scholarly journals A Region-Specific Ground-Motion Model for Inelastic Spectral Displacement in Northern Italy Considering Spatial Correlation Properties

2021 ◽  
Author(s):  
Chen Huang ◽  
Karim Tarbali ◽  
Carmine Galasso
Keyword(s):  
Spatial Correlation ◽  
Ground Motion ◽  
Northern Italy ◽  
Model Parameters ◽  
Motion Model ◽  
Practical Applications ◽  
Ground Motion Model ◽  
Engineered Systems ◽  
Ground Motion Records ◽  
Correlation Properties

Abstract The peak inelastic displacement of single-degree-of-freedom bilinear systems (Sdi) is an effective intensity measure linking ground-motion features to the inelastic response and subsequent structural and nonstructural damage of engineered systems. This study develops a region-specific ground-motion model for Sdi considering source, path, and site effects and explicitly accounting for the spatial correlation between intraevent residuals when the model parameters are estimated. The model is developed based on 2427 two-component horizontal ground-motion records from 85 events in northern Italy with magnitudes ranging from 4.0 to 6.4 and source-to-site distances less than 200 km. An exponential stationary and isotropic model is considered to represent the spatial correlation properties of Sdi (after scrutinizing the appropriateness of the underlying assumptions for such a model). Comparisons are performed with existing models in the literature in terms of Sdi estimates, as well as the (spatial correlation) effective range parameter. Two practical applications of the developed model are presented: one on estimating the spatial distribution of Sdi (as an essential ingredient for seismic loss assessments) and one on the engineering validation of region-specific ground-motion simulations. Challenges regarding such validations are also discussed.

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 Simulation of seismic ground motion fields via object-oriented spatial statistics with an application in Northern Italy

2020 ◽  
Vol 34 (10) ◽  
pp. 1607-1627
Author(s):  
Alessandra Menafoglio ◽  
Sara Sgobba ◽  
Giovanni Lanzano ◽  
Francesca Pacor
Keyword(s):  
Ground Motion ◽  
Spatial Statistics ◽  
Functional Model ◽  
Object Oriented ◽  
Northern Italy ◽  
Motion Patterns ◽  
Ground Motion Model ◽  
Systematic Effects ◽  
Ground Motion Records ◽  
Physical Features

Abstract This work offers a novel methodological framework to address the problem of generating data-driven earthquake shaking fields at different vibration periods, which are key to support decision making and civil protection planning. We propose to analyse the entire profiles of spectral accelerations and project their information content to unsampled locations in the system, based on the theory of Object Oriented Spatial Statistics. The proposed methodology combines a non-ergodic ground motion model with a fully functional model for the residual term, the latter consisting of (i) the spatially-varying systematic effects due to source, site and path, and (ii) the remaining aleatory error. The proposed methodology allows to generate multiple shaking scenarios conditioned on the data, jointly and consistently for all the vibration periods, overcoming the intrinsic limitations of existing multivariate approaches to the problem. The approach is tested on a vast dataset of ground motion records collected in the study-area of the Po Plain (Northern Italy), for which a region-specific fully non-ergodic GMM was previously calibrated. Our validation tests demonstrate the potentiality of the approach, which is capable to effectively simulate spectral acceleration profiles, while keeping the ability to capture the main physical features of ground motion patterns in the region.

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 Ground-motion relations for eastern North America

1995 ◽  
Vol 85 (1) ◽  
pp. 17-30 ◽  
Author(s):  
Gail M. Atkinson ◽  
David M. Boore
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Response Spectra ◽  
Model Parameters ◽  
Eastern North America ◽  
Motion Model ◽  
Ground Acceleration ◽  
Ground Motion Model ◽  
Definition Of ◽  
Validation Of Results

Abstract Predictive relations are developed for ground motions from eastern North American earthquakes of 4.0 ≦ M ≦ 7.25 at distances of 10 ≦ R ≦ 500 km. The predicted parameters are response spectra at frequencies of 0.5 to 20 Hz, and peak ground acceleration and velocity. The predictions are derived from an empirically based stochastic ground-motion model. The relations differ from previous work in the improved empirical definition of input parameters and empirical validation of results. The relations are in demonstrable agreement with ground motions from earthquakes of M 4 to 5. There are insufficient data to adequately judge the relations at larger magnitudes, although they are consistent with data from the Saguenay (M 5.8) and Nahanni (M 6.8) earthquakes. The underlying model parameters are constrained by empirical data for events as large as M 6.8.

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.

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