150
Views
8
CrossRef citations to date
0
Altmetric
Original Articles

A robust domain decomposition algorithm for singularly perturbed semilinear systems

&
Pages 1108-1122 | Received 25 Dec 2014, Accepted 30 Jan 2016, Published online: 20 May 2016
 

ABSTRACT

We consider a system of M(2) singularly perturbed semilinear reaction–diffusion equations. To solve this system numerically we develop an overlapping Schwarz domain decomposition algorithm, where we use the asymptotic behaviour of the exact solution for domain partitioning as well as to construct the iterative algorithm. The algorithm is analysed by defining some auxiliary problems, that allows to prove the uniform convergence of the method in two steps, splitting the discretization error and the iteration error. It is shown that the algorithm gives almost fourth uniform numerical approximations for the exact solution. More importantly, it is shown that for small values of the perturbation parameter just one iteration is required to achieve the almost fourth-order accuracy. Numerical results support our theoretical findings.

AMS SUBJECT CLASSIFICATIONS:

Acknowledgments

The authors gratefully acknowledge the valuable comments and suggestions from the anonymous referees.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,129.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.