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.

scholarly journals Ground-motion prediction equation and site effect characterization for the central area of the Main Syncline, Upper Silesia Coal Basin, Poland

2018 ◽  
Vol 10 (1) ◽  
pp. 474-483 ◽  
Author(s):  
Maciej Jan Mendecki ◽  
Angelika Duda ◽  
Adam Idziak
Keyword(s):  
Ground Motion ◽  
Central Area ◽  
Site Effect ◽  
Prediction Equation ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction ◽  
Coal Basin ◽  
Ground Acceleration ◽  
Upper Silesia

Abstract The aim of the study was to find the best model of ground-motion prediction equation (GMPE) forecasting peak ground acceleration (PGA) caused by induced seismicity. The maximum values of PGA on the surface are a major seismic threat for the infrastructure, especially in the highly urbanized areas, such is the Upper Silesian Metropolitan Area. The forecasting equations were estimated based on the values of PGA, epicenter distances and mining tremor energy registered by 14 surface seismometer stations located in the central area of the Main Syncline of the Upper Silesia Coal Basin. Data were collected within the period from January 2010 to December 2016, and the total number of seismic events used in the calculations was 15 541. The final model predicted the PGA values and amplification coefficients representing the characteristics of the site effects under seismometer stations.

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

scholarly journals What is the impact of the August 24, 2016 Amatrice earthquake on the seismic hazard assessment in central Italy?

2016 ◽  
Vol 59 ◽  
Author(s):  
Maura Murru ◽  
Matteo Taroni ◽  
Aybige Akinci ◽  
Giuseppe Falcone
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Hazard Assessment ◽  
Central Italy ◽  
Seismic Hazard Assessment ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
The Impact

<p>The recent Amatrice strong event (M<sub>w</sub>6.0) occurred on August 24, 2016 in Central Apennines (Italy) in a seismic gap zone, motivated us to study and provide better understanding of the seismic hazard assessment in the macro area defined as “Central Italy”. The area affected by the sequence is placed between the M<sub>w</sub>6.0 1997 Colfiorito sequence to the north (Umbria-Marche region) the Campotosto area hit by the 2009 L’Aquila sequence M<sub>w</sub>6.3 (Abruzzo region) to the south. The Amatrice earthquake occurred while there was an ongoing effort to update the 2004 seismic hazard map (MPS04) for the Italian territory, requested in 2015 by the Italian Civil Protection Agency to the Center for Seismic Hazard (CPS) of the Istituto Nazionale di Geofisica e Vulcanologia INGV. Therefore, in this study we brought to our attention new earthquake source data and recently developed ground-motion prediction equations (GMPEs). Our aim was to validate whether the seismic hazard assessment in this area has changed with respect to 2004, year in which the MPS04 map was released. In order to understand the impact of the recent earthquakes on the seismic hazard assessment in central Italy we compared the annual seismic rates calculated using a smoothed seismicity approach over two different periods; the Parametric Catalog of the Historical Italian earthquakes (CPTI15) from 1871 to 2003 and the historical and instrumental catalogs from 1871 up to 31 August 2016. Results are presented also in terms of peak ground acceleration (PGA), using the recent ground-motion prediction equations (GMPEs) at Amatrice, interested by the 2016 sequence.</p>

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
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