Simulation of non-stationary stochastic ground motions based on recent Italian earthquakes

Fabio Sabetta,Antonio Pugliese,Giovanni Lanzano,Gabriele Fiorentino,Lucia Luzi

doi:10.1007/s10518-021-01077-1

Abstract

This 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.

Highlights

With the increase of computational power and the advent of performance-based earthquake engineering, nonlinear dynamic analyses in the time domain are more often employed for the seismic assessment of new and existing civil constructions, including strategic and base-isolated structures, high ductility and irregular structures, coupled soil-structure systems
The simulated time series depend on few input parameters: moment magnitude, source to site distance, shear wave velocity at the site, and style of faulting
The same dataset has been used to derive the predictive equations for the most relevant parameters required for the time series simulation proposed in this study: Arias intensity and significant duration

Summary

Introduction

With the increase of computational power and the advent of performance-based earthquake engineering, nonlinear dynamic analyses in the time domain are more often employed for the seismic assessment of new and existing civil constructions, including strategic and base-isolated structures, high ductility and irregular structures, coupled soil-structure systems. The simulated ground motions must be compatible with a given design response spectrum and the assumed earthquake scenario, usually described in terms of magnitude, distance, site geological conditions and focal mechanism. The filtering and windowing of white noise, as the classic stochastic stationary procedure of SIMQKE (Gasparini and Vanmarcke 1976) and the analysis of the nonlinear dynamic response in the Kanai-Tajimi model (Kanai 1961; Lin and Yong 1987) were used in the past. These methods, based on the random-vibration theory (Boore and Joyner 1984), provide accelerograms whose response spectra match the target spectrum. The main weakness of this kind of approach is that the time series are stationary in frequency and completely unrelated to any geophysical parameter

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