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

被引：4

作者：

Zentner, I. ^{[1
]}

Ferre, G. ^{[2
]}

Poirion, F. ^{[3
]}

Benoit, M. ^{[4
]}

机构：

[1] Univ Paris Saclay, UMR EDF ENSTA CNRS CEA 9219, IMSIA, 828 Blvd Marechaux, F-91762 Palaiseau, France

[2] Ecole Ponts ParisTech, CERMICS, 6 & 8 Ave Blaise Pascal, F-77455 Champs Sur Marne 2, Marne La Vallee, France

[3] Off Natl Etud & Rech Aerosp, Dept Struct Dynam & Aeroelast, BP72,29 Ave Div Leclerc, F-92322 Chatillon, France

[4] Aix Marseille Univ, Ecole Cent Marseille, CNRS, IRPHE,UMR 7342, 49 Rue Freder Joliot Curie,BP 146, F-13384 Marseille 13, France

来源：

JOURNAL OF COMPUTATIONAL PHYSICS | 2016年 / 314卷

关键词：

Random fields; Non-Gaussian; Non-stationary; Bi-orthogonal decomposition; Simulation; Karhunen-Loeve; Earthquake; Sea state; KARHUNEN-LOEVE EXPANSION;

D O I：

10.1016/j.jcp.2016.02.067

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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). (C) 2016 Elsevier Inc. All rights reserved.

引用

页码：1 / 13

页数：13

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