Ground-Motion Prediction Equations Based on Data from the Himalayan and Zagros Regions

This study derives ground-motion prediction equations for the horizontal elastic response spectral acceleration for 5% damping for application to the Indian Himalayas. The present equations include a consideration of site category (rock/soil) and style-of-faulting (strike-slip/reverse). Due to a lack of near-field data from India, additional strong-motion data have been included from the Zagros region of Iran, which has comparable seismotectonics to the Himalayas (continental compression). A set of 201 records from 16 earthquakes were used within the regression. The derived model predicts similar ground motions to previously published equations for the Himalayan region but with lower standard deviations.     

Technical Note: Practical Challenges Facing the Selection of Conditional Spectrum-Compatible Accelerograms

There are various possibilities for the selection and scaling of ground motions for advanced seismic assessment of buildings using nonlinear response-history analyses. As part of an on-going project looking at building-specific loss assessment in Italy, this article highlights a number of challenges currently facing the use of conditional spectra for ground motion selection in practice, essentially related to the limited amount of seismic hazard information that is publicly available. To illustrate the points being made, the challenges faced when trying to develop conditional spectra and select spectrum-compatible accelerograms for a rock site in Napoli, Italy, are described and the seismic assessment results obtained for a number of reinforced concrete wall structures are presented. Aside from providing practitioners with an appreciation of the potential difficulty associated with using conditional spectra for record selection, this technical note should also motivate national authorities to provide more background information on national seismic hazard data and detailed guidance for record selection.     

Can Earthquake Loss Models be Validated Using Field Observations?

The occurrence of a damaging earthquake provides an opportunity to compare observed and estimated damage, provided that detailed observations of the earthquake effects are made in the field. A question that arises is whether such comparisons can provide the basis for validation of an earthquake loss model. In order to explore this issue, a case study loss model for the northern Marmara region has been set up and the losses have been calculated for various ground-motion fields that arise when different assumptions are made about the ground-motion variability. In particular, the influence of removing the inter-event variability for a scenario earthquake and modeling spatial correlation among ground motions is studied. Further analyses are conducted assuming that a number of accelerograms are available within the region and that knowledge of spatial correlations among ground motions can therefore be used to better predict the motions at sites in the vicinity of the recording stations. The results demonstrate that unless one has a dense network of accelerographs (commensurate with the geographical resolution of exposure), then the variability in the losses cannot be sufficiently reduced to allow validation of the loss model.     

A Bayesian Updating Applied to Earthquake Ground-Motion Prediction Equations for Iran

This article presents new ground-motion prediction equations for three distinct seismic regions of Iran via updating the previous global model using observed data for each region by means of Bayesian updating. The Bayesian theory has the advantage that it results in more accurate results even in situations when little data is available. This leads the way for updating global models to obtain new local models for seismotectonic regions with little available data like Iran. The proposed updated model was compared against currently available models for Iran and the results reveal the overall stability and quality performance of the proposed model.     

Some Discussions on Data-Driven Testing of Ground-Motion Prediction Equations under the Turkish Ground-Motion Database

Data-driven testing of ground-motion prediction equations (GMPEs) can help researchers in the ranking and selection of GMPEs for seismic hazard assessment. This paper presents and discusses the details of the major features of well-known testing methods which employ likelihood and Euclidean distance concepts. A set of local, regional, and global GMPEs are assessed under a ground-motion database. The data-driven testing of GMPEs is supported by thorough residual analyses under the database, providing valuable insights into the testing of GMPEs. The researchers are advised to evaluate all options together instead of focusing on a specific tool to build well-structured ground-motion logic trees.     

Probabilistic Seismic Performance Assessment of Classes of Buildings Using Physics-Based Simulations and Ground-Motion Prediction Equations

We discuss the applicability of two different near field representations of seismic input within the capacity-demand diagram method for seismic performance assessment of classes of buildings in urban areas. The two representations of seismic input used are: (1) synthetic accelerograms obtained from 3D wave simulations of random rupture scenarios are used to estimate seismic risk, through the Monte-Carlo approximation; and (2) random realizations of elastic spectral displacement obtained through ground-motion prediction equations. The implementation of the proposed formulation in evaluating the seismic performance of two classes of buildings in the town of Sulmona, Italy, indicates that empirical ground-motion prediction equations, combined with non-iterative methods for estimating the inelastic seismic demand, can produce results comparable to the physics-based simulations.     

Empirical Correlations of Frequency-Content Parameters of Ground Motions with Other Intensity Measures

Empirical correlations between the frequency-content parameters of earthquake ground motions and amplitude-, cumulative-, and duration-based intensity measures (IMs) are examined in this study. Three commonly used scalar frequency-content parameters are considered, namely the mean period (T_m), the average spectral period (T_avg), and the smoothed spectral predominant period (T₀). It is found that the frequency-content parameters have weakly negative correlations with high-frequency IMs such as peak ground acceleration (PGA) and spectral accelerations (SAs) at periods smaller than 0.3 s, low-to-moderate positive correlations with peak ground velocity (PGV) and SA within a period range of 0.5 s–10 s, negligible correlations with cumulative-based IMs, and weakly positive correlations (in the vicinity of 0.1–0.3) with significant durations. Simple piecewise parametric equations are proposed to fit the empirical correlations of T_m, T_avg, and T₀ with SA over the entire period range. The presented correlation results and parametric models enable the frequency-content parameters to be easily used in various applications such as ground-motion selection and vector-based probabilistic seismic hazard analysis.