Generation of spectrum-compatible accelerograms using information theory

International audienceThe paper is devoted to the generation of seismic accelerograms compatible with a given response spectrum and other associated properties. The time sampling of the stochastic accelerogram yields a time series represented by a random vector in high stochastic dimension. The probability density function (pdf) of this random vector is constructed using the Maximum Entropy (MaxEnt) principle under constraints defined by the available information. In this research, a novel algorithm, adapted to the high stochastic dimension, is proposed to identify the Lagrange multipliers introduced in the MaxEnt principle to take into account the constraints. The algorithm is validated through an application for which the available information is relative to the variance of each component of the random vector representing the accelerogram, statistics on the response spectrum such as the mean value and the envelopes, statistics on the Peak Ground Acceleration (PGA) and the velocity and displacement traces (behavior of the signals at the final time)