Computational multiscale method for parabolic wave approximations in heterogeneous media

Eric Chung, Yalchin Efendiev, Sai-Mang Pun and Zecheng Zhang

Applied Mathematics and Computation, 2022, vol. 425, issue C

Abstract: In this paper, we develop a computational multiscale method to solve the parabolic wave approximation with heterogeneous and variable media. Parabolic wave approximation is a technique to approximate the full wave equation. One benefit of the method is that one wave propagation direction can be taken as an evolution direction, and one then can discretize it using a classical scheme like backward Euler method. Consequently, one obtains a set of quasi-gas-dynamic (QGD) models with possibly different heterogeneous permeability fields. For coarse discretization, we employ constraint energy minimization generalized multiscale finite element method (CEM-GMsFEM) to perform spatial model reduction. The resulting system can be solved by combining the central difference in time evolution. Due to the variable media, we apply the technique of proper orthogonal decomposition (POD) to further the dimension of the problem and solve the corresponding model problem in the POD space instead of in the whole multiscale space spanned by all possible multiscale basis functions. We prove the stability of the full discretization scheme and give the convergence analysis of the proposed approximation scheme. Numerical results verify the effectiveness of the proposed method.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:425:y:2022:i:c:s0096300322001308

DOI: 10.1016/j.amc.2022.127044

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