A method for spatial estimation of peak ground acceleration in dense arrays

Harmandar, Ebru; Çaktı, Eser; Erdik, Mustafa

doi:10.1111/j.1365-246x.2012.05671.x

Cited by 5 publications

(10 citation statements)

References 13 publications

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“…The fault plane solutions are strike-slip mechanism for the first six events [20]. The fault mechanisms of events 7 and 8 are normal faulting [20] and oblique faulting (strike-slip and normal types, [19]), respectively. The epicenter locations are displayed in Figure 3.…”

Section: Istanbul Rapid Response and Early Warning Systemmentioning

confidence: 99%

A spatial correlation model of peak ground acceleration and response spectra based on data of the Istanbul Earthquake Rapid Response and Early Warning System

Wagener

Goda

Erdik

et al. 2016

Soil Dynamics and Earthquake Engineering

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Ground motion intensity measures such as the peak ground acceleration (PGA) and the pseudo spectral acceleration (PSA) at two sites due to the same seismic event are correlated. The spatial 2 correlation needs to be considered when modeling ground-motion fields for seismic loss assessments, since it can have a significant influence on the statistical moments and probability distribution of aggregated seismic loss of a building portfolio. Empirical models of spatial correlation of ground motion intensity measures exist only for a few seismic regions in the world such as Japan, Taiwan and California, since for this purpose a dense observation network of earthquake ground motion is required. The Istanbul Earthquake Rapid Response and Early Warning System (IERREWS) provides one such dense array with station spacing of typically 2 km in the urban area of Istanbul. Based on the records of eight small to moderate (Mw3.5-Mw5.1) events, which occurred since 2003 in the Marmara region, we establish a model of intra-event spatial correlation for PGA and PSA up to the natural period of 1.0 s. The results indicate that the correlation coefficients of PGA and short-period PSA decay rapidly with increasing interstation distance, resulting in correlation lengths of approximately 3-4 km, while correlation lengths at longer natural periods (above 0.5 s) exceed 6 km. Finally, we implement the correlation model in a Monte Carlo simulation to evaluate economic loss in Istanbul's district Zeytinburnu due to a Mw7.2 scenario earthquake.

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Section: Istanbul Rapid Response and Early Warning Systemmentioning

confidence: 99%

A spatial correlation model of peak ground acceleration and response spectra based on data of the Istanbul Earthquake Rapid Response and Early Warning System

Wagener

Goda

Erdik

et al. 2016

Soil Dynamics and Earthquake Engineering

Self Cite

View full text Add to dashboard Cite

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“…These results provide confidence for predicting the PGA in unchecked sites. It is possible to interpolate peak ground acceleration from discrete array stations for generating a better shaking map after an earthquake [34]. In this study, calculating the PGA in the 24 subdivision zones requires a spatial relationship to determine a new location to represent each subdivision zone.…”

Section: Evaluation Of Seismic Design Value In Subdivision Zonementioning

confidence: 99%

Seismic Design Value Evaluation Based on Checking Records and Site Geological Conditions Using Artificial Neural Networks

Kerh¹,

Lin²,

Saunders³

2013

Abstract and Applied Analysis

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This study proposes an improved computational neural network model that uses three seismic parameters (i.e., local magnitude, epicentral distance, and epicenter depth) and two geological conditions (i.e., shear wave velocity and standard penetration test value) as the inputs for predicting peak ground acceleration—the key element for evaluating earthquake response. Initial comparison results show that a neural network model with three neurons in the hidden layer can achieve relatively better performance based on the evaluation index of correlation coefficient or mean square error. This study further develops a new weight-based neural network model for estimating peak ground acceleration at unchecked sites. Four locations identified to have higher estimated peak ground accelerations than that of the seismic design value in the 24 subdivision zones are investigated in Taiwan. Finally, this study develops a new equation for the relationship of horizontal peak ground acceleration and focal distance by the curve fitting method. This equation represents seismic characteristics in Taiwan region more reliably and reasonably. The results of this study provide an insight into this type of nonlinear problem, and the proposed method may be applicable to other areas of interest around the world.

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“…After then, 20 stations have been added. Detailed information of IERRS and data can be found in Harmandar et al (2012). The epicenters of earthquakes utilized in the present work are shown in Figure 1.…”

Section: Data and Local Site Conditionsmentioning

confidence: 99%

Vs30 değerine bağlı koherans modeli

Harmandar

2020

European Journal of Science and Technology

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Strong ground motion caused by earthquakes at every point of extended structures would not be same. This difference in ground movement has an important effect on the design of these types of structures. Meanwhile, the seismic resistant design has been lead to investigate the variability of earthquake ground motion over last decades. In this study, frequency domained variability named coherency is considered. Several coherency models have been proposed without considering soil effect. In this context, spatial variation of seismic ground motion based on the average shear wave velocity over the upper 30 m of depth, VS30 is analyzed. Initially, coherency values are calculated using data triggered during six earthquakes recorded by the Istanbul Earthquake Rapid Response System. Lagged coherency data is considered in the process to get the coherency model. Nonlinear regression analysis is used for the model to obtain a good-fit to observed data. A coefficient is defined based on VS30 values of the station-pairs. The cohereny model based on this coefficient of VS30 is derived for EW and NS components. It is expected that coherency function decreases with the increase of frequency and separation distance. The decrease in the coefficient of VS30 causes decrease in coherency. The reason is that the heterogenity in soil causes the scattering of the earthuqke waves. The variance in the coherency model between EW and NS components is small. This coherency model is used to simulate spatial variable ground motion for the accurate seismic design of extended structures for the future studies.

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A method for spatial estimation of peak ground acceleration in dense arrays

Cited by 5 publications

References 13 publications

A spatial correlation model of peak ground acceleration and response spectra based on data of the Istanbul Earthquake Rapid Response and Early Warning System

A spatial correlation model of peak ground acceleration and response spectra based on data of the Istanbul Earthquake Rapid Response and Early Warning System

Seismic Design Value Evaluation Based on Checking Records and Site Geological Conditions Using Artificial Neural Networks

Vs30 değerine bağlı koherans modeli

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