A Non-Ergodic Ground-Motion Model for California
A new approach is used in the development of a fully non-ergodic ground motion model (GMM) for pseudo-spectral accelerations (PSA). First, a non-ergodic effective Fourier amplitude spectrum (EAS) GMM is developed, and then, through random vibration theory (RVT), it is converted to a PSA non-ergodic GMM; the advantage of this two-step approach is that it can better capture the non-ergodic source, path, and site effects through the small magnitude earthquakes. Fourier transform is a linear operation, and therefore, the non-ergodic effects from the small magnitude events can be applied directly to the large magnitude earthquakes; the response spectrum is a non-linear operator, which makes the non-ergodic terms magnitude dependent, and so the small magnitude data cannot be used that easily to constrain the non-ergodic behavior of the large events.
The Bayless and Abrahamson (2019) ergodic EAS GMM is used as a backbone for the non-ergodic EAS GMM; the non-ergodic effects related to the source and site are modeled as spatially varying coefficients, and the non-ergodic effects related to the path are captured through a cell-specific anelastic attenuation. The PSA non-ergodic effects are expressed as ergodic to non-ergodic PSA ratios, which is the adjustment that needs to be applied to an ergodic PSA GMM to incorporate the non-ergodic effects. To calculate these ratios, first both the ergodic and non-ergodic EAS are calculated for a scenario of interest (M, Rrup, VS30, xeq, xsite, etc.) and then, with RVT, the equivalent PSA values are computed; this second step is the one that introduces the magnitude dependence in the non-ergodic PSA terms. This approach leads to an approximately 40% reduction in the total aleatory standard deviation compared to the Abrahamson et al. (2014) ergodic GMM. The epistemic uncertainty associated with the PSA ratios is small in areas close to stations and past events; in areas with sparse data, the mean of the non-ergodic ratios goes to zero implying ergodic scaling and the epistemic uncertainty increases.
Presenting Author: Grigorios Lavrentiadis
Student Presenter: Yes
Day: 4/21/2021
Time: 2:00 PM - 3:15 PM Pacific
Additional Authors
Grigorios Lavrentiadis Presenting Author Corresponding Author glavrent@berkeley.edu University of California, Berkeley |
Norman Abrahamson abrahamson@berkeley.edu University of California, Berkeley |
Nicolas Kuehn kuehn@ucla.edu University of California, Los Angeles |
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A Non-Ergodic Ground-Motion Model for California
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