Table of Contents
Fetching ...

Error Inhibiting Methods for Finite Elements

Adi Ditkowski, Anne Le Blanc, Chi-Wang Shu

TL;DR

This work develops Block Finite Difference (BFD) schemes for the heat equation, showing that BFD is a special case of a nodal-based Discontinuous Galerkin (DG) method and proving stability via DG techniques. A Fourier-like analysis identifies an optimal parameter choice that yields high-order convergence, and post-processing filters can further boost accuracy (up to 6th order in some cases). The framework is extended to two and three dimensions, with both periodic and Dirichlet boundary conditions handled through ghost-point extrapolation and corresponding DG formulations. The results demonstrate stable, high-order schemes that bridge finite difference and finite element perspectives, with practical gains for multi-dimensional parabolic problems and potential extensions to advection and complex geometries.

Abstract

Finite Difference methods (FD) are one of the oldest and simplest methods for solving partial differential equations (PDE). Block Finite Difference methods (BFD) are FD methods in which the domain is divided into blocks, or cells, containing two or more grid points, with a different scheme used for each grid point, unlike the standard FD method. It was shown in recent works that BFD schemes might be one to three orders more accurate than their truncation errors. Due to these schemes' ability to inhibit the accumulation of truncation errors, these methods were called Error Inhibiting Schemes (EIS). This manuscript shows that our BFD schemes can be viewed as a particular type of Discontinuous Galerkin (DG) method. Then, we prove the BFD scheme's stability using the standard DG procedure while using a Fourier-like analysis to establish its optimal convergence rate. We present numerical examples in one and two dimensions to demonstrate the efficacy of these schemes.

Error Inhibiting Methods for Finite Elements

TL;DR

This work develops Block Finite Difference (BFD) schemes for the heat equation, showing that BFD is a special case of a nodal-based Discontinuous Galerkin (DG) method and proving stability via DG techniques. A Fourier-like analysis identifies an optimal parameter choice that yields high-order convergence, and post-processing filters can further boost accuracy (up to 6th order in some cases). The framework is extended to two and three dimensions, with both periodic and Dirichlet boundary conditions handled through ghost-point extrapolation and corresponding DG formulations. The results demonstrate stable, high-order schemes that bridge finite difference and finite element perspectives, with practical gains for multi-dimensional parabolic problems and potential extensions to advection and complex geometries.

Abstract

Finite Difference methods (FD) are one of the oldest and simplest methods for solving partial differential equations (PDE). Block Finite Difference methods (BFD) are FD methods in which the domain is divided into blocks, or cells, containing two or more grid points, with a different scheme used for each grid point, unlike the standard FD method. It was shown in recent works that BFD schemes might be one to three orders more accurate than their truncation errors. Due to these schemes' ability to inhibit the accumulation of truncation errors, these methods were called Error Inhibiting Schemes (EIS). This manuscript shows that our BFD schemes can be viewed as a particular type of Discontinuous Galerkin (DG) method. Then, we prove the BFD scheme's stability using the standard DG procedure while using a Fourier-like analysis to establish its optimal convergence rate. We present numerical examples in one and two dimensions to demonstrate the efficacy of these schemes.
Paper Structure (25 sections, 85 equations, 9 figures)

This paper contains 25 sections, 85 equations, 9 figures.

Figures (9)

  • Figure 1: Error and Convergence plots, $\log_{10} \| {{\bf E}} \|$ vs. $\log_{10} h$ for 1D Heat Problem - Dirichlet boundary conditions. Left: without Post-Processing; right: with Post-Processing.
  • Figure 2: Grid in 2 Dimensions - Illustration
  • Figure 3: Illustration of the dependence on node ${{\bf x}} _{i-1/2,j-1/2}$ from neighbouring nodes in 2D
  • Figure 4: 2D Heat Problem - Two Points Block, BFD scheme - Periodic BC - Error at Final Time $T=1$ - $N=50$ - No post-processing
  • Figure 5: 2D Heat Problem - Two Points Block, BFD scheme, Convergence plots, $\log_{10} \| {{\bf E}} \|$ vs. $\log_{10} h$ - Periodic BC - Left: no post-processing; right: Spectral post-processing
  • ...and 4 more figures

Theorems & Definitions (1)

  • Definition 1: The Operator ${\Theta}_{j-1/2}$