Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6930280 | Journal of Computational Physics | 2016 | 13 Pages |
Abstract
In this paper, a new method for the identification and simulation of non-Gaussian and non-stationary stochastic fields given a database is proposed. It is based on two successive biorthogonal decompositions aiming at representing spatio-temporal stochastic fields. The proposed double expansion allows to build the model even in the case of large-size problems by separating the time, space and random parts of the field. A Gaussian kernel estimator is used to simulate the high dimensional set of random variables appearing in the decomposition. The capability of the method to reproduce the non-stationary and non-Gaussian features of random phenomena is illustrated by applications to earthquakes (seismic ground motion) and sea states (wave heights).
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
I. Zentner, G. Ferré, F. Poirion, M. Benoit,