Comparative numerical analysis using reduced-order modeling strategies for nonlinear large-scale systems

被引：36

作者：

Dimitriu, Gabriel ^{[1
]}

Stefanescu, Razvan ^{[2
]}

Navon, Ionel M. ^{[3
]}

机构：

[1] Univ Med & Pharm Grigore T Popa, Dept Math & Informat, Str Univ 16, Iasi 700115, Romania

[2] North Carolina State Univ, Dept Math, Raleigh, NC 27615 USA

[3] Florida State Univ, Dept Comp Sci, Tallahassee, FL 32306 USA

来源：

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2017年 / 310卷

关键词：

Reduced-order modeling; Proper Orthogonal Decomposition (POD); Gappy POD; Discrete Empirical Interpolation; Missing Point Estimation; Predator-prey model; PROPER ORTHOGONAL DECOMPOSITION; SHALLOW-WATER EQUATIONS; PREDATOR-PREY SYSTEM; COHERENT STRUCTURES; EMPIRICAL INTERPOLATION; PRINCIPAL COMPONENTS; FLUID-DYNAMICS; REDUCTION; POD; TURBULENCE;

D O I：

10.1016/j.cam.2016.07.002

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We perform a comparative analysis using three reduced-order strategies - Missing Point Estimation (MPE) method, Gappy POD method, and Discrete Empirical Interpolation Method (DEIM)- applied to a biological model describing the spatio-temporal dynamics of a predator-prey community. The comparative study is focused on the efficiency of the reduced-order approximations and the complexity reduction of the nonlinear terms. Different variants are discussed related to the projection-based model reduction framework combined with selective spatial sampling to efficiently perform the online computations. Numerical results are presented. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：32 / 43

页数：12

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