An evaluation of strong motion records and a new parameter A95

From the past studies of acceleration records, it is generally recognised that peak acceleration is not a suitable measure of the ground motion for design purposes. Usually, peak accelerations are difficult to predict. They occur in high frequency pulses containing very little energy and therefore are of little consequence. On the other hand acceleration has direct and useful application in engineering design. A new parameter A₉₅ is introduced in this paper which is defined as that level of acceleration which contains up to 95 per cent of the Arias Intensity. From the study of 135 records, it is noticed that the variation of the fraction of Arias Intensity with acceleration level can be described by a very well defined relationship. It is also observed that A₉₅ and Arias Intensity bear a stable relationship. Furthermore, the Arias Intensity at a site correlates more closely with the earthquake magnitude and the distance of the site from the source in attenuation relationships. From the available data, relationships are derived which show that there is a difference between the near-field and the far-field attenuation laws. The following relationships are obtained: where E_s = Arias Intensity, E_x = fraction of Arias Intensity above an acceleration level A, M = surface wave magnitude, R = nearest distance to the energy source or focal distance in km.     

Near-source ground motion attenuation relationship for PGA and PSA of the vertical and horizontal components

In this paper, empirical ground-motion models for the vertical and average horizontal components of peak ground-motion and acceleration response spectra from shallow crustal earthquakes are derived using near-source database. These attenuation relationships were derived using a worldwide dataset consisted of corrected and processed accelerograms of 678 strong-motion records recorded with 60 km of the rupture plane of earthquakes between M_w 5.2 and 7.9. Ground motion models are functions of earthquake mechanism, distance from source to site, local average shear wave velocity, nonlinear soil response, sediment depth, depth-to-top of the rupture, hanging wall effects and faulting mechanism.     

Empirical attenuation relationship for Arias Intensity

Arias Intensity is a ground motion parameter that captures the potential destructiveness of an earthquake as the integral of the square of the acceleration–time history. It correlates well with several commonly used demand measures of structural performance, liquefaction, and seismic slope stability. A new empirical relationship is developed to estimate Arias Intensity as a function of magnitude, distance, fault mechanism, and site category based on 1208 recorded ground motion data from 75 earthquakes in active plate‐margins. Its functional form is derived from the point‐source model, and the coefficients are determined through non‐linear regression analyses using a random‐effects model. The results show that for large magnitude earthquakes (M > 7) Arias Intensity was significantly overestimated by previous relationships while it was underestimated for smaller magnitude events (M ? 6). The average horizontal Arias Intensity is not significantly affected by forward rupture directivity in the near‐fault region. The aleatory variability associated with Arias Intensity is larger than that of most other ground motion parameters such as spectral acceleration. However, it may be useful in assessing the potential seismic performance of stiff engineering systems whose response is dominated by the short‐period characteristics of ground motions. Copyright © 2003 John Wiley & Sons, Ltd.     

Comparison of conventional and Monte Carlo simulation-based probabilistic seismic hazard analyses for Shiraz city,southern Iran

Estimation of ground-motion amplitudes of different hazard levels is of paramount importance in planning of urban development of any metropolis. Such estimation can be computed through a probabilistic seismic hazard analysis (PSHA). This paper concentrates on the PSHA of an area located in Shiraz city, southern Iran. The area includes whole of Shiraz city (i.e., one of the largest and most populous cities of Iran) and its outskirts. Conventional and Monte Carlo simulation-based approaches are utilized to perform the PSHA of the studied area. Two areal seismic source models are delineated, and thence seismicity parameters of all zones associated with their corresponding uncertainties are computed. Uncertainties in ground-motion prediction are accounted for via three ground-motion prediction equations (GMPEs) within the logic tree framework. These GMPEs are applied to estimate bedrock ground shaking (V_s30?=?760 m/s) for several return periods (i.e., 75, 475, 975, and 2475 years). In general, the results of the two abovementioned PSHA approaches show relatively similar results. However, the Monte Carlo simulation-based approach overpredicts bedrock spectral accelerations at periods of 0.4–2.5 s compared to the conventional PSHA approach for return periods of 475, 975, and 2475 years.     

Assessment of ground motion variability and its effects on seismic hazard analysis: a case study for iceland

Probabilistic seismic hazard analysis (PSHA) generally relies on the basic assumption that ground motion prediction equations (GMPEs) developed for other similar tectonic regions can be adopted in the considered area. This implies that observed ground motion and its variability at considered sites could be modelled by the selected GMPEs. Until now ground-motion variability has been taken into account in PSHA by integrating over the standard deviation reported in GMPEs, which significantly affects estimated ground motions, especially at very low probabilities of exceedance. To provide insight on this issue, ground-motion variability in the South Iceland Seismic Zone (SISZ), where many ground-motion records are available, is assessed. Three statistical methods are applied to separate the aleatory variability into source (inter-event), site (inter-site) and residual (intra-event and intra-site) components. Furthermore, the current PSHA procedure that makes the ergodic assumption of equality between spatially and temporal variability is examined. In contrast to the ergodic assumption, several recent studies show that the observed ground-motion variability at an individual location is lower than that implied by the standard deviation of a GMPE. This could imply a mishandling of aleatory uncertainty in PSHA by ignoring spatial variability and by mixing aleatory and epistemic uncertainties in the computation of sigma. Station correction coefficients are introduced in order to capture site effects at different stations. The introduction of the non-ergodic assumption in PSHA leads to larger epistemic uncertainty, although this is not the same as traditional epistemic uncertainty modelled using different GMPEs. The epistemic uncertainty due to the site correction coefficients (i.e. mean residuals) could be better constrained for future events if more information regarding the characteristics of these seismic sources and path dependence could be obtained.     

Criteria for Selecting and Adjusting Ground-Motion Models for Specific Target Regions: Application to Central Europe and Rock Sites

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.     

基于阿里亚斯烈度估值的概率性地震危险性分析——以四川丹棱县及其周缘为例

以编制《中国地震动参数区划图》时所构建的地震潜在震源区模型和地震活动性模型为基本输入,在四川省丹棱县及其周缘地区开展基于阿里亚斯烈度的概率地震危险性分析,计算50年超越概率10%的阿里亚斯烈度(Arias Intensity,Ia)。结果表明:丹棱县及其周缘绝大部分地区的Ia值都在0.11m/s以上,部分地区在0.32m/s甚至0.54m/s以上,具有较高的地震诱发滑坡风险,应当加强人员密集区的地震诱发滑坡危险性评估。根据不同Ia预测方程计算得到的Ia分布有较大差异,因此在计算Ia时应考虑多个Ia预测方程,对最终结果进行加权平均,以减小Ia结果的不确定性。同时还发现Ia值与1.0s的谱加速度具有很好的相关性,这也印证了Ia和1.0s谱加速度与砂土液化的相关性。     

Damage potential of near-fault records: sliding displacement against conventional “Intensity Measures”

The potential of a particular ground accelerogram to inflict damage to asymmetric strongly-inelastic systems is studied in the paper. An idealised analogue, the rigid block with frictional contact on an inclined base, is adopted as the generic representation of such systems. The inclined base (of (a sufficiently steep) angle) is shaken with numerous strong records bearing the effects of forward-directivity and/or fling-step. The accumulated slippage, D, of the block caused by each record is taken as the induced “damage” to the system. The relevance of a variety of ‘Intensity Measures’ of each accelerogram (ranging from PGA and PGV to Housner’s and Arias’ Intensities) in predicting this damage, is investigated statistically. It is shown that only a few of these ‘Intensity Measures’ are reasonably successful and their use could therefore be recommended, but only for statistical inference. A detailed deterministic analysis presented in the paper for one of these successful measures, Arias Intensity, reveals the unacceptably poor predictive power of this measure. Upper-bound curves of slippage provided in closed-form expressions, are an improvement over the state-of-practice Makdisi & Seed diagrams.     

Sensitivity of site response analysis on the number of ground motion records and implications for PSHA

This paper investigates issues related to the number of ground-motion records required for the performance of site response analysis and the inclusion of the site-specific amplification function within probabilistic seismic hazard calculations (PSHA). It explores the minimum number of records required for a robust estimation of the median and standard deviation of the site amplification function, as well as the impact of the selected ground-motion suites on the results of PSHA. Site response analyses are performed using both equivalent linear and nonlinear methodologies. Although the median amplification was observed to be relatively easy to capture, the standard deviation was seen to fluctuate considerably, especially when suites of few records were used. It was observed that in the case of the nonlinear site response analysis 10 records provide relatively stable estimates of the hazard curves for the majority of periods, while in the case of the equivalent linear analysis 20 records or more are required to achieve a similar level of accuracy.     

Correlation properties of integral ground-motion intensity measures from Italian strong-motion records

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.     

A predictive model for Arias intensity at multiple sites and consideration of spatial correlations

Arias intensity, I_a, has been identified as an efficient intensity measure for the estimation of earthquake‐induced losses. In this paper, a new model for the prediction of Arias intensity, which incorporates nonlinear site response through the use of the average shear‐wave velocity and a heteroskedastic variance structure, is proposed. In order to estimate the effects of ground motions on spatially‐distributed systems, it is important to take into account the spatial correlation of the intensity measure. However, existing loss‐estimation models, which use I_a as an input, do not take this aspect of the ground motion into account. Therefore, the potential to model the spatial correlation of Arias intensity is also investigated. The empirical predictive model is developed using recordings from the Pacific Earthquake Engineering Research Center Next Generation of Attenuation database whereas the model for spatial correlation makes use of the well‐recorded events from this database, that is the Northridge and Chi‐Chi earthquakes. Copyright © 2011 John Wiley & Sons, Ltd.     

Scalar and vector probabilistic seismic hazard analysis: application for Algiers City

This study deals with the application of probabilistic seismic hazard analysis (PSHA) for a rock site located in Algiers city. For this purpose, recent ground motion prediction equations developed in the world for similar sismotectonic context are used through logic tree in PSHA framework; the obtained results reflect clearly the high seismicity of the considered region. Moreover, deaggregation analysis is conducted to obtain the mean scenario in terms of magnitude and distance. In addition to the scalar-PSHA, a new method named vector-PSHA developed in recent years is performed in this study. Based on the multivariate probability theory, the software used in scalar approach is modified allowing the application of this approach for a real site in Algiers city with a vector of two and three parameters of intensity measure. The results are presented in terms of the joint annual rate of exceeding several thresholds such as PGA, PSA(T) of multiple vibration periods, peak ground velocity and Arias intensity and comparison between results of PSHA and V-PSHA is done.     

Sensitivity analysis study of the source parameter uncertainty factors for predicting near-field strong ground motion

Uncertainty factors have substantial influences on the numerical simulations of earthquakes. However, most simulation methods are deterministic and do not sufficiently consider those uncertainty factors. A good approach for predicting future destructive earthquakes that is also applied to probabilistic hazard analysis is studying those uncertainty factors, which is very significant for improving the reliability and accuracy of ground-motion predictions. In this paper, we investigated several uncertainty factors, namely the initial rupture point, stress drop, and number of sub-faults, all of which display substantial influences on ground-motion predictions, via sensitivity analysis. The associated uncertainties are derived by considering the uncertainties in the parameter values, as those uncertainties are associated with the ground motion itself. A sensitivity analysis confirms which uncertainty factors have large influences on ground motion predictions, based upon which we can allocate appropriate weights to those uncertainty factors during the prediction process. We employ the empirical Green function method as a numerical simulation tool. The effectiveness of this method has been previously validated, especially in areas with sufficient earthquake record data such as Japan, Southwest China, and Taiwan, China. Accordingly, we analyse the sensitivities of the uncertainty factors during a prediction of strong ground motion using the empirical Green function method. We consequently draw the following conclusions. (1) The stress drop has the largest influence on ground-motion predictions. The discrepancy between the maximum and minimum PGA among three different stations is very large. In addition, the PGV and PGD also change drastically. The Arias intensity increases exponentially with an increase in the stress drop ratio of two earthquakes. (2) The number of sub-faults also has a large influence on various ground-motion parameters but a small influence on the Fourier spectrum and response spectrum. (3) The initial rupture point largely influences the PGA and Arias intensity. We will accordingly pay additional attention to these uncertainty factors when we conduct ground-motion predictions in the future.     

Peak ground accelerations from large (<Emphasis Type="Bold">M</Emphasis> ≥ 7.2) shallow crustal earthquakes: a comparison with predictions from eight recent ground-motion models

Strong-motion data from large (M ≥ 7.2) shallow crustal earthquakes invariably make up a small proportion of the records used to develop empirical ground motion prediction equations (GMPEs). Consequently GMPEs are more poorly constrained for large earthquakes than for small events. In this article peak ground accelerations (PGAs) observed in 38 earthquakes worldwide with M ≥ 7.2 are compared with those predicted by eight recent GMPEs. Well over half of the 38 earthquakes were not considered when deriving these GMPEs but the data were identified by a thorough literature review of strong-motion reports from the past 60 years. These data are provided in an electronic supplement for future investigations on ground motions from large earthquakes. The addition of these data provides better constraint of the between-event ground-motion variability in large earthquakes. It is found that the eight models generally provide good predictions for PGAs from these earthquakes, although there is evidence for slight under- or over-prediction of motions by some models (particularly for M > 7.6). The between-event variabilities predicted by most models match the observed variability, if data from two events (2001 Bhuj and 2005 Crescent City) that are likely atypical of earthquakes in active regions are excluded. For some GMPEs there is evidence that they are over-predicting PGAs in the near-source region of large earthquakes as well as over-predicting motions on hard rock. Overall, however, all the considered models, despite having been derived using limited data, provide reliable predictions of PGAs in the largest crustal earthquakes.     

The 2014 Earthquake Model of the Middle East: ground motion model and uncertainties

We summarize the main elements of a ground-motion model, as built in three-year effort within the Earthquake Model of the Middle East (EMME) project. Together with the earthquake source, the ground-motion models are used for a probabilistic seismic hazard assessment (PSHA) of a region covering eleven countries: Afghanistan, Armenia, Azerbaijan, Cyprus, Georgia, Iran, Jordan, Lebanon, Pakistan, Syria and Turkey. Given the wide variety of ground-motion predictive models, selecting the appropriate ones for modeling the intrinsic epistemic uncertainty can be challenging. In this respect, we provide a strategy for ground-motion model selection based on data-driven testing and sensitivity analysis. Our testing procedure highlights the models of good performance in terms of both data-driven and non-data-driven testing criteria. The former aims at measuring the match between the ground-motion data and the prediction of each model, whereas the latter aims at identification of discrepancies between the models. The selected set of ground models were directly used in the sensitivity analyses that eventually led to decisions on the final logic tree structure. The strategy described in great details hereafter was successfully applied to shallow active crustal regions, and the final logic tree consists of four models (Akkar and Ça?nan in Bull Seismol Soc Am 100:2978–2995, 2010; Akkar et al. in Bull Earthquake Eng 12(1):359–387, 2014; Chiou and Youngs in Earthq Spectra 24:173–215, 2008; Zhao et al. in Bull Seismol Soc Am 96:898–913, 2006). For other tectonic provinces in the considered region (i.e., subduction), we adopted the predictive models selected within the 2013 Euro-Mediterranean Seismic Hazard Model (Woessner et al. in Bull Earthq Eng 13(12):3553–3596, 2015). Finally, we believe that the framework of selecting and building a regional ground-motion model represents a step forward in ground-motion modeling, particularly for large-scale PSHA models.     

Investigating strong ground-motion variability using analysis of variance and two-way-fit plots

A statistical method to quantitatively assess the relative importance of unmodelled site and source effects on the observed variability (σ) in ground motions is presented. The method consists of analysis of variance (ANOVA) using the computed residuals with respect to an empirical ground-motion model for strong-motion records of various earthquakes recorded at a common set of stations. ANOVA divides the overall variance (σ ²) into the components due to site and source effects (respectively σ _S ² and σ _E ²) not modelled by the ground-motion model plus the residual variance not explained by these effects (σ _R ²). To test this procedure, four sets of observed strong-motion records: two from Italy (Umbria-Marche and Molise), one from the French Antilles and one from Turkey, are used. It is found that for the data from Italy, the vast majority of the observed variance is attributable to unmodelled site effects. In contrast, the variation in ground motions in the French Antilles and Turkey data is largely attributable, especially at short periods, to source effects not modelled by the ground-motion estimation equations used.     

A strong-motion database from the Central American subduction zone

Subduction earthquakes along the Pacific Coast of Central America generate considerable seismic risk in the region. The quantification of the hazard due to these events requires the development of appropriate ground-motion prediction equations, for which purpose a database of recordings from subduction events in the region is indispensable. This paper describes the compilation of a comprehensive database of strong ground-motion recordings obtained during subduction-zone events in Central America, focusing on the region from 8 to 14° N and 83 to 92° W, including Guatemala, El Salvador, Nicaragua and Costa Rica. More than 400 accelerograms recorded by the networks operating across Central America during the last decades have been added to data collected by NORSAR in two regional projects for the reduction of natural disasters. The final database consists of 554 triaxial ground-motion recordings from events of moment magnitudes between 5.0 and 7.7, including 22 interface and 58 intraslab-type events for the time period 1976–2006. Although the database presented in this study is not sufficiently complete in terms of magnitude–distance distribution to serve as a basis for the derivation of predictive equations for interface and intraslab events in Central America, it considerably expands the Central American subduction data compiled in previous studies and used in early ground-motion modelling studies for subduction events in this region. Additionally, the compiled database will allow the assessment of the existing predictive models for subduction-type events in terms of their applicability for the Central American region, which is essential for an adequate estimation of the hazard due to subduction earthquakes in this region.     

Ground-motion prediction equations (GMPEs) for inelastic response and structural behaviour factors

The objective of this paper is to present ground-motion prediction equations describing constant-ductility inelastic spectral ordinates and structural behaviour factors. These equations are intended for application within the framework of Eurocode 8. Most of the strong-motion data used in the present work is obtained from the ISESD (Internet Site for European Strong-motion Data) databank. Present analysis includes ground motion records from significant Icelandic earthquakes, which are augmented by records obtained from continental Europe and the Middle East. In all cases the selected ground motion records are generated during shallow earthquakes within a distance of 100 km from the recording station. The classification of site conditions in the present work is based on the Eurocode 8 definition.     

Wavelet-Hilbert transform-based simulation of pulse-like ground motion

In nonlinear dynamic structural analysis, a suite of pulse-like ground motions is required for the performance-based design of structures near active faults. The dissimilarity in the amplitude and frequency content of the earthquake time series referred to nonstationary properties in temporal and spectral, respectively. An approach is proposed based on the nonstationary properties of the far-field records and the seismological information in an event for simulating pulse-like records. The pulse-like earthquake time history is estimated via the superposition of the residual part of the earthquake with the estimated pulse. The wavelet-based Hilbert transform is utilized to characterize the nonstationary properties, the instantaneous amplitude, and frequencies of far-field records to model residual part. The effects of near-fault and pulse are estimated based on the seismological properties of the region. The validation of the procedure is indicated by comparing simulated time-series, response spectra, and Arias intensity with recorded pulse-like records in two different earthquakes in California; the M_w 6.7 1994 Northridge and the M_w 6.5 1979 Imperial valley.

     

Intensity attenuation for active crustal regions

We develop globally applicable macroseismic intensity prediction equations (IPEs) for earthquakes of moment magnitude M _W 5.0?C7.9 and intensities of degree II and greater for distances less than 300?km for active crustal regions. The IPEs are developed for two distance metrics: closest distance to rupture (R _rup) and hypocentral distance (R _hyp). The key objective for developing the model based on hypocentral distance??in addition to more rigorous and standard measure R _rup??is to provide an IPE which can be used in near real-time earthquake response systems for earthquakes anywhere in the world, where information regarding the rupture dimensions of a fault may not be known in the immediate aftermath of the event. We observe that our models, particularly the model for the R _rup distance metric, generally have low median residuals with magnitude and distance. In particular, we address whether the direct use of IPEs leads to a reduction in overall uncertainties when compared with methods which use a combination of ground-motion prediction equations and ground motion to intensity conversion equations. Finally, using topographic gradient as a proxy and median model predictions, we derive intensity-based site amplification factors. These factors lead to a small reduction of residuals at shallow gradients at strong shaking levels. However, the overall effect on total median residuals is relatively small. This is in part due to the observation that the median site condition for intensity observations used to develop these IPEs is approximately near the National Earthquake Hazard Reduction Program CD site-class boundary.