A biorthogonal decomposition for the identification and simulation of non-stationary and non-Gaussian random fields

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• 作者：I. Zentner^a ; G. Ferré ; ^b ; ^{gregoire.ferre@ponts.org" class="auth_mail" title="E-mail the corresponding author} ; F. Poirion^c ; M. Benoit^d
• 关键词：Random fields ; Non-Gaussian ; Non-stationary ; Bi-orthogonal decomposition ; Simulation ; Karhunen&ndash ; Loè ; ve ; Earthquake ; Sea state
• 刊名：Journal of Computational Physics
• 出版年：2016
• 出版时间：1 June 2016
• 年：2016
• 卷：314
• 期：Complete
• 页码：1-13
• 全文大小：4280 K

文摘

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).