ALBERT

Description: This article proposes a new framework for the inclusion of site effects in empirical ground-motion prediction equations (GMPEs) by characterizing stations through their one-quarter wavelength velocities and assessed confidence limits. The approach is demonstrated for 14 stations of the French accelerometric network (Reseau Accelerometrique Permanent). This method can make use of all the available information about a given site, for example, the surface geology, the soil profile, standard penetration test measurements, near-surface velocity estimated from the topographic slope, depth to bedrock, and crustal structure. These data help to constrain the velocity profile down to a few kilometers. Based on a statistical study of 858 real profiles from three different regions (Japan, western North America, and France) physically realistic profiles are generated that comply with the information available for each site. In order to evaluate the confidence limits for the shear-wave velocity profiles and derived site amplifications for each station, a stochastic method is adopted: several thousand profiles are randomly generated based on parameters derived in the statistical study and the constraints available for each station. Then, the one-quarter wavelength assumption is used to estimate the amplification for each station. It is found that a good knowledge of near-surface attenuation (i.e., kappa or Q) is mandatory for obtaining precise amplification estimates at high frequencies. Nevertheless, the proposed scheme highlights the important differences in the uncertainties of the site amplifications, depending on the information available for a given station. We suggest that these results could, therefore, be used when developing GMPEs by weighting records from each station depending on the variability in the computed one-quarter wavelength velocities. This approach relies on the assumption that local site effects are only one-dimensional, which is far from true, especially in sedimentary basins. However, most GMPEs only model one-dimensional site effects, so this is not an issue specific to this study. Finally, a way to improve this technique is to use earthquakes or noise recorded at the stations to further constrain the shear-wave velocity profiles and to consequently derive more accurate one-quarter wavelength velocities.

Description: Fragility curves are generally developed using a single parameter to relate the level of shaking to the expected structural damage. The main goal of this work is to use several parameters to characterize the earthquake ground motion. The fragility curves will, therefore, become surfaces when the ground motion is represented by two parameters. To this end, the roles of various strong-motion parameters on the induced damage in the structure are compared through nonlinear time-history numerical calculations. A robust structural model that can be used to perform numerous nonlinear dynamic calculations, with an acceptable cost, is adopted. The developed model is based on the use of structural elements with concentrated nonlinear damage mechanics and plasticity-type behavior. The relations between numerous ground-motion parameters, characterizing different aspects of the shaking, and the computed damage are analyzed and discussed. Natural and synthetic accelerograms were chosen/computed based on a consideration of the magnitude-distance ranges of design earthquakes. A complete methodology for building fragility surfaces based on the damage calculation through nonlinear numerical analysis of multi-degree-of-freedom systems is proposed. The fragility surfaces are built to represent the probability that a given damage level is reached (or exceeded) for any given level of ground motion characterized by the two chosen parameters. The results show that an increase from one to two ground-motion parameters leads to a significant reduction in the scatter in the fragility analysis and allows the uncertainties related to the effect of the second ground-motion parameter to be accounted for within risk assessments. Copyright © 2009 John Wiley & Sons, Ltd.