Reduced Wiener Chaos representation of random fields via basis adaptation and projection

JOURNAL OF COMPUTATIONAL PHYSICS

卷:341

Article

Tsilifis, Panagiotis^1,2  Ghanem, Roger G.² 

[1] Univ Southern Calif, Dept Math, Los Angeles, CA 90089 USA

[2] Univ Southern Calif, Dept Civil Engn, Los Angeles, CA 90089 USA

关键词: Polynomial Chaos;    Gaussian Hilbert space;    Cameron-Martin space;    Basis adaptation;    Model reduction;    Wick product;   

DOI  :  10.1016/j.jcp.2017.04.009

来源: Elsevier

【 摘 要 】

A new characterization of random fields appearing in physical models is presented that is based on their well-known Homogeneous Chaos expansions. We take advantage of the adaptation capabilities of these expansions where the core idea is to rotate the basis of the underlying Gaussian Hilbert space, in order to achieve reduced functional representations that concentrate the induced probability measure in a lower dimensional subspace. For a smooth family of rotations along the domain of interest, the uncorrelated Gaussian inputs are transformed into a Gaussian process, thus introducing a mesoscale that captures intermediate characteristics of the quantity of interest. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

Free