A Referenced Empirical Ground-Motion Model for Arias Intensity and Cumulative Absolute Velocity Based on the NGA-East Database

2020 ◽  
Vol 110 (2) ◽  
pp. 508-518
Author(s):  
Ali Farhadi ◽  
Shahram Pezeshk

ABSTRACT In this study, we use the referenced empirical method of Atkinson (2008) to develop a ground-motion model (GMM) for estimating Arias intensity (IA) and cumulative absolute velocity (CAV) for the central and eastern North America. We use Campbell and Bozorgnia (2019) as the reference model. To achieve the objectives of this study, we begin with computing the geometric mean of the IA and CAV from the two as-recorded horizontal components of the motion for the recording motions in the Next Generation Attenuation-East strong-motion database. Then, we calculate the residuals of Campbell and Bozorgnia (2019) reference GMM for both IA and CAV. Next, we use the mixed-effect regression approach introduced by Abrahamson and Youngs (1992) to define adjustment factors to the Campbell and Bozorgnia (2019) model. Finally, we evaluate the proposed referenced empirical model by performing a set of residual analyses and comparing model predictions with observed data. The proposed model shows no apparent residual trend for magnitude or distance and implicitly accounts for the site term using the site factors proposed by Campbell and Bozorgnia (2019) model. The valid distance and magnitude range of the proposed model is the same as the selected reference model. In addition, we consider our new model to be applicable for time-averaged shear-wave velocity in the upper 30 m (VS30) between 150 and 2000  m/s.

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.


Author(s):  
Zach Bullock

This study proposes empirical ground motion models for a variety of non-spectral intensity measures and significant durations in New Zealand. Equations are presented for the prediction of the median and maximum rotated components of Arias intensity, cumulative absolute velocity, cumulative absolute velocity above a 5 cm/s2 acceleration threshold, peak incremental ground velocity, and the 5% to 75% and 5% to 95% significant durations. Recent research has highlighted the usefulness of these parameters in both structural and geotechnical engineering. The New Zealand Strong Motion Database provides the database for regression and includes many earthquakes from all regions of New Zealand with the exceptions of Auckland and Northland, Otago and Southland, and Taranaki. The functional forms for the proposed models are selected using cross validation. The possible influence of effects not typically included in ground motion models for these intensity measures is considered, such as hanging wall effects and basin depth effects, as well as altered attenuation in the Taupo Volcanic Zone. The selected functional forms include magnitude and rupture depth scaling, attenuation with distance, and shallow site effects. Finally, the spatial autocorrelation of the models’ within-event residuals is considered and recommendations are made for developing correlated maps of intensity predictions stochastically.


2012 ◽  
Vol 28 (3) ◽  
pp. 931-941 ◽  
Author(s):  
Kenneth W. Campbell ◽  
Yousef Bozorgnia

Arias intensity (AI) and cumulative absolute velocity (CAV) have been proposed as instrumental intensity measures that can incorporate the cumulative effects of ground motion duration and intensity on the response of structural and geotechnical systems. In this study, we have developed a ground motion prediction equation (GMPE) for the horizontal component of AI in order to compare its predictability to a similar GMPE for CAV. Both GMPEs were developed using the same strong motion database and functional form in order to eliminate any bias these factors might cause in the comparison. This comparison shows that AI exhibits significantly greater amplitude scaling and aleatory uncertainty than CAV. The smaller standard deviation and less sensitivity to amplitude suggests that CAV is more predictable than AI and should be considered as an alternative to AI in engineering and geotechnical applications where the latter intensity measure is traditionally used.


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.


2008 ◽  
Vol 24 (1) ◽  
pp. 139-171 ◽  
Author(s):  
Kenneth W. Campbell ◽  
Yousef Bozorgnia

We present a new empirical ground motion model for PGA, PGV, PGD and 5% damped linear elastic response spectra for periods ranging from 0.01–10 s. The model was developed as part of the PEER Next Generation Attenuation (NGA) project. We used a subset of the PEER NGA database for which we excluded recordings and earthquakes that were believed to be inappropriate for estimating free-field ground motions from shallow earthquake mainshocks in active tectonic regimes. We developed relations for both the median and standard deviation of the geometric mean horizontal component of ground motion that we consider to be valid for magnitudes ranging from 4.0 up to 7.5–8.5 (depending on fault mechanism) and distances ranging from 0–200 km. The model explicitly includes the effects of magnitude saturation, magnitude-dependent attenuation, style of faulting, rupture depth, hanging-wall geometry, linear and nonlinear site response, 3-D basin response, and inter-event and intra-event variability. Soil nonlinearity causes the intra-event standard deviation to depend on the amplitude of PGA on reference rock rather than on magnitude, which leads to a decrease in aleatory uncertainty at high levels of ground shaking for sites located on soil.


Author(s):  
Li Xuejing ◽  
Weijin Xu ◽  
Mengtan Gao

ABSTRACT Arias intensity (IA), as an important seismic parameter, which contains the information of amplitude, frequencies, and duration of ground motion, plays a crucial role in characterizing seismic hazard such as earthquake-induced landslides. In this article, we conducted probabilistic seismic hazard analysis (PSHA) based on IA in China’s north–south seismic belt. We adopted the seismic sources and seismicity parameters used in the fifth generation of the Seismic Ground Motion Parameter Zoning Map of China, and two ground-motion model of IA. The results show that the values of IA are greater than 0.11 m/s in most regions of the north–south seismic belt. The provincial capital cities and most prefecture-level cities in the seismic zone are located in the region with IA-values greater than 0.32 m/s. The values of IA are above 0.54 m/s in the region around the main fault zone. This means that the north–south seismic belt is prone to extremely high-seismic hazard, particularly earthquake-induced landslides. Therefore, it is important to strengthen the evaluation and prevention of earthquake-induced landslides in this area. As we have found significant differences in the values of IA calculated from different ground-motion model, it is necessary to study the ground-motion model of IA for the western geological environment of China. In addition, the PSHA based on IA gives more consideration to the influence of large earthquakes than that based on peak ground acceleration. Therefore, IA plays an important role in seismic design of major engineering projects. The results of this article are of great scientific significance for understanding the seismic hazard of the north–south seismic belt.


2019 ◽  
Vol 35 (3) ◽  
pp. 1289-1310 ◽  
Author(s):  
Kenneth W. Campbell ◽  
Yousef Bozorgnia

We updated our Next Generation Attenuation (NGA)-West1 ground motion models (GMMs) for the horizontal components of Arias intensity (AI) and cumulative absolute velocity (CAV) using the functional form and NGA-West2 database we used to develop GMMs for peak-amplitude and peak-spectral ground motion intensity measures (GMIMs). Our results show that CAV has the best goodness-of-fit statistics of all the GMIMs we have evaluated up to this time. Its relatively small between- and within-event standard deviations confirm its superior predictability. On the other hand, AI has the highest standard deviation of any GMIM we have studied thus far, which is approximately double that of CAV. Although either CAV or AI or a combination of both have been shown to meet various performance metrics proposed in the context of performance-based earthquake engineering (PBEE), CAV's high level of predictability makes it superior to AI for use in engineering applications, such as PBEE, that involve probabilistic inference.


2016 ◽  
Vol 32 (2) ◽  
pp. 1033-1054 ◽  
Author(s):  
Manisha Rai ◽  
Adrian Rodriguez-Marek ◽  
Alan Yong

We develop a model to predict the effects of topography on earthquake ground motions using a database of small- to medium-magnitude earthquakes from California. The proposed model relies on a parameter called relative elevation that quantifies topography using the elevation of a site relative to its surroundings. We also investigate an alternative parameterization of topography called smoothed curvature. We study the bias in the residuals from the Chiou et al. (2010) ground motion model with respect to these parameters and fit a model to remedy those biases. We then compare these models by assessing their goodness of fit to the data. The proposed model for topographic effects is intended as a correction to the Chiou et al. (2010) small- to medium-magnitude earthquake prediction model.


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