A nodally bound-preserving finite element method for time-dependent convection–diffusion equations

Abdolreza Amiri, Gabriel R. Barrenechea, Tristan Pryer

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a new method to approximate the time-dependent convection–diffusion equations using conforming finite element methods, ensuring that the discrete solution respects the physical bounds imposed by the differential equation. The method is built by defining, at each time step, a convex set of admissible finite element functions (that is, the ones that satisfy the global bounds at their degrees of freedom) and seeks for a discrete solution in this admissible set. A family of θ-schemes is used as time integrators, and well-posedness of the discrete schemes is proven for the whole family, but stability and optimal-order error estimates are proven for the implicit Euler scheme. Nevertheless, our numerical experiments show that the method also provides stable and optimally-convergent solutions when the Crank–Nicolson method is used.

Original languageEnglish
Article number116691
JournalJournal of Computational and Applied Mathematics
Volume470
Early online date17 Apr 2025
DOIs
Publication statusE-pub ahead of print - 17 Apr 2025

Data Availability Statement

No data was used for the research described in the article.

Funding

The work of AA, GRB, and TP has been partially supported by the Leverhulme Trust Research Project, United Kingdom Grant No. RPG-2021-238. TP is also partially supported by EPRSC grants EP/W026899/2, EP/X017206/1 and EP/X030067/1.

FundersFunder number
Engineering and Physical Sciences Research Council

Keywords

  • Positivity preservation
  • Stabilised finite-element approximation
  • Time-dependent convection–diffusion equation
  • Variational inequality

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'A nodally bound-preserving finite element method for time-dependent convection–diffusion equations'. Together they form a unique fingerprint.

Cite this