A novel localized least-squares collocation method for coupled bulk-surface problems

Zhuochao Tang, Zhuojia Fu*, Meng Chen*, Leevan Ling

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

In this paper, we present a novel least-squares formulation of the Generalized Finite Difference Method (GFDM) and utilize its high-order schemes to solve the coupled bulk-surface reaction-diffusion equations. The coupled bulk-surface problems are composed of bulk equations and surface equations and coupled via some Robin-type boundary conditions. For differential operators on curved surfaces, we focus on the extrinsic definition that defines the surface operators using projection operator to tangent spaces of the surface. By utilizing localization and FD data points, the coupled model is discretized as a large sparse system using the LS-GFDM with two sets of arbitrarily distributed points. Compared with the original GFDM, the LS-GFDM brings about the advantage that it gains flexibility to use FD data points at locations different from the unknown nodal solution values. Finally, numerical demonstrations and applications of Turing pattern formations verify the effectiveness and robustness of the proposed method.

Original languageEnglish
Article number129250
Number of pages16
JournalApplied Mathematics and Computation
Volume492
Early online date18 Dec 2024
DOIs
Publication statusE-pub ahead of print - 18 Dec 2024

Scopus Subject Areas

  • Computational Mathematics
  • Applied Mathematics

User-Defined Keywords

  • Least-squares
  • Laplace-Beltrami operator
  • Extrinsic
  • Bulk-surface equations
  • Pattern formations

Fingerprint

Dive into the research topics of 'A novel localized least-squares collocation method for coupled bulk-surface problems'. Together they form a unique fingerprint.

Cite this