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摘要
In this study, we use a genetic algorithm to invert horizontal groundmotion intensity measures (GMIMs) predicted from the empirical Next Generation Attenuation-West2 (NGA-West2) ground-motion prediction equations (GMPEs) to estimate a consistent and correlated set of seismological parameters to use with an equivalent point-source stochastic model. The GMIMs are peak ground acceleration and pseudospectral acceleration evaluated over a wide range of magnitudes, distances, and frequencies. The inversion is performed for M 3.5-8.0, R-RUP = 1-300 km, T = 0.01-10 s, and National Earthquake Hazard Reduction Program (NEHRP) B/C site conditions. Seismological parameters are obtained as a function of earthquake magnitude. The near-source geometric spreading was modeled as both magnitude-and frequency dependent to fit the empirical predictions. The agreement between the model and empirical predictions over all magnitudes and distances evaluated in this study is generally within 10%, with some local exceptions. The near-source geometric spreading is consistent with a distance decay of R-0.8 to R-1.3 at frequencies of f <= 1 Hz for Mranging from 3.5 to 8. Near 5 Hz, the distance decay is expressed as R-1.17, on average at short distances. At larger frequencies, the near-source distance decay varies from R-1.0 to R-1.25. This stochasticmodel can be used for any application that requires a frequencydomain representation of the NGA-West2 GMPEs.
Electronic Supplement: Plots showing comparisons of predicted response spectra from the median Next Generation Attenuation-West2 (NGA-West2) ground-motion prediction equations (GMPEs) with the predicted response spectra for different magnitudes, distances, and frequencies, and residuals versus frequency between the predicted response spectra from the median NGA-West2 GMPEs and the predicted response spectra for different magnitudes, distances, and frequencies.
- 出版日期2018-4
