A posteriori error estimators for linear reduced-order models using Krylov-based integrators

被引：13
|
作者：
Amsallem, D. [1 ]
Hetmaniuk, U. [2 ]
机构：
[1] Stanford Univ, Dept Aeronaut & Astronaut, Stanford, CA 94305 USA
[2] Univ Washington, Dept Appl Math, Seattle, WA 98195 USA
来源：
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING | 2015年 / 102卷 / 05期
关键词：
projection-based model reduction; Petrov-Galerkin projection; error estimation; Krylov-based integrator; off-line; online decomposition; PROPER ORTHOGONAL DECOMPOSITION; COMPUTATIONAL-FLUID-DYNAMICS; REAL-TIME SOLUTION; BASIS APPROXIMATION; REDUCTION; EQUATIONS; SYSTEMS;
D O I：
10.1002/nme.4753
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Reduced-order models for linear time-invariant dynamical systems are considered, and the error between the full-order model and the reduced-order model solutions is characterized. Based on the analytical representation of the error, an a posteriori error indicator is proposed that combines a Krylov-based exponential integrator and an a posteriori residual-based estimate. Numerical experiments illustrate the quality of the error estimator. Copyright (c) 2014 John Wiley & Sons, Ltd.
引用
收藏
页码：1238 / 1261
页数：24
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