Two‐sided Krylov enhanced proper orthogonal decomposition methods for partial differential equations with variable coefficients

Author:

Wang Li1,Miao Zhen2ORCID,Jiang Yao‐Lin3ORCID

Affiliation:

1. School of Mathematics and Statistics Ningxia University Ningxia Yinchuan China

2. School of Mathematics and Statistics Northwestern Polytechnical University Xi'an Shaanxi China

3. School of Mathematics and Statistics Xi'an Jiaotong University Xi'an Shaanxi China

Abstract

AbstractIn this paper, new fast computing methods for partial differential equations with variable coefficients are studied and analyzed. They are two kinds of two‐sided Krylov enhanced proper orthogonal decomposition (KPOD) methods. First, the spatial discrete scheme of an advection‐diffusion equation is obtained by Galerkin approximation. Then, an algorithm based on a two‐sided KPOD approach involving the block Arnoldi and block Lanczos processes for the obtained time‐varying equations is put forward. Moreover, another type of two‐sided KPOD algorithm based on Laguerre orthogonal polynomials in frequency domain is provided. For the two kinds of two‐sided KPOD methods, we present a theoretical analysis for the moment matching of the discrete time‐invariant transfer function in time domain and give the error bound caused by the reduced‐order projection between the Galerkin finite element solution and the approximate solution of the two‐sided KPOD method. Finally, the feasibility of four two‐sided KPOD algorithms is verified by several numerical results with different inputs and setting parameters.

Publisher

Wiley

Subject

Applied Mathematics,Computational Mathematics,Numerical Analysis,Analysis

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