Multi-fidelity stochastic collocation method for computation of statistical moments

JOURNAL OF COMPUTATIONAL PHYSICS

卷:341

Article

Zhu, Xueyu¹  Linebarger, Erin M.²  Xiu, Dongbin³ 

[1] Univ Iowa, Dept Math, Iowa City, IA 52242 USA

[2] Univ Utah, Dept Math, Salt Lake City, UT 84112 USA

[3] Ohio State Univ, Dept Math, Columbus, OH 43210 USA

关键词: Uncertainty quantification;    Stochastic collocation;    Multi-fidelity;   

DOI  :  10.1016/j.jcp.2017.04.022

来源: Elsevier

【 摘 要 】

We present an efficient numerical algorithm to approximate the statistical moments of stochastic problems, in the presence of models with different fidelities. The method extends the multi-fidelity approximation method developed in [18,26]. By combining the efficiency of low-fidelity models and the accuracy of high-fidelity models, our method exhibits fast convergence with a limited number of high-fidelity simulations. We establish an error bound of the method and present several numerical examples to demonstrate the efficiency and applicability of the multi-fidelity algorithm. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

Free