A New Ground Motion Selection and Scaling Procedure for Nonlinear Seismic Response Prediction

This study presents a methodology for selecting and scaling real earthquake ground motions to be used in the estimation of nonlinear structural response. The proposed procedure explicitly considers the uncertainty in the target intensity measure with the level of spectral variability preserved in the ground motion suite. The candidate ground motion sets are constructed based on dispersion statistics about the target spectral demand. The optimum ground-motion set is linearly scaled by using an optimization algorithm that minimizes the error between scaled median and target spectra. The scaling stage ensures that the median record spectrum provides a reasonable match to target median in a previously defined period interval. The effect of the spectral variability on seismic demand estimations is investigated using various inelastic single degree of freedom structural systems. In order to investigate the impact of different selection and scaling methodologies on nonlinear structural response, the results are compared with those obtained by the Conditional Spectrum (CS) based scaling methodology. The variability in the nonlinear structural response due to the use of different numbers of scaled recordings are also examined with the aim of finding optimum number of ground motions for reliable and stable estimation of nonlinear structural behavior.