Wavelet-based Edge Multiscale Finite Element Methods for Singularly Perturbed Convection-Diffusion Equations
Shubin Fu, Eric Chung, Guanglian Li

TL;DR
This paper introduces a wavelet-based edge multiscale finite element method for efficiently solving singularly perturbed convection-diffusion equations, with proven convergence and verified numerical results in 2D and 3D.
Contribution
It develops a novel wavelet-based multiscale finite element approach with a local solution splitting and hierarchical basis approximation, ensuring robustness and convergence for challenging equations.
Findings
Proven convergence rate with minimal mesh restrictions.
Effective approximation of solution layers inside and outside boundary layers.
Validated performance through extensive 2D and 3D numerical tests.
Abstract
We propose a novel efficient and robust Wavelet-based Edge Multiscale Finite Element Method (WEMsFEM) motivated by \cite{MR3980476,GL18} to solve the singularly perturbed convection-diffusion equations. The main idea is to first establish a local splitting of the solution over a local region by a local bubble part and local Harmonic extension part, and then derive a global splitting by means of Partition of Unity. This facilitates a representation of the solution as a summation of a global bubble part and a global Harmonic extension part, where the first part can be computed locally in parallel. To approximate the second part, we construct an edge multiscale ansatz space locally with hierarchical bases as the local boundary data that has a guaranteed approximation rate \noteLg{both inside and outside of the layers}. The key innovation of this proposed WEMsFEM lies in a provable…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Mathematical Modeling in Engineering · Differential Equations and Numerical Methods · Advanced Numerical Methods in Computational Mathematics
