New fuzzy method in choosing Ground Motion Prediction Equation (GMPE) in probabilistic seismic hazard analysis

2016 ◽  
Vol 10 (2) ◽  
pp. 389-408 ◽  
Author(s):  
Mostafa Mahmoudi ◽  
MohsenAli Shayanfar ◽  
Mohammad Ali Barkhordari ◽  
Ehsan Jahani
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Hazard Analysis ◽  
Prediction Equation ◽  
Seismic Hazard Analysis ◽  
Motion Prediction ◽  
Probabilistic Seismic Hazard ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction ◽  
Fuzzy Method

A ground motion based procedure to identify the earthquakes that are the most relevant for probabilistic seismic hazard analysis

2021 ◽  
pp. 875529302098198
Author(s):  
John G Anderson ◽  
Fabrice Cotton ◽  
Dino Bindi
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Time Window ◽  
Hazard Analysis ◽  
Prediction Equation ◽  
Seismic Hazard Analysis ◽  
Motion Prediction ◽  
Probabilistic Seismic Hazard ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction

A method is proposed to identify within seismic catalogs those earthquakes that are most relevant to the seismic hazard. The approach contrasts with the classical approach to decluster the seismic catalog with the expectation that the remaining main shocks will be the relevant events for the seismic hazard analysis. We apply a time window like in the window declustering approach of Gardner and Knopoff, but the time window is motivated by relevance to engineering. A ground motion criterion replaces the spatial window. An event in the time window is included in the “Maximum Shaking Earthquake Catalog (MSEQ catalog)” if the median ground motion at its epicenter exceeds the predicted median ground motion there from the main shock, using a locally appropriate ground motion prediction equation. Ground motion can be measured by any parameter that is estimated by a ground motion prediction equation. We consider peak acceleration and spectral amplitude (SA) at periods of 0.2, 1.0, and 3.0 s. The longer period parameters systematically remove more small events. The purpose is not to produce a declustered catalog, in which each group of physically related earthquakes is represented by its largest event. Statistical properties of the MSEQ catalog somewhat resemble the corresponding declustered catalog in three tested regions, but the MSEQ catalogs all retain more large-magnitude earthquakes. The MSEQ catalog may better represent the potential hazard in a region, and thus might be considered as an alternative to a declustered catalog in developing the seismicity model for probabilistic seismic hazard analysis.

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.

On the Forecasting of Ground-Motion Parameters for Probabilistic Seismic Hazard Analysis

2011 ◽  
Vol 27 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Danny Arroyo ◽  
Mario Ordaz
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Prediction Models ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Motion Prediction ◽  
Probabilistic Seismic Hazard ◽  
Ground Motion Prediction ◽  
Data Set

It is well understood that the range of application for an empirical ground-motion prediction model is constrained by the range of predictor variables covered in the data used in the analysis. However, in probabilistic seismic hazard analysis (PSHA), the limits in the application of ground-motion prediction models (GMPMs) are often ignored, and the empirical relationships are extrapolated. In this paper, we show that this extrapolation leads to a quantifiable increment in the uncertainty of a GMPM when it is used to forecast a future value of a given intensity parameter. This increment, which is clearly of epistemic nature, depends on the adopted functional form, on the covariance matrix of the regression coefficients, on the used regression technique, and on the quality of the data set. In addition, through some examples using the database of the Next Generation of Ground-Motion Attenuation Models project and some currently favored functional forms we study the increment in the seismic hazard produced by the extrapolation of GMPMs.

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