scholarly journals Developing an Application‐Specific Ground‐Motion Model for Induced Seismicity

2015 ◽  
Vol 106 (1) ◽  
pp. 158-173 ◽  
Author(s):  
Julian J. Bommer ◽  
Bernard Dost ◽  
Benjamin Edwards ◽  
Peter J. Stafford ◽  
Jan van Elk ◽  
...  
2019 ◽  
Vol 35 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Georgios Zalachoris ◽  
Ellen M. Rathje

A ground motion model (GMM) tuned to the characteristics of the observed, and potentially induced, seismicity in Texas, Oklahoma, and Kansas is developed using a database of 4,528 ground motions recorded during 376 events of Mw > 3.0 in the region. The GMM is derived using the referenced empirical approach with an existing Central and Eastern North America model as the reference GMM and is applicable for Mw = 3.0–5.8 and hypocentral distances less than 500 km. The proposed model incorporates weaker magnitude scaling than the reference GMM for periods less than about 1.0 s, resulting in smaller predicted ground motions at larger magnitudes. The proposed model predicts larger response spectral accelerations at short hypocentral distances (≤20 km), which is likely because of the shallow hypocenters of events in Texas, Oklahoma, and Kansas. Finally, the VS30 scaling for the newly developed model predicts less amplification at VS30 < 600 m/s than the reference GMM, which is likely because of the generally thinner sediments in the study area. This finding is consistent with recent studies regarding site amplification in Central and Eastern North America.


2018 ◽  
Vol 17 (8) ◽  
pp. 4441-4456 ◽  
Author(s):  
B. Edwards ◽  
B. Zurek ◽  
E. van Dedem ◽  
P. J. Stafford ◽  
S. Oates ◽  
...  

Author(s):  
Fabio Sabetta ◽  
Antonio Pugliese ◽  
Gabriele Fiorentino ◽  
Giovanni Lanzano ◽  
Lucia Luzi

AbstractThis work presents an up-to-date model for the simulation of non-stationary ground motions, including several novelties compared to the original study of Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996). The selection of the input motion in the framework of earthquake engineering has become progressively more important with the growing use of nonlinear dynamic analyses. Regardless of the increasing availability of large strong motion databases, ground motion records are not always available for a given earthquake scenario and site condition, requiring the adoption of simulated time series. Among the different techniques for the generation of ground motion records, we focused on the methods based on stochastic simulations, considering the time- frequency decomposition of the seismic ground motion. We updated the non-stationary stochastic model initially developed in Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996) and later modified by Pousse et al. (Bull Seism Soc Am 96:2103–2117, 2006) and Laurendeau et al. (Nonstationary stochastic simulation of strong ground-motion time histories: application to the Japanese database. 15 WCEE Lisbon, 2012). The model is based on the S-transform that implicitly considers both the amplitude and frequency modulation. The four model parameters required for the simulation are: Arias intensity, significant duration, central frequency, and frequency bandwidth. They were obtained from an empirical ground motion model calibrated using the accelerometric records included in the updated Italian strong-motion database ITACA. The simulated accelerograms show a good match with the ground motion model prediction of several amplitude and frequency measures, such as Arias intensity, peak acceleration, peak velocity, Fourier spectra, and response spectra.


2021 ◽  
Author(s):  
Grigorios Lavrentiadis ◽  
Norman A. Abrahamson ◽  
Nicolas M. Kuehn

Abstract A new non-ergodic ground-motion model (GMM) for effective amplitude spectral (EAS) values for California is presented in this study. EAS, which is defined in Goulet et al. (2018), is a smoothed rotation-independent Fourier amplitude spectrum of the two horizontal components of an acceleration time history. The main motivation for developing a non-ergodic EAS GMM, rather than a spectral acceleration GMM, is that the scaling of EAS does not depend on spectral shape, and therefore, the more frequent small magnitude events can be used in the estimation of the non-ergodic terms. The model is developed using the California subset of the NGAWest2 dataset Ancheta et al. (2013). The Bayless and Abrahamson (2019b) (BA18) ergodic EAS GMM was used as backbone to constrain the average source, path, and site scaling. The non-ergodic GMM is formulated as a Bayesian hierarchical model: the non-ergodic source and site terms are modeled as spatially varying coefficients following the approach of Landwehr et al. (2016), and the non-ergodic path effects are captured by the cell-specific anelastic attenuation attenuation following the approach of Dawood and Rodriguez-Marek (2013). Close to stations and past events, the mean values of the non-ergodic terms deviate from zero to capture the systematic effects and their epistemic uncertainty is small. In areas with sparse data, the epistemic uncertainty of the non-ergodic terms is large, as the systematic effects cannot be determined. The non-ergodic total aleatory standard deviation is approximately 30 to 40% smaller than the total aleatory standard deviation of BA18. This reduction in the aleatory variability has a significant impact on hazard calculations at large return periods. The epistemic uncertainty of the ground motion predictions is small in areas close to stations and past event.


2019 ◽  
Vol 18 (1) ◽  
pp. 57-76 ◽  
Author(s):  
Giovanni Lanzano ◽  
Lucia Luzi

2019 ◽  
Vol 17 (6) ◽  
pp. 2871-2898 ◽  
Author(s):  
Alexandra Tsioulou ◽  
Alexandros A. Taflanidis ◽  
Carmine Galasso

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