scholarly journals GROUND MOTION PREDICTION EQUATION OF THE SEISMIC INTENSITY MEASURE TO EVALUATE STRUCTURAL DAMAGE TO HOUSES AND BUILDINGS FOR CRUSTAL EARTHQUAKES IN JAPAN

2020 ◽  
Vol 85 (770) ◽  
pp. 475-484
Author(s):  
Kensuke ARAI ◽  
Yuki SAKAI
Keyword(s):  
Ground Motion ◽  
Structural Damage ◽  
Prediction Equation ◽  
Seismic Intensity ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction ◽  
Intensity Measure ◽  
Crustal Earthquakes

Ground motion prediction equation for crustal earthquakes in Taiwan

2020 ◽  
Vol 36 (4) ◽  
pp. 2129-2164
Author(s):  
Van-Bang Phung ◽  
Chin Hsiung Loh ◽  
Shu Hsien Chao ◽  
Brian SJ Chiou ◽  
Bor-Shouh Huang
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Functional Form ◽  
Hazard Analysis ◽  
Prediction Equation ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction ◽  
Crustal Earthquakes ◽  
Magnitude Scaling

We develop a ground motion prediction equation (GMPE) for estimating horizontal ground motion amplitudes caused by crustal earthquakes, based on an integrated data set that includes strong motion recordings mainly from Taiwan earthquakes and only from large magnitude earthquakes in the NGA-West2 database. This GMPE is developed for probabilistic seismic hazard analysis study, which is introduced as a part of Taiwan Senior Seismic Hazard Analysis Committee Level 3 projects. The functional form developed by Chiou and Youngs was carefully studied to determine the key modeling parameters needed to regress against ground motion in the target region. Using this functional form, the GMPE achieves considerable improvement over previously developed Taiwan GMPEs. In particular, the use of a high-order function in magnitude scaling enables representation of the saturation effects of large earthquakes. Moreover, consideration of focal mechanisms, depth effects, and dip effects are used to correct the magnitude scaling; consideration of nonlinear site amplification is conditioned on VS30 and reference ground motion on rock; and consideration of basin depth effect is a function of Z1.0 in correlation with VS30. In addition, ground motion data used in this study are not only expanded by more than three times as many earthquakes and records compared with a previous Taiwan model but also provide the metadata of these records that were not available or were previously incomplete. In this study, we compare the proposed model with the NGA-West2 models and discuss the regional difference in ground motion in terms of spectral shape, magnitude scaling, distance scaling, depth scaling, style of faulting, and site effects. We provide median and single standard deviations of peak ground acceleration and 5% damped pseudospectral acceleration response ordinates of the orientation-independent average horizontal component of ground motion (RotD50) for the spectral period of 0.01–10 s.

A New Ground Motion Prediction Equation for Japan Applicable up to M9 Mega-Earthquake

2013 ◽  
Vol 8 (5) ◽  
pp. 878-888 ◽  
Author(s):  
Nobuyuki Morikawa ◽  
◽  
Hiroyuki Fujiwara
Keyword(s):  
Ground Motion ◽  
Strong Motion ◽  
Prediction Equation ◽  
Seismic Intensity ◽  
Moment Magnitude ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction ◽  
The Moment ◽  
Complete Amplitude

In this study we suggest a new ground motion prediction equation applicable up to the moment magnitude 9 using the strong motion records from the 2011 Tohoku-oki earthquake. We determined a base model with moment magnitude and the shortest distance from the source fault as parameters. In order to avoid overestimating amplitude atmagnitude larger than 8, we examined two models – a quadratic magnitude term and a linear magnitude term with a complete amplitude saturation term at someMw. We then adopt additional correction terms corresponding to amplification by deep sediments or shallow soft soils, and anomalous seismic intensity distribution in order to improve prediction.

A Ground-Motion Prediction Equation for the Western and the Southwestern Parts of China Based on Local Strong-Motion Records and an Overseas Reference Model for the Vertical Component

2021 ◽  
Author(s):  
Hao Xing ◽  
John X. Zhao
Keyword(s):  
Ground Motion ◽  
Earthquake Engineering ◽  
Reference Model ◽  
Prediction Equation ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction ◽  
Magnitude Scaling ◽  
The Absolute ◽  
Standard Deviations

ABSTRACT A ground-motion prediction equation for the vertical ground motions from the western and the southwestern parts of China (referred to as SWC) is presented in this study. Based on the Xing and Zhao (2021) study, the Zhao et al. (2017) model (referred to as ZHAO2017) for the shallow crustal earthquakes in Japan was used as the reference model. We used a bilinear magnitude-scaling function hinged at a moment magnitude (Mw) of 7.1. The magnitude-scaling rate for events with Mw>7.1 was determined by records from the SWC dataset and the large events in the Pacific Earthquake Engineering Research Center Next Generation Attenuation-West2 dataset. Site classes (SCs) were used as the site response proxy. All other parameters were derived from the SWC dataset only. The magnitude-scaling rates for events with Mw≤7.1 in this study are larger than in the ZHAO2017 model at most periods. The absolute values of the geometric attenuation rates are larger, and the absolute values of the anelastic attenuation rates are smaller than in the ZHAO2017 model. The between-event standard deviations are smaller than in the ZHAO2017 model at short periods, and the within-event standard deviations are larger than in the ZHAO2017 model at all periods. The differences in the between-site standard deviations vary significantly from one SC to another. We also find that the between-event and within-event residuals are almost independent of magnitude and source distance. The response spectrum attenuates less rapidly than in the ZHAO2017 model at distances less than 30 km.

scholarly journals A New Approach to Estimate a Mixed Model–Based Ground Motion Prediction Equation

2007 ◽  
Vol 23 (3) ◽  
pp. 665-684 ◽  
Author(s):  
Behrooz Tavakoli ◽  
Shahram Pezeshk
Keyword(s):  
Ground Motion ◽  
Mixed Model ◽  
Prediction Equation ◽  
Regression Coefficients ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Predictive Equation ◽  
Ground Motion Prediction ◽  
Data Set ◽  
Motion Data

A derivative-free approach based on a hybrid genetic algorithm (HGA) is proposed to estimate a mixed model–based ground motion prediction equation (attenuation relationship) with several variance components. First, a simplex search algorithm (SSA) is used to reduce the search domain to improve the convergence speed. Then, a genetic algorithm (GA) is employed to obtain the regression coefficients and the uncertainties of a predictive equation in a unified framework using one-stage maximum-likelihood estimation. The proposed HGA results in a predictive equation that best fits a given ground motion data set. The proposed HGA is able to handle changes in the functional form of the equation. To demonstrate the solution quality of the proposed HGA, the regression coefficients and the uncertainties of a test function based on a simulated ground motion data set are obtained. Then, the proposed HGA is applied to fit two functional attenuation forms to an actual data set of ground motion. For illustration, the results of the HGA are compared with those used by previous conventional methods. The results indicate that the HGA is an appropriate algorithm to overcome the shortcomings of the previous methods and to provide reliable and stable solutions.

Ground‐Motion Prediction Equation for the Chilean Subduction Zone

2017 ◽  
Vol 107 (2) ◽  
pp. 901-911 ◽  
Author(s):  
Gonzalo A. Montalva ◽  
Nicolás Bastías ◽  
Adrian Rodriguez‐Marek
Keyword(s):  
Subduction Zone ◽  
Ground Motion ◽  
Prediction Equation ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction
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