Preserving the accuracy of numerical methods discretizing anisotropic elliptic problems

11/26/2019
by   Chang Yang, et al.
0

In this paper we study the loss of precision of numerical methods discretizing anisotropic problems and propose alternative approaches free from this drawback. The deterioration of the accuracy is observed when the coordinates and the mesh are unrelated to the anisotropy direction. While this issue is commonly addressed by increasing the scheme approximation order, we demonstrate that, though the gains are evident, the precision of these numerical methods remain far from optimal and limited to moderate anisotropy strengths. This is analysed and explained by an amplification of the approximation error related to the anisotropy strength. We propose an approach consisting in the introduction of an auxiliary variable aimed at removing the amplification of the discretization error. By this means the precision of the numerical approximation is demonstrated to be independent of the anisotropy strength.

READ FULL TEXT
research
01/27/2021

A diffuse interface box method for elliptic problems

We introduce a diffuse interface box method (DIBM) for the numerical app...
research
03/06/2023

Numerical analysis of a nonsmooth quasilinear elliptic control problem: II. Finite element discretization and error estimates

In this paper, we carry out the numerical analysis of a nonsmooth quasil...
research
03/15/2023

Auxiliary Splines Space Preconditioning for B-Splines Finite Elements: The case of H(curl,Ω) and H(div,Ω) elliptic problems

This paper presents a study of large linear systems resulting from the r...
research
06/28/2023

A new error analysis for parabolic Dirichlet boundary control problems

In this paper, we consider the finite element approximation to a parabol...
research
07/13/2023

Optimal Algorithms for Numerical Integration: Recent Results and Open Problems

We present recent results on optimal algorithms for numerical integratio...
research
12/15/2020

Geometry-aligned moving frames by removing spurious divergence in curvilinear mesh with geometric approximation error

The vertices of curvilinear elements usually lie on the exact domain. Ho...
research
10/24/2022

Precision Machine Learning

We explore unique considerations involved in fitting ML models to data w...

Please sign up or login with your details

Forgot password? Click here to reset