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Determining the characteristic period of ground motions (Tg) is an essential step in the seismic design of structures, but a critical problem that needs to be solved is figuring out how to do so when bedrock ground motion is utilized as an input. In this paper, the relationship between surface and borehole temperature data is investigated, and the main factors affecting the Tg are analyzed. Then, the algorithm for predicting Tg is presented. It is found that two factors, i.e., peak ground acceleration (PGA) and fault distance have significant effects on the value of Tg. By comparing the values of Tg for borehole and surface motions, we find that, contrary to expectation, Tg for borehole motions is usually larger than that for surface motions in most cases. Finally, the conversion equation between the Tg for borehole and surface motions is given using regression analysis. [ABSTRACT FROM AUTHOR]

Due to the complexity of the crustal medium and stratigraphic boundaries, seismic waves typically exhibit attenuation and dispersion after propagation through the medium. By studying the regularity of seismic wave dispersion, soil layer information can be extracted. Current spectral decomposition techniques take less account of signal filtering processing of seismic waves, and the complexity of the stratigraphy tends to reduce the accuracy of dispersion analysis. Based on the above, a new method for calculating the dispersion characteristics of a site from surface and downhole ground vibration recordings is proposed, which is simpler than the spectra analysis of surface waves (SASW) method and eliminates the need for multiple pickups and additional equipment. This method is based on wavelet decomposition and seismic wave filtering, and a numerical simulation example is established to verify the effectiveness of the method. Then, the records of the Tohoku earthquake on March 11, 2011 are used as actual strong earthquake examples for filtering and dispersion analysis. Finally, it is concluded that the seismic wave dispersion analysis method based on wavelet decomposition can effectively filter and analyze seismic waves in specific frequency bands. [ABSTRACT FROM AUTHOR]

Strong motion records with acceleration spikes have occurred frequently in recent major earthquakes, acceleration spikes contribute to the peak ground accelerations (PGAs) and the amplitudes are significantly higher than the predicted values based on present attenuation relation. The generation mechanism of acceleration spikes is revealed based on long-term monitoring after the 2008 Mw 8.0 Wenchuan earthquake. The horizontal accelerogram with obvious spikes from the Mw 9.0 Tohoku-Oki earthquake is reproduced by using numerical simulation, and it's found that the dilatancy cyclic mobility (DCM) mechanism can explain the generation of acceleration spikes. The support vector machine (SVM) is used to efficiently identify DCM sites. We found that the spatial distribution of DCM sites is parallel to the earthquake source fault and the corresponding PGAs of ground motions recorded in DCM sites differ significantly from those recorded in non-dilatancy cyclic mobility (NDCM) sites. [ABSTRACT FROM AUTHOR]

Assessing the nonlinearity of a site plays a crucial role in earthquake engineering. For some building structures and lifeline projects that need safety assessment after earthquakes, the analysis of nonlinear degree of sites can help accurately revealing the amplification effect of sites and evaluating the damage degree of buildings which is convenient for subsequent reinforcement and demolition work. The quantitation of nonlinear threshold of sites is an important method to evaluate the degree of site nonlinearity. In this paper, a nonlinear characteristic index reflecting the degradation of shear modulus is proposed based on the instantaneous frequency of the site calculated by using the vector auto-regression moving average (VARMA) model. Then, seismic records of class I, II, III and IV sites specified as per code for seismic design of buildings in China are selected from the KiK-net network in Japan, and the threshold value of ground motion acceleration characterizing the nonlinear response of sites are provided. Finally, the variation of the nonlinear characteristic index (shear modulus degradation) vs. different (peak ground acceleration) PGA for four types of sites are presented. [ABSTRACT FROM AUTHOR]

The seismic response of buildings is crucial for structural performance analysis. For structures with complete design data, the seismic response can be predicted using finite element analysis. However, for structures lacking necessary information, building finite element models and predicting their seismic response can be challenging. Compared to finite element analysis, convolutional neural networks (CNNs) can establish a neural network mapping relationship between the structure and the seismic response to predict the structural response without design data. In this paper, a structural response prediction model based on CNNs is established, aiming to analyze the effect of natural frequency reduction on the structural response after the Tohoku earthquake. The successful prediction of the structural acceleration and displacement response provides a new analytical method for predicting the seismic response of buildings lacking design data. [ABSTRACT FROM AUTHOR]