scholarly journals A regionally adaptable ground-motion model for fourier amplitude spectra of shallow crustal earthquakes in Europe

Author(s):  
Sreeram Reddy Kotha ◽  
Dino Bindi ◽  
Fabrice Cotton
2019 ◽  
Vol 109 (5) ◽  
pp. 2088-2105 ◽  
Author(s):  
Jeff Bayless ◽  
Norman A. Abrahamson

Abstract We present a summary of the Bayless and Abrahamson (2018b) empirical ground‐motion model (GMM) for shallow crustal earthquakes in California based on the Next Generation Attenuation‐West2 database (Ancheta et al., 2014). This model is denoted as BA18. Rather than the traditional response spectrum GMM, BA18 is developed for the smoothed effective amplitude spectrum (EAS), as defined by the Pacific Earthquake Engineering Research Center (Goulet et al., 2018). The EAS is the orientation‐independent horizontal‐component Fourier amplitude spectrum of ground acceleration. The model is developed using a database dominated by California earthquakes but takes advantage of crustal earthquake data worldwide to constrain the magnitude scaling and geometric spreading. The near‐fault saturation is guided by finite‐fault numerical simulations, and nonlinear site amplification is incorporated using a modified version of Hashash et al. (2018). The model is applicable for rupture distances of 0–300 km, M 3.0–8.0, and over the frequency range 0.1–100 Hz. The model is considered applicable for VS30 in the range 180–1500  m/s, although it is not well constrained for VS30 values >1000  m/s. Models for the median and the aleatory variability of the EAS are developed. Regional models for Japan and Taiwan will be developed in a future update of the model. A MATLAB program that implements the EAS GMM is provided in the Ⓔ supplemental content to this article.


2020 ◽  
Vol 18 (9) ◽  
pp. 4091-4125 ◽  
Author(s):  
Sreeram Reddy Kotha ◽  
Graeme Weatherill ◽  
Dino Bindi ◽  
Fabrice Cotton

2016 ◽  
Vol 32 (2) ◽  
pp. 979-1004 ◽  
Author(s):  
Yousef Bozorgnia ◽  
Kenneth W. Campbell

We summarize the development of the NGA-West2 Bozorgnia-Campbell empirical ground motion model (GMM) for the vertical components of peak ground acceleration (PGA), peak ground velocity (PGV), and 5%-damped elastic pseudo-absolute acceleration response spectra (PSA) at vertical periods ranging from 0.01 s to 10 s. In the development of the vertical GMM, similar to our 2014 horizontal GMM, we used the extensive PEER NGA-West2 worldwide database. We consider our new vertical GMM to be valid for shallow crustal earthquakes in active tectonic regions for magnitudes ranging from 3.3 to 7.5–8.5, depending on the style of faulting, and for distances as far as 300 km from the fault.


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

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