Peak Ground Acceleration of East Malaysia Based on a Proposed Ground Motion Prediction Equation

2021 ◽  
pp. 74-81
Author(s):  
Noor Sheena Herayani Harith
Keyword(s):  
Ground Motion ◽  
Peak Ground Acceleration ◽  
Prediction Equation ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction ◽  
Ground Acceleration ◽  
East Malaysia

scholarly journals Assessment of Peak Ground Acceleration for South Chhattisgarh (India), with Local Site Parameters: A Deterministic Method

2019 ◽  
Vol 8 (3) ◽  
pp. 873-877
Keyword(s):  
Ground Motion ◽  
Peak Ground Acceleration ◽  
Prediction Equation ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction ◽  
Ground Acceleration ◽  
Seismogenic Source ◽  
Earthquake Resistant ◽  
Earthquake Resistant Structures

Looking into the present scenario worldwide, it is obvious that there is rapid increase in construction activities hence, the vulnerability to calamities of areas leading to large loss potentials. So the researches all over the globe are basically focused over disaster management, to safeguard the life and properties. The district headquarters Dantewara, Jagdalpur and Kanker are located in the south of Chhattisgarh state (India), where high concentration of the tribal population and rapid infrastructure development is observed. In order to trim down vulnerability, precise microzonation studies are required to be a constituent of the master plan, for construction activities, of earthquake resistant structures in the south of Chhattisgarh region. In the present research, the Deterministic Seismic Hazard Analysis (DSHA) for district headquarters of south Chhattisgarh has been carried out. In order to estimate the seismic parameters, past earthquake data of district headquarters of south Chhattisgarh, with radius of 300kM around them has been analyzed. Thirteen, Twelve and Eighteen tectonic features have been identified as potential seismogenic source, from the seismotectonic atlas of India for Dantewara, Jagdalpur and Kanker respectively. The maximum magnitude has been assigned to each seismogenic source. To evaluate the hazard in the study region, Ground Motion Prediction Equation (GMPE) developed by Cornell (1976) and Raghukanth and Iyengar (2004) has been used. The Peak Ground Acceleration (PGA) values are estimated for district headquarters of Dantewara, Jagdalpur & Kanker around its adjoining areas. Maximum PGA value for return period of100 years at bed rock level is 0.05063g and 0.06378g for Dantewara region using Ground Motion Prediction Equation (GMPE) developed by Cornell (1976) and Raghukanth & Iyengar (2004). It has been reported from the study that the above values are found to be on the lower side as compared to the recommendation given by IS Code of practice (IS:1893 part I (2016).The outcome of present research can be directly implemented for design of earthquake resistant structures in south Chhattisgarh region. Thus the study accounts that south Chhattisgarh is safe from seismic risk.

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.

scholarly journals A Ground-Motion Prediction Equation for Fennoscandian Nuclear Installations

2020 ◽  
Vol 110 (3) ◽  
pp. 1211-1230 ◽  
Author(s):  
Ludovic Fülöp ◽  
Vilho Jussila ◽  
Riina Aapasuo ◽  
Tommi Vuorinen ◽  
Päivi Mäntyniemi
Keyword(s):  
Ground Motion ◽  
Prediction Equation ◽  
Nuclear Industry ◽  
Motion Prediction ◽  
Depth Range ◽  
Ground Motion Prediction Equation ◽  
Ground Motion Prediction ◽  
Local Data ◽  
Backbone Curve ◽  
Ground Acceleration

ABSTRACT We propose a ground-motion prediction equation (GMPE) for probabilistic seismic hazard analysis of nuclear installations in Finland. We collected and archived the acceleration recordings of 77 earthquakes from seismic stations on very hard rock (VHR, i.e., the shear-wave velocity in the upper 30 m of the geological profile=2800  m/s according to the definition used in the nuclear industry) in Finland and Sweden since 2006 and computed the corresponding response spectra important for engineering evaluation. We augmented the narrow magnitude range of the local data by a subset of VHR recordings of 33 earthquakes from the Next Generation Attenuation for Central and Eastern North America (CENA) (NGA-East) database, mainly from eastern Canada. We adapted the backbone curves of the G16 equation proposed by Graizer (2016) for CENA. After the calibration, we evaluated the accuracy of the median prediction and the random error. We conclude that the GMPE developed can be used for predicting ground motions in Fennoscandia. Because of compatibility with the original G16 backbone curve and comparisons with the NGA-East GMPEs, we estimate that the formulation proposed is valid on VHR over the range of 2≤moment magnitude≤7.0 and 0≤ rupture distance ≤300  km, the depth range over 1.5–37 km, and frequencies between 1 and 100 Hz. The median of the composite prediction of the GMPE proposed was reasonable. The standard deviation of the prediction error (σ) was over the range of 0.73–0.86, in ln spectral acceleration units, for the relevant spectral frequencies. This is somewhat lower than the G16 σ, indicating lower aleatory variability. The new Fenno-G16 GMPE is applicable over a wider range of magnitudes than the two older GMPEs available in Finland and fits the data better, especially for peak ground acceleration and 25 Hz.

Global Ground Motion Prediction Equation for Shallow Crustal Regions

2013 ◽  
Vol 29 (3) ◽  
pp. 777-791 ◽  
Author(s):  
Vladimir Graizer ◽  
Erol Kalkan ◽  
Kuo-Wan Lin
Keyword(s):  
United States ◽  
Ground Motion ◽  
Physical Phenomenon ◽  
Prediction Equation ◽  
Motion Prediction ◽  
Ground Motion Prediction Equation ◽  
Eastern United States ◽  
Ground Motion Prediction ◽  
Ground Acceleration ◽  
Recorded Data

The Graizer-Kalkan ground-motion prediction equation (GMPE) for peak ground acceleration (PGA) constitutes a series of filters, each of which represents a certain physical phenomenon affecting the radiation of seismic waves from the source. The performance of this GMPE is examined by using about 14,000 records from 245 worldwide shallow crustal events. The recorded data and predictions show an excellent match as far as 100 km from the fault. Beyond 100 km, the data generally show faster attenuation on the order of Rrup−4 due to a relatively low Q (as in the western United States) or slower attenuation on the order of Rrup−1.5 due to a high Q (as in the central and eastern United States). An improved GMPE is developed to account for regional variations in ground motion attenuation. The The new GMPE produces a better match to recorded data up to 500 km from the fault.

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.

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