A Novel Stochastic Methodology for the Generation of Artificial Seismic Accelerograms

Abstract

Abstract Time-history analysis requires the use of suites of accelerograms that represent the input ground motion. A simple and computationally efficient stochastic methodology for the generation of suites of fully non-stationary artificial accelerograms is presented. The proposed methodology ensures that the record suites have a given target spectral mean and variability for the whole period range of interest. The model first produces an ensemble of target spectra with a given mean and variability and then a methodology based on spectral representation techniques is used to obtain the corresponding acceleration time-histories. The proposed approach also ensures that the produced ground motions are fully non-stationary and have different duration. The outcome is a suite of ground motion time-histories whose spectral mean and variability match those obtained from a ground motion model (GMM).