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1.
The variation of ground motions at specific stations from events in six narrow areas was inspected by using K-NET and KiK-net records. A source-area factor for individual observation stations was calculated by averaging ratios between observed values for horizontal peak acceleration and velocity, as well as acceleration response spectra for 5% damping, and predicted values using a ground-motion model (usually known as an attenuation relation) by Kanno et al. (Bull Seismol Soc Am, 96:879–897, 2006). Standard deviations between observed and predicted amplitudes after the correction factor are less than 0.2 on the logarithmic scale and decrease down to around 0.15 in the short-period range. Intra-event standard deviation clearly increases with decreasing distance due to differing paths around near source area. Standard deviations may increase with amplitude or decrease with magnitude; however, both amplitude and magnitude of the data are strongly correlated with distance. The standard deviation calculated in this study is obviously much smaller than that of the original ground-motion model, as epistemic uncertainties are minimized by grouping ground motions at specific stations. This result indicates that the accuracy of strong ground motion prediction could be improved if ground-motion models for specified region are determined individually. For this to be possible, it is necessary to have dense strong-motion networks in high-seismicity regions, such as K-NET and KiK-net.  相似文献   

2.
Macroseismic intensity data plays an important role in the process of seismic hazard analysis as well in developing of reliable earthquake loss models. This paper presents a physical-based model to predict macroseismic intensity attenuation based on 560 intensity data obtained in Iran in the time period 1975–2013. The geometric spreading and energy absorption of seismic waves have been considered in the proposed model. The proposed easy to implement relation describes the intensity simply as a function of moment magnitude, source to site distance and focal depth. The prediction capability of the proposed model is assessed by means of residuals analysis. Prediction results have been compared with those of other intensity prediction models for Italy, Turkey, Iran and central Asia. The results indicate the higher attenuation rate for the study area in distances less than 70 km.  相似文献   

3.
A partially non-ergodic ground-motion prediction equation is estimated for Europe and the Middle East. Therefore, a hierarchical model is presented that accounts for regional differences. For this purpose, the scaling of ground-motion intensity measures is assumed to be similar, but not identical in different regions. This is achieved by assuming a hierarchical model, where some coefficients are treated as random variables which are sampled from an underlying global distribution. The coefficients are estimated by Bayesian inference. This allows one to estimate the epistemic uncertainty in the coefficients, and consequently in model predictions, in a rigorous way. The model is estimated based on peak ground acceleration data from nine different European/Middle Eastern regions. There are large differences in the amount of earthquakes and records in the different regions. However, due to the hierarchical nature of the model, regions with only few data points borrow strength from other regions with more data. This makes it possible to estimate a separate set of coefficients for all regions. Different regionalized models are compared, for which different coefficients are assumed to be regionally dependent. Results show that regionalizing the coefficients for magnitude and distance scaling leads to better performance of the models. The models for all regions are physically sound, even if only very few earthquakes comprise one region.  相似文献   

4.
Earthquake ground-motion relationships for soil and rock sites in Iran have been developed based on the specific barrier model (SBM) used within the context of the stochastic modeling and calibrated against up-to-date Iranian strong-motion data. A total of 171 strong-motion accelerograms recorded at distances of up to 200 km from 24 earthquakes with moment magnitudes ranging from Mw 5.2 to 7.4 are used to determine the region-specific source parameters of this model. Regression analysis was conducted using the “random effects” methodology that considers both earthquake-to-earthquake (inter-event) variability and within-earthquake (intra-event) variability to effectively handle the problem of weighting observations from different earthquakes. The minimization of the error function in each iteration of the “random effects” procedure was performed using the genetic algorithm method. The residuals are examined against available Iranian strong-motion data to confirm that the model predictions are unbiased and that there are no significant residual trends with distance and magnitude. No evidence of self-similarity breakdown is observed between the source radius and its seismic moment. To verify the robustness of the results, tests were performed to confirm that the results are unchanged if the number of observations is changed by removing different randomly selected datasets from the original database. Stochastic simulations, using the derived SBM, are then performed to predict peak ground-motion and response spectra parameters for a wide range of magnitudes and distances. The stochastic SBM predictions agree well with the new empirical regression equations proposed for Iran, Europe and Middle East in the magnitude–distance ranges well represented by the data. It has been shown that the SBM of this study provides unbiased ground-motion estimates over the entire frequency range of most engineering interests (1–10 Hz) for the Iranian earthquakes. Our results are also important for the assessment of hazards in other seismically active environments in the Middle East and Mediterranean regions.  相似文献   

5.
The first ground-motion prediction equation derived from European and Middle Eastern strong-motion data was published more than 30 years ago; since then strong-motion networks and the resulting databank of accelerograms in the region have expanded significantly. Many equations for the prediction of peak ground-motion parameters and response spectral ordinates have been published in recent years both for the entire Euro-Mediterranean and Middle Eastern region as well as for individual countries within this region. Comparisons among empirical ground-motion models for these parameters, developed using large regional datasets, do not support the hypothesis of there being significant differences in earthquake ground-motions from one area of crustal seismicity to another. However, there are certain regions within Europe—affected by different tectonic regimes—for which the existing pan-European equations may not be applicable. The most recent European equations make it possible to now implement overdue modifications to the presentation of seismic design actions in Eurocode 8 that allow an improved approximation to the target uniform hazard spectrum (UHS). Using these recent equations, this study outlines a new approach via which an approximation to the UHS may be constructed using hazard maps calculated for peak ground velocity and the corner period T D in addition to the maps for peak ground acceleration that underpin the current stipulations of Eurocode 8.  相似文献   

6.
Considering multiple ground motion intensity measures is important in seismic hazard analysis and ground motion selection process. Using the NGA strong motion database and recently developed ground-motion prediction models, empirical correlations are developed between cumulative absolute velocity (CAV) and spectral accelerations (Sa) at periods from 0.01 to 10 s. The CAV–Sa correlations at long periods are significantly influenced by rupture distance due to modification of the frequency content and duration of the acceleration time history through travel path. Similarly, the presence of strong velocity pulses in near-source ground motions also affects the correlations at moderate to long periods. On the other hand, the correlations are not particularly sensitive to the earthquake magnitude, orientation of the ground-motion recordings, selection of ground-motion prediction models and local site conditions. Piecewise linear fitting equations are provided to quantify the correlations for various cases. The application of the CAV–Sa correlations in ground motion selection process is also discussed.  相似文献   

7.
We present the regional ground-motion prediction equations for peak ground acceleration (PGA), peak ground velocity (PGV), pseudo-spectral acceleration (PSA), and seismic intensity (MSK scale) for the Vrancea intermediate depth earthquakes (SE-Carpathians) and territory of Romania. The prediction equations were constructed using the stochastic technique on the basis of the regional Fourier amplitude spectrum (FAS) source scaling and attenuation models and the generalised site amplification functions. Values of considered ground motion parameters are given as the functions of earthquake magnitude, depth and epicentral distance. The developed ground-motion models were tested and calibrated using the available data from the large Vrancea earthquakes. We suggest to use the presented equations for the rapid estimation of seismic effect after strong earthquakes (Shakemap generation) and seismic hazard assessment, both deterministic and probabilistic approaches.  相似文献   

8.
A vital component of any seismic hazard analysis is a model for predicting the expected distribution of ground motions at a site due to possible earthquake scenarios. The limited nature of the datasets from which such models are derived gives rise to epistemic uncertainty in both the median estimates and the associated aleatory variability of these predictive equations. In order to capture this epistemic uncertainty in a seismic hazard analysis, more than one ground-motion prediction equation must be used, and the tool that is currently employed to combine multiple models is the logic tree. Candidate ground-motion models for a logic tree should be selected in order to obtain the smallest possible suite of equations that can capture the expected range of possible ground motions in the target region. This is achieved by starting from a comprehensive list of available equations and then applying criteria for rejecting those considered inappropriate in terms of quality, derivation or applicability. Once the final list of candidate models is established, adjustments must be applied to achieve parameter compatibility. Additional adjustments can also be applied to remove the effect of systematic differences between host and target regions. These procedures are applied to select and adjust ground-motion models for the analysis of seismic hazard at rock sites in West Central Europe. This region is chosen for illustrative purposes particularly because it highlights the issue of using ground-motion models derived from small magnitude earthquakes in the analysis of hazard due to much larger events. Some of the pitfalls of extrapolating ground-motion models from small to large magnitude earthquakes in low seismicity regions are discussed for the selected target region.  相似文献   

9.
This study investigates the correlation properties of integral ground-motion intensity measures (IMs) from Italian strong-motion records. The considered integral IMs include 5–95% significant duration, Housner intensity, cumulative absolute velocity, and Arias intensity. Both IM spatial correlation and the correlation between different integral and amplitude-based IMs (i.e., cross-IM correlation) are addressed in this study. To this aim, a new Italian ground-motion model (GMM) with spatial correlation for integral IMs is first introduced. Based on the newly developed GMM, the empirical correlation coefficients from interevent and intraevent residuals are investigated and various analytical correlation models between integral IMs and amplitude-based IMs are proposed. The effective range parameter representing spatial correlation properties and the trend in the cross-IM correlations are compared with existing models in the literature. The variability of the effective range parameters with respect to event-specific features is also discussed. Modeling ground-motion spatial and cross-IM correlations is an important step in seismic hazard and risk assessment of spatially distributed systems. Investigating region-specific correlation properties based on Italian strong-motion records is of special interest as several correlation models have been developed based on global datasets, often lacking earthquakes in extensional regions such as Italy.  相似文献   

10.
Ground-motion models (GMMs) are widely used in probabilistic seismic hazard analysis (PSHA) to estimate the probability distributions of earthquake-induced ground-motion intensity measures (IMs) at a site, given an earthquake of a certain magnitude occurring at a nearby location. Accounting for spatial and cross-IM correlations in earthquake-induced ground motions has important implications on probabilistic seismic hazard and loss estimates. This study first develops a new Italian GMM with spatial correlation for 31 amplitude-related IMs, including peak ground acceleration (PGA), peak ground velocity (PGV), and 5%-damped elastic pseudo-spectral accelerations (PSAs) at 29 periods ranging from 0.01 to 4 seconds. The model estimation is performed through a recently developed one-stage nonlinear regression algorithm proposed by the authors, known as the Scoring estimation approach. In fact, current state-of-practice approaches estimate spatial correlation separately from the GMM estimation, resulting in inconsistent and statistically inefficient estimators of interevent and intraevent variances and parameters in the spatial correlation model. We test whether this affects the subsequent cross-IM correlation analysis. To this aim, based on the newly developed GMM, the empirical correlation coefficients from interevent and intraevent residuals are investigated. Finally, a set of analytical correlation models between the selected IMs are proposed. This is of special interest as several correlation models between different IMs have been calibrated and validated based on advanced GMMs and global datasets, lacking earthquakes in extensional regions; however, modeling the correlation between different IM types has not been adequately addressed by current, state-of-the-art GMMs and recent ground-motion records for Italy.  相似文献   

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