Development of a Record-Based Stochastic Ground Motion Model for Chile

Abstract eng:
Stochastic ground motion models can facilitate a versatile description of earthquake acceleration time histories by modulating a white-noise sequence through functions that address spectral and temporal properties of the excitation. This is established by (i) selecting appropriate time/frequency modulation functions and (ii) relating the parameters of these functions to seismological (fault type, moment magnitude and rupture distance) and site (shear wave velocity) characteristics through predictive relationships. Various approaches have been proposed to accomplish these tasks. Sourcebased models (also known as physics-based) rely on physical modeling of the rupture and wave propagation mechanisms, whereas record-based models (also known as site-based) are developed by fitting a preselected “waveform” to a suite of recorded regional ground motions. In recent years, record-based models have gained increasing popularity within the structural engineering community, due to their versatility in selecting their waveforms to capture all important features of ground motion (such as spectral non-stationarities, deemed important for inelastic structures). This paper investigates the development of a record-based stochastic ground motion model for Chile by utilizing a suite of ground motions recorded by the RENADIC (Red de cobertuta nacional de acelerografos) network and the Seismological Center of the University of Chile. A stochastic model that addresses both temporal and spectral non-stationarities, corresponding to a series of cascading single-degree-of-freedom (SDOF) oscillators with time-varying frequency and damping, is adopted as the basis for this development. The stochastic model is then modified appropriately through information extracted from the available ground motion suite. This facilitates a complete parameterization of the time and frequency functions defining the stochastic ground motion model. An identification framework is then discussed that provides the optimal fit of the parameterized model to a specific ground motion, and a validation of the resultant model is proposed in terms of the corresponding response spectrum. The results of this identification are then exploited to develop, though regression analyses, predictive relationships that relate the model parameters to seismicity characteristics. This facilitates the generation of synthetic motions for specific seismic scenarios. The corresponding model and regression relationships are finally validated by comparison to regional ground motion prediction equations.

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