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.     

Fully probabilistic seismic displacement analysis of spatially distributed slopes using spatially correlated vector intensity measures

Earthquake‐induced slope displacement is an important parameter for safety evaluation and earthquake design of slope systems. Traditional probabilistic seismic hazard analysis usually focuses on evaluating slope displacement at a particular location, and it is not suitable for spatially distributed slopes over a large region. This study proposes a computationally efficient framework for fully probabilistic seismic displacement analysis of spatially distributed slope systems using spatially correlated vector intensity measures (IMs). First, a spatial cross‐correlation model for three key ground motion IMs, that is, peak ground acceleration (PGA), Arias intensity, and peak ground velocity, is developed using 2686 ground motion recordings from 11 recent earthquakes. To reduce the computational cost, Monte Carlo simulation and data reduction techniques are utilized to generate spatially correlated random fields for the vector IMs. The slope displacement hazards over the region are further quantified using empirical predictive equations. Finally, an illustrative example is presented to highlight the importance of the spatial correlation and the advantage of using spatially correlated vector IMs in seismic hazard analysis of spatially distributed slopes. Copyright © 2013 John Wiley & Sons, Ltd.     

Ground-motion prediction equations for the intermediate depth Vrancea (Romania) earthquakes

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.     

Influence of ground-motion correlation on probabilistic assessments of seismic hazard and loss: sensitivity analysis

Recent studies have shown that the proper treatment of ground-motion variability and, particularly, the correlation of ground motion are essential for the estimation of the seismic hazard, damage and loss for distributed portfolios. In this work we compared the effects of variations in the between-earthquake correlation and in the site-to-site correlation on probabilistic estimations of seismic damage and loss for the extended objects (hypothetical portfolio) and critical elements (e.g. bridges) of a network. Taiwan Island has been chosen as a test case for this study because of relatively high seismicity and previous experience in earthquake hazard modelling. The hazard and loss estimations were performed using Monte Carlo approach on the basis of stochastic catalogues and random ground-motion fields. We showed that the influence of correlation on parameters of seismic hazard, characteristics of loss distribution and the probability of damage depend, on one hand, on level of hazard and probability level of interest (return period) and, on the other hand, the relative influence of each type of correlation is not equal.     

Spatial correlations of ground motion for non-ergodic seismic hazard analysis

Traditional probabilistic seismic hazard analysis (PSHA) uses ground-motion models that are based on the ergodic assumption, which means that the distribution of ground motions over time at a given site is the same as their spatial distribution over different sites. Evaluations of ground-motion data sets with multiple measurements at a given site and multiple earthquakes in a given region have shown that the ergodic assumption is not appropriate as there are strong systematic region-specific source terms and site-specific path and site terms that are spatially correlated. We model these correlations using a spatial Gaussian process model. Different correlations functions are employed, both stationary and non-stationary, and the results are compared in terms of their predictive power. Spatial correlations of residuals are investigated on a Taiwanese strong-motion data set, and ground motions are collected at the ANZA, CA array. Source effects are spatially correlated, but provide a much stronger benefit in terms of prediction for the ANZA data set than for the Taiwanese data set. We find that systematic path effects are best modeled by a non-stationary covariance function that is dependent on source-to-site distance and magnitude. The correlation structure estimated from Californian data can be transferred to Taiwan if one carefully accounts for differences in magnitudes. About 50% of aleatory variance can be explained by accounting for spatial correlation.     

地震动强度参数相关性对地震滑坡危险性影响分析

本文基于全概率地震滑坡危险性分析方法,利用蒙特卡罗模拟研究在不同临界屈服加速度a_c、永久位移模型、场地类别和断层距情况下,地震动强度参数相关性对地震滑坡危险性结果的影响规律。主要结果表明:在进行滑坡危险性分析时,不考虑多地震动强度参数相关性会造成预测位移值偏小,滑坡风险被低估。因此,考虑地震动强度参数相关性对滑坡危险性评价很有必要,这能使预测结果反映地震动参数样本作为输入时的实际相关性特征,为合理进行滑坡防护提供理论依据和参考。     

Post-earthquake estimates of different ground motion intensity measures for the 2012 Emilia earthquake

Estimates of the earthquake ground motion intensity over a geographical area have multiple uses, that is, emergency management, civil protection and seismic fragility assessment. In particular, with reference to fragility assessment, it is of interest to have estimates of the values of different ground-motion intensity measures in order to correlate them with the observed damage. To this purpose, the present paper uses a procedure recently proposed in the literature to estimate the ground-motion intensity for the 2012 Emilia mainshocks, considering different ground motion intensity measures and directionality effects. Ground motion prediction equations based on different site effect models, and spatial correlation models are calibrated for the Emilia earthquakes. The paper discusses the accuracy of the shakemaps obtained using the different soil effect models considered and presents the obtained shakemaps as supplementary material. The procedure presented in the paper is aimed at providing ground motion intensity values for seismic fragility assessment and is not intended as a tool to estimate shakemaps for rapid emergency assessment.     

Application of a Monte‐Carlo simulation approach for the probabilistic assessment of seismic hazard for geographically distributed portfolio

The conventional integral approach is very well established in probabilistic seismic hazard assessment (PSHA). However, Monte‐Carlo (MC) simulations can become an efficient and flexible alternative against conventional PSHA when more complicated factors (e.g. spatial correlation of ground shaking) are involved. This study aims at showing the implementation of MC simulation techniques for computing the annual exceedance rates of dynamic ground‐motion intensity measures (GMIMs) (e.g. peak ground acceleration and spectral acceleration). We use multi‐scale random field technique to incorporate spatial correlation and near‐fault directivity while generating MC simulations to assess the probabilistic seismic hazard of dynamic GMIMs. Our approach is capable of producing conditional hazard curves as well. We show various examples to illustrate the potential use of the proposed procedures in the hazard and risk assessment of geographically distributed structural systems. Copyright © 2015 John Wiley & Sons, Ltd.     

Vector-valued fragility functions for seismic risk evaluation

This article presents a method for the development of vector-valued fragility functions, which are a function of more than one intensity measure (IM, also known as ground-motion parameters) for use within seismic risk evaluation of buildings. As an example, a simple unreinforced masonry structure is modelled using state-of-the-art software and hundreds of nonlinear time-history analyses are conducted to compute the response of this structure to earthquake loading. Dozens of different IMs (e.g. peak ground acceleration and velocity, response spectral accelerations at various periods, Arias intensity and various duration and number of cycle measures) are considered to characterize the earthquake shaking. It is demonstrated through various statistical techniques (including Receiver Operating Characteristic analysis) that the use of more than one IM leads to a better prediction of the damage state of the building than just a single IM, which is the current practice. In addition, it is shown that the assumption of the lognormal distribution for the derivation of fragility functions leads to more robust functions than logistic, log-logistic or kernel regression. Finally, actual fragility surfaces using two pairs of IMs (one pair are uncorrelated while the other are correlated) are derived and compared to scalar-based fragility curves using only a single IM and a significant reduction in the uncertainty of the predicted damage level is observed. This type of fragility surface would be a key component of future risk evaluations that take account of recent developments in seismic hazard assessment, such as vector-valued probabilistic seismic hazard assessments.     

Accounting for site effect in probabilistic assessment of seismic hazard for Romania and Bucharest: a case of deep seismicity in Vrancea zone

The paper presents recent achievements in evaluations of site-dependent seismic hazard in Romania and the capital city of Bucharest caused by the Vrancea focal zone (SE-Carpathians). The zone is characterized by a high rate of occurrence of large earthquakes in a narrow focal volume at depths 60–170 km. The database that was used for the hazard evaluation includes parameters of seismicity, ground-motion source scaling and attenuation models (Fourier amplitude spectra), and site-dependent spectral amplification functions. Ground-motion characteristics were evaluated on the basis of several hundred records from more than 120 small magnitude (M 3.5–5) earthquakes occurred in 1996–2001 and a few tens of acceleration records obtained during four large (M 7.4, 7.2, 6.9 and 6.3) earthquakes. The data provide a basis for probabilistic seismic hazard assessment in terms of peak ground acceleration, peak spectral acceleration and MSK intensity using Fourier amplitude spectra for various exceedance probabilities or average return periods. It has been shown that the influence of geological factors plays very important role in distribution of earthquake ground-motion parameters along the territory of Romania.     

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.     

Selection of optimal intensity measures in probabilistic seismic demand models of highway bridge portfolios

Probabilistic seismic demand models are a common and often essential step in generating analytical fragility curves for highway bridges. With these probabilistic models being traditionally conditioned on a single seismic intensity measure (IM), the degree of uncertainty in the models is dependent on the IM used. Selection of an optimal IM for conditioning these demand models is not a trivial matter and has been the focus of numerous studies. Unlike previous studies that consider a single structure for IM selection, this study evaluates optimal IMs for use when generating probabilistic seismic demand models for bridge portfolios such as would be found in HAZUS‐MH. Selection criteria such as efficiency, practicality, sufficiency, and hazard computability are considered in the selection process. A case study is performed considering the multi‐span simply supported steel girder bridge class. Probabilistic seismic demand models are generated considering variability in the geometric configurations and material properties, using two suites of ground motions—one synthetic and one recorded motion suite. Results show that of the 10 IMs considered, peak ground acceleration (PGA) and spectral acceleration at the fundamental period are the most optimal for the synthetic motions, and that cumulative absolute velocity is also a close contender when using recorded motions. However, when hazard computability is considered, PGA is selected as the IM of choice. Previous studies have shown that spectrally based quantities perform better than PGA for a given structure, but the findings of this study indicate that when a portfolio of bridges is considered, PGA should be used. Copyright © 2007 John Wiley & Sons, Ltd.     

Probabilistic seismic hazard assessment of the Pyrenean region

A unified probabilistic seismic hazard assessment (PSHA) for the Pyrenean region has been performed by an international team composed of experts from Spain and France during the Interreg IIIA ISARD project. It is motivated by incoherencies between the seismic hazard zonations of the design codes of France and Spain and by the need for input data to be used to define earthquake scenarios. A great effort was invested in the homogenisation of the input data. All existing seismic data are collected in a database and lead to a unified catalogue using a local magnitude scale. PSHA has been performed using logic trees combined with Monte Carlo simulations to account for both epistemic and aleatory uncertainties. As an alternative to hazard calculation based on seismic sources zone models, a zoneless method is also used to produce a hazard map less dependant on zone boundaries. Two seismogenic source models were defined to take into account the different interpretations existing among specialists. A new regional ground-motion prediction equation based on regional data has been proposed. It was used in combination with published ground-motion prediction equations derived using European and Mediterranean data. The application of this methodology leads to the definition of seismic hazard maps for 475- and 1,975-year return periods for spectral accelerations at periods of 0 (corresponding to peak ground acceleration), 0.1, 0.3, 0.6, 1 and 2 s. Median and percentiles 15% and 85% acceleration contour lines are represented. Finally, the seismic catalogue is used to produce a map of the maximum acceleration expected for comparison with the probabilistic hazard maps. The hazard maps are produced using a grid of 0.1°. The results obtained may be useful for civil protection and risk prevention purposes in France, Spain and Andorra.     

Fractional order intensity measures for probabilistic seismic demand modeling applied to highway bridges

Probabilistic seismic analysis of structures involves the construction of seismic demand models, often stated as probabilistic models of structural response conditioned on a seismic intensity measure. The uncertainty introduced by the model is often a result of the chosen intensity measure. This paper introduces the concept of using fractional order intensity measures (IMs) in probabilistic seismic demand analysis and uses a single frame integral concrete box‐girder bridge class and a seismically designed multispan continuous steel girder bridge class as case studies. The fractional order IMs considered include peak ground response and spectral accelerations at 0.2 and 1.0 s considering a single degree of freedom system with fractional damping, , as well as a linear single degree of freedom system with fractional response, . The study reveals the advantage of fractional order IMs relative to conventional IMs such as peak ground acceleration, peak ground velocity, or spectral acceleration at 0.2 and 1.0 s. Metrics such as efficiency, sufficiency, practicality, and proficiency are measured to assess the optimal nature of fractional order IMs. The results indicate that the proposed fractional order IMs produce significant improvements in efficiency and proficiency, whereas maintaining practicality and sufficiency, and thus providing superior demand models that can be used in probabilistic seismic demand analysis. Copyright © 2011 John Wiley & Sons, Ltd.     

Probabilistic seismic hazard assessment for Romania and sensitivity analysis: A case of joint consideration of intermediate-depth (Vrancea) and shallow (crustal) seismicity

The earthquake risk on Romania is one of the highest in Europe, and seismic hazard for almost half of the territory of Romania is determined by the Vrancea seismic region, which is situated beneath the southern Carpathian Arc. The region is characterized by a high rate of occurrence of large earthquakes in a narrow focal volume at depth from 70 to 160 km. Besides the Vrancea area, several zones of shallow seismicity located within and outside the Romanian territory are considered as seismically dangerous. We present the results of probabilistic seismic hazard analysis, which implemented the “logic tree” approach, and which considered both the intermediate-depth and the shallow seismicity. Various available models of seismicity and ground-motion attenuation were used as the alternative variants. Seismic hazard in terms of macroseismic intensities, peak ground acceleration, and response spectra was evaluated for various return periods. Sensitivity study was performed to analyze the impact of variation of input parameters on the hazard results. The uncertainty on hazard estimates may be reduced by better understanding of parameters of the Vrancea source zone and the zones of crustal seismicity. Reduction of uncertainty associated with the ground-motion models is also very important issue for Romania.     

Intensity measures for probabilistic assessment of non‐structural components acceleration demand

A fundamental issue in the framework of seismic probabilistic risk analysis is the choice of ground motion intensity measures (IMs). Based on the floor response spectrum method, the present contribution focuses on the ability of IMs to predict non‐structural components (NSCs) horizontal acceleration demand. A large panel of IMs is examined and a new IM, namely equipment relative average spectral acceleration (E‐ASA_R), is proposed for the purpose of NSCs acceleration demand prediction. The IMs efficiency and sufficiency comparisons are based on (i) the use of a large dataset of recorded earthquake ground motions; (ii) numerical analyses performed on three‐dimensional numerical models, representing actual structural wall and frame buildings; and (iii) systematic statistical analysis of the results. From the comparative study, the herein introduced E‐ASA_R shows high efficiency with respect to the estimation of maximum floor response spectra ordinates. Such efficiency is particularly remarkable in the case of structural wall buildings. Besides, the sufficiency and the simple formulation allowing the use of existing ground motion prediction models make the E‐ASA_R a promising IMs for seismic probabilistic risk assessment. Copyright © 2015 John Wiley & Sons, Ltd.     

地震危险性概率分析方法:存在的问题和纠正

地震危险性概率分析(PSHA)是目前最广泛应用于地震灾害与风险性评估的方法。然而它在计算中却存在着一个错误:把强地面运动衰减关系(一个函数)的条件超越概率等同于强地面运动误差(一个变量)的超越概率。这个错误导致了运用强地面运动误差(空间分布特征)去外推强地面运动的发生(时间分布特征)或称之为遍历性假设,同时也造成了对PSHA理解和应用上的困难。本文推导出新的灾害计算方法(称之为KY-PSHA)来纠正这种错误。     

The Influence of Ground-Motion Variability in Earthquake Loss Modelling

Earthquake loss models are subject to many large uncertainties associated with the input parameters that define the seismicity, the ground motion, the exposure and the vulnerability characteristics of the building stock. In order to obtain useful results from a loss model, it is necessary to correctly identify and characterise these uncertainties, incorporate them into the calculations, and then interpret the results taking account of the influence of the uncertainties. An important element of the uncertainty will always be the aleatory variability in the ground-motion prediction. Options for handling this variability include following the traditional approach used in site-specific probabilistic seismic hazard assessment or embedding the variability within the vulnerability calculations at each location. The physical interpretation of both of these approaches, when applied to many sites throughout an urban area to assess the overall effects of single or multiple earthquake events, casts doubts on their validity. The only approach that is consistent with the real nature of ground-motion variability is to model the shaking component of the loss model by triggering large numbers of earthquake scenarios that sample the magnitude and spatial distributions of the seismicity, and also the distribution of ground motions for each event as defined by the aleatory variability.     

Prediction of spatially distributed seismic demands in specific structures: Ground motion and structural response

The efficacy of various ground motion intensity measures (IMs) in the prediction of spatially distributed seismic demands (engineering demand parameters, (EDPs)) within a structure is investigated. This has direct implications to building‐specific seismic loss estimation, where the seismic demand on different components is dependent on the location of the component in the structure. Several common IMs are investigated in terms of their ability to predict the spatially distributed demands in a 10‐storey office building, which is measured in terms of maximum interstorey drift ratios and maximum floor accelerations. It is found that the ability of an IM to efficiently predict a specific EDP depends on the similarity between the frequency range of the ground motion that controls the IM and that of the EDP. An IMs predictability has a direct effect on the median response demands for ground motions scaled to a specified probability of exceedance from a ground motion hazard curve. All of the IMs investigated were found to be insufficient with respect to at least one of magnitude, source‐to‐site distance, or epsilon when predicting all peak interstorey drifts and peak floor accelerations in a 10‐storey reinforced concrete frame structure. Careful ground motion selection and/or seismic demand modification is therefore required to predict such a spatially distributed demands without significant bias. Copyright © 2009 John Wiley & Sons, Ltd.     

Peak ground motion predictions in India: an appraisal for rock sites

Proper selection and ranking of Ground Motion Prediction Equations (GMPEs) is critical for successful logic-tree implementation in probabilistic seismic hazard analysis. The present study explores this issue in predicting peak ground accelerations at the rock sites in India. Macroseismic intensity data complemented with limited strong ground-motion recordings are used for the purpose. The findings corroborate the possible conformity between the GMPEs developed for tectonically active shallow crust across the globe. On the other hand, the relevant GMPEs in the intraplate regions cluster into two different groups with the equations of lower ranks catering to higher ground motions. The earthquakes in the subduction zones have significant regional implications. However, affinity in the ground-motion attenuations between the major interface events (M _W > 7.4) in Andaman-Nicobar, Japan and Cascadia, respectively, is noted. This can be also observed for the intraslab events in the Hindukush and Taiwan respectively. Overall, we do not observe any significant advantage with the equations developed using the regional data. These findings are expected to be useful in probabilistic seismic hazard analysis across the study region.