307
Views
8
CrossRef citations to date
0
Altmetric
Original Articles

Efficient time discretization scheme for nonlinear space fractional reaction–diffusion equations

, , , &
Pages 1274-1291 | Received 27 Mar 2017, Accepted 29 Sep 2017, Published online: 29 Nov 2017
 

ABSTRACT

We present a novel Exponential Time Differencing (ETD) scheme for nonlinear Riesz space fractional reaction–diffusion equations. This scheme is based on using a real distinct poles (RDP) discretization for the underlying matrix exponentials. Due to these RDP, the algorithm could be easily implemented in parallel to take advantage of multiple processors for increased computational efficiency. The method is established to be second-order convergent; and proven to be robust for problems involving non-smooth/mismatched initial and boundary conditions and steep solution gradients. We examine the stability of the scheme through its amplification factor and plot the boundaries of the stability regions comparative to other second-order ETD schemes. This numerical scheme combined with fractional central differencing is used for simulating some nonlinear space fractional problems. We demonstrate the superiority of our method over competing second-order ETD schemes, BDF2 scheme, and IMEX schemes. Our experiments show that the proposed scheme is computationally more efficient (in terms of cpu time). Furthermore, we investigate the trade-off between using fractional central differencing and matrix transfer technique in discretization of Riesz fractional derivatives.

2010 AMS SUBJECT CLASSIFICATIONS:

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.