Seismic Ground Motion Model

2020 ◽  
pp. 25-44
Author(s):  
Jie Li ◽  
Wei Liu
Keyword(s):  
Ground Motion ◽  
Motion Model ◽  
Seismic Ground Motion ◽  
Ground Motion Model

A New Non-Stationary Stochastic Seismic Ground Motion Model and its Application

2011 ◽  
Vol 243-249 ◽  
pp. 4627-4633
Author(s):  
Zhi Hua Wang ◽  
Chong Shi Gu
Keyword(s):  
Seismic Response ◽  
Ground Motion ◽  
Analysis Procedure ◽  
Response Analysis ◽  
Model Parameters ◽  
Motion Model ◽  
Seismic Response Analysis ◽  
Seismic Ground Motion ◽  
Ground Motion Model ◽  
Stochastic Seismic Response

Considering the uncertainty and the time variation of frequency contents of real seismic excitation, a new versatile stochastic strong ground motion model named general stochastic seismic ground motion (GSSGM) model is presented in this paper. Some essential assumptions for the earthquake process used in this paper are first given. The intensity and energy of the target seismic ground motion are used to determine the model parameters. The frequency contents are demanded to be agreed with the main characteristics of the target ground motions. The GSSGM model is appropriate to simulate the stationary, intensity non-stationary and fully non-stationary stochastic processes. Additionally, a simple non-stationary stochastic seismic response analysis procedure based on the GSSGM model and the pseudo excitation theory is put forward. The presented non-stationary stochastic seismic response analysis procedure is later applied in the seismic response analysis of a real homogeneous earth dam. The non-stationary analysis results display the effects of non-stationarity on the seismic response of the dam and reflect the main phenomena of dynamic embankment-foundation interaction. The results indicate that the GSSGM model and the presented analysis procedure are effective.

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

2021 ◽  
Author(s):  
Fabio Sabetta ◽  
Antonio Pugliese ◽  
Gabriele Fiorentino ◽  
Giovanni Lanzano ◽  
Lucia Luzi
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Strong Motion ◽  
Stochastic Simulations ◽  
Model Parameters ◽  
Motion Model ◽  
Arias Intensity ◽  
Time Frequency ◽  
Ground Motion Model ◽  
Ground Motion Records

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.

scholarly journals A Non-Ergodic Effective Amplitude Ground-Motion Model for California

2021 ◽  
Author(s):  
Grigorios Lavrentiadis ◽  
Norman A. Abrahamson ◽  
Nicolas M. Kuehn
Keyword(s):  
Standard Deviation ◽  
Ground Motion ◽  
Epistemic Uncertainty ◽  
Amplitude Spectrum ◽  
Time History ◽  
Motion Model ◽  
Small Magnitude ◽  
Varying Coefficients ◽  
Ground Motion Model ◽  
Systematic Effects

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.

A ground motion model for volcanic areas in Italy

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

scholarly journals Validation of stochastic ground motion model modification by comparison to seismic demand of recorded ground motions

2019 ◽  
Vol 17 (6) ◽  
pp. 2871-2898 ◽  
Author(s):  
Alexandra Tsioulou ◽  
Alexandros A. Taflanidis ◽  
Carmine Galasso
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Seismic Demand ◽  
Motion Model ◽  
Model Modification ◽  
Ground Motion Model

Conditional Ground-Motion Model for Damaging Characteristics of Near-Fault Ground Motions Based on Instantaneous Power

2020 ◽  
Vol 110 (6) ◽  
pp. 2828-2842
Author(s):  
Esra Zengin ◽  
Norman Abrahamson
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Accurate Estimation ◽  
Spectral Acceleration ◽  
Motion Model ◽  
Velocity Pulse ◽  
Near Fault ◽  
Instantaneous Power ◽  
Ground Motion Model ◽  
Short Time

ABSTRACT The velocity pulse in near-fault ground motions has been used as a key characteristic of damaging ground motions. Characterization of the velocity pulse involves three parameters: presence of the pulse, period of the pulse, and amplitude of the pulse. The basic concept behind the velocity pulse is that a large amount of seismic energy is packed into a short time, leading to larger demands on the structure. An intensity measure for near-fault ground motions, which is a direct measure of the amount of energy arriving in short time, called instantaneous power (IP (T1)), is defined as the maximum power of the bandpass-filtered velocity time series measured over a time interval of 0.5T1, in which T1 is the fundamental period of the structure. The records are bandpass filtered in the period band (0.2T1−3T1) to remove the frequencies that are not expected to excite the structure. Zengin and Abrahamson (2020) showed that the drift is better correlated with the IP (T1) than with the velocity pulse parameters for records scaled to the same spectral acceleration at T1. A conditional ground-motion model (GMM) for the IP is developed based on the 5%-damped spectral acceleration at T1, the earthquake magnitude, and the rupture distance. This conditional GMM can be used for record selection for near-fault ground motions that captures the key features of velocity pulses and can lead to a better representation of the median and variability of the maximum interstory drift. The conditional GMM can also be used in a vector hazard analysis for spectral acceleration (T1) and IP (T1) that can be used for more accurate estimation of drift hazard and seismic risk.

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