated ground motions agree well with the attenuation characteristics of seismic ground motion without modulating process. Moreover, the pseudo-acceleration response spectrum error between the recorded ground motion and the average of the simulated ground motions is 5.2%, which fulfills the requirement prescribed in Eurocode 8 for artificially simulated ground motions. Besides, the cumulative power spectra between the simulated and recorded ground motions agree well on both high- and low-frequency regions. Therefore, the proposed method offers a feasible alternative in enriching response spectrum-compatible ground motions, especially on the regions with insufficient ground motions.

Conditioned Simulation of Ground-Motion Time Series at Uninstrumented Sites Using Gaussian Process Regression

2021 ◽  
Author(s):  
Aidin Tamhidi ◽  
Nicolas Kuehn ◽  
S. Farid Ghahari ◽  
Arthur J. Rodgers ◽  
Monica D. Kohler ◽  
...  
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Ground Motion ◽  
San Francisco ◽  
Earthquake Engineering ◽  
Seismic Analysis ◽  
Ground Motions ◽  
Free Field ◽  
Gaussian Process Regression ◽  
Motion Time

ABSTRACT Ground-motion time series are essential input data in seismic analysis and performance assessment of the built environment. Because instruments to record free-field ground motions are generally sparse, methods are needed to estimate motions at locations with no available ground-motion recording instrumentation. In this study, given a set of observed motions, ground-motion time series at target sites are constructed using a Gaussian process regression (GPR) approach, which treats the real and imaginary parts of the Fourier spectrum as random Gaussian variables. Model training, verification, and applicability studies are carried out using the physics-based simulated ground motions of the 1906 Mw 7.9 San Francisco earthquake and Mw 7.0 Hayward fault scenario earthquake in northern California. The method’s performance is further evaluated using the 2019 Mw 7.1 Ridgecrest earthquake ground motions recorded by the Community Seismic Network stations located in southern California. These evaluations indicate that the trained GPR model is able to adequately estimate the ground-motion time series for frequency ranges that are pertinent for most earthquake engineering applications. The trained GPR model exhibits proper performance in predicting the long-period content of the ground motions as well as directivity pulses.

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