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A Probabilistic Seismic Hazard Analysis Method Incorporating Physics-Based Simulation and Ground Motion Prediction Equation

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摘要 The traditional approach to probabilistic seismic hazard analysis(PSHA)relies on ground motion records,which restricts its application in regions with sparse seismic records or low seismicity.Recently,the 3D physics-based simulation(PBS)has been recognized as a more effective tool,which offers the flexibility to generate time histories of simulated ground motions.The PBS methods are essential for obtaining ground motion parameters and compensating for lack of records.In this study,building on the theoretical framework of the China Probabilistic Seismic Hazard Analysis(CPSHA)method,we integrated the hierarchical potential focal region model from the fifth-generation seismic ground motion parameters zonation map of China and an appropriate seismicity model reflecting spatial distribution characteristics.Ground motion parameters at the target scale were calculated using PBS for near-field seismic simulations and ground motion prediction equations(GMPEs)for far-field seismic predictions,accounting for the uncertainties in ground motion attenuation from both methods to compute the seismic hazard of each site.In this manner,we established a comprehensive regional probabilistic seismic hazard analysis method combining PBS and GMPE.Using Tianjin as a case study,a probabilistic seismic hazard analysis was conducted with this method,providing seismic hazard curves for specific sites within each administrative region and zoning maps,which were then compared with the results of the fifth-generation zonation maps.The results indicate that the calculated seismic hazard values are generally consistent with the fifth-generation map at the lower limit,while the upper limit is slightly higher due to the near-fault effect.
出处 《International Journal of Disaster Risk Science》 2025年第3期392-407,共16页 国际灾害风险科学学报(英文版)
基金 supported by the National Key Research and Development Program of China under Grant No.2023YFC3805200 the National Natural Science Foundation of China under Grant Nos.52178495 and 52308513 the Postdoctoral Fellowship Program of CPSF under Grant No.GZB20230487。
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