Towards fully data driven ground-motion prediction models for Europe

2013 ◽  
Vol 12 (1) ◽  
pp. 495-516 ◽  
Author(s):  
Boumédiène Derras ◽  
Pierre Yves Bard ◽  
Fabrice Cotton
Keyword(s):  
Ground Motion ◽  
Prediction Models ◽  
Data Driven ◽  
Motion Prediction ◽  
Ground Motion Prediction

Non-isotropic and Isotropic Ground Motion Prediction Models

2019 ◽  
Vol 177 (2) ◽  
pp. 801-819
Author(s):  
Saman Yaghmaei-Sabegh ◽  
Mehdi Ebrahimi-Aghabagher
Keyword(s):  
Ground Motion ◽  
Prediction Models ◽  
Motion Prediction ◽  
Ground Motion Prediction

Ground-motion prediction models evoked by seismicity in the Upper Silesia Coal Basin, Poland, the review with case studies

2020 ◽  
Vol 224 (2) ◽  
pp. 1381-1403
Author(s):  
Maciej J Mendecki ◽  
Judyta Odrobińska ◽  
Renata Patyńśka ◽  
Adam F Idziak
Keyword(s):  
Ground Motion ◽  
Regression Models ◽  
Prediction Models ◽  
Motion Prediction ◽  
Model Parameters ◽  
Ground Motion Prediction ◽  
Coal Basin ◽  
Upper Silesia ◽  
Regression Parameters ◽  
The Impact

SUMMARY This paper presents the results of new research on ground-motion relations from three areas in the Upper Silesia Coal Basin (USCB) in Poland and compares them with of ground-motion relations. These three mining areas of the USCB were investigated in order to better predict ground motion caused by seismic events. The study focused on variations in regression parameters and predicted PGA (peak ground acceleration) for different areas to better understand the influence of geology. To compare our results to previous models we had to unify the known ground-motion prediction equations (GMPE). Then, we used various regression models to predict the corresponding PGA values of a relatively strong USCB seismic event with an energy level of 108 J (ML = 3.3) and compared their results. The regression model parameters were compared to each other, particularly those related to energy and distance, which corresponds to a geometrical scattering (attenuation) of seismic waves as well as the influence of wave type (body or surface). Finally, building upon several established regression models, our analysis showed a strong linear correlation between two regression parameters corresponding to energy and distance. However, an open question remains whether this relation can be explained by physics, or, from a mathematical point of view, it is the effect of linear dependence of matrix vectors logE and logR. A comparison of different GMPEs allows for better verification of knowledge about the impact of tremors on ground motion in the USCB.

Watts Bar Nuclear Power Plant Strong-Motion Records of the 12 December 2018 M 4.4 Decatur, Tennessee, Earthquake

2020 ◽  
Vol 91 (3) ◽  
pp. 1579-1592 ◽  
Author(s):  
Vladimir Graizer ◽  
Dogan Seber ◽  
Scott Stovall
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Ground Motion ◽  
Nuclear Power ◽  
Prediction Models ◽  
Ground Motions ◽  
Strong Motion ◽  
Motion Prediction ◽  
Ground Motion Prediction ◽  
Digital Recordings

Abstract The moment magnitude M 4.4 on 12 December 2018 Decatur, Tennessee, earthquake occurred in the eastern Tennessee seismic zone. Although the causative fault is not known, the earthquake had a predominantly strike-slip mechanism with an estimated hypocentral depth of about 8 km. It was felt over a distance of 500 km stretching from Southern Kentucky to Georgia. Strong shaking, capable of causing slight damage, was reported near the epicenter. The Watts Bar nuclear power plant (NPP) is only 4.9 km from the epicenter of the earthquake and experienced only slight shaking. The earthquake was recorded by the plant’s seismic strong-motion instrumentation installed at four different locations. Near-real-time calculations by the plant operators indicated that the operating basis earthquake (OBE) ground motion was not exceeded during the earthquake. We obtained and processed the recorded motions to calculate corrected accelerations, velocities, and displacements. In addition, we computed the Fourier and 5% damped response spectra to compare them with the plant’s OBE. Comparisons of the ground-motion prediction models with the digital recordings at the plant site indicated that recorded ground motions were significantly below the predicted results calculated using the ground-motion prediction models approved for regulatory use. Availability of high-quality, digital recordings in this case helped make a quick decision about the ground motions not exceeding the OBE and hence prevented unnecessary shutdown of the NPP. Availability of earthquake recordings from the four locations in the NPP also presented an opportunity to analyze the linear response of plant structures.

The Variability of Ground-Motion Prediction Models and Its Components

2010 ◽  
Vol 81 (5) ◽  
pp. 794-801 ◽  
Author(s):  
L. A. Atik ◽  
N. Abrahamson ◽  
J. J. Bommer ◽  
F. Scherbaum ◽  
F. Cotton ◽  
...  
Keyword(s):  
Ground Motion ◽  
Prediction Models ◽  
Motion Prediction ◽  
Ground Motion Prediction

Ground-Motion Attenuation Model for Small-To-Moderate Shallow Crustal Earthquakes in California and Its Implications on Regionalization of Ground-Motion Prediction Models

2010 ◽  
Vol 26 (4) ◽  
pp. 907-926 ◽  
Author(s):  
Brian Chiou ◽  
Robert Youngs ◽  
Norman Abrahamson ◽  
Kofi Addo
Keyword(s):  
Ground Motion ◽  
Regional Differences ◽  
Regional Difference ◽  
Prediction Models ◽  
Motion Prediction ◽  
Ground Motion Prediction ◽  
Small Magnitude ◽  
Attenuation Model ◽  
Crustal Earthquakes ◽  
Active Tectonic

This paper presents the development of a ground-motion prediction model for small-to-moderate shallow crustal earthquakes (3M5.5, up to 200 km distance) using data from the California ShakeMap systems. Our goal is to provide an empirical model that can be confidently used in the investigation of ground-motion difference between California and other active tectonic regions (such as the Pacific Northwest and British Columbia, Canada) where the bulk of ground-motion data from shallow crustal earthquakes is in the small-to-moderate magnitude range. This attenuation model is developed as a small-magnitude extension of the Chiou and Youngs NGA model (CY2008). We observe, and incorporate into this model, a regional difference in median amplitude between central and southern California earthquakes. The strength of the regional difference diminishes with increasing spectral period. More importantly, it is magnitude dependent and becomes insignificant for M6 earthquakes, as indicated by the large-magnitude California data used in CY2008. Together, these findings have important implications on the practice of utilizing the regional differences observed in small-to-moderate earthquakes to infer the regional differences expected in large earthquakes, including the NGA model applicability in active tectonic regions outside California.

Turkey-Adjusted NGA-W1 Horizontal Ground Motion Prediction Models

2016 ◽  
Vol 32 (1) ◽  
pp. 75-100 ◽  
Author(s):  
Zeynep Gülerce ◽  
Bahadır Kargoığlu ◽  
Norman A. Abrahamson
Keyword(s):  
Ground Motion ◽  
Strong Ground Motion ◽  
Prediction Models ◽  
Ground Motions ◽  
Site Amplification ◽  
Motion Prediction ◽  
Ground Motion Prediction ◽  
Data Set ◽  
Horizontal Ground Motion ◽  
Strong Ground

The objective of this paper is to evaluate the differences between the Next Generation Attenuation: West-1 (NGA-W1) ground motion prediction models (GMPEs) and the Turkish strong ground motion data set and to modify the required pieces of the NGA-W1 models for applicability in Turkey. A comparison data set is compiled by including strong motions from earthquakes that occurred in Turkey and earthquake metadata of ground motions consistent with the NGA-W1 database. Random-effects regression is employed and plots of the residuals are used to evaluate the differences in magnitude, distance, and site amplification scaling. Incompatibilities between the NGA-W1 GMPEs and Turkish data set in small-to-moderate magnitude, large distance, and site effects scaling are encountered. The NGA-W1 GMPEs are modified for the misfit between the actual ground motions and the model predictions using adjustments functions. Turkey-adjusted NGA-W1 models are compatible with the regional strong ground motion characteristics and preserve the well-constrained features of the global models.

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