128
Views
5
CrossRef citations to date
0
Altmetric
Original Articles

The BDF orthogonal spline collocation method for the two-dimensional evolution equation with memory

&
Pages 2011-2025 | Received 31 Dec 2016, Accepted 14 May 2017, Published online: 10 Jul 2017
 

ABSTRACT

In this paper, a second-order backward differentiation formula (BDF) orthogonal spline collocation (OSC) method with the truncation error of order 32 in time and hr+1 in space is presented for a kind of partial differential equation (PDE) with memory. The stability and convergence of the BDF OSC method in a new norm are proved. Besides, we provide three numerical experiments to demonstrate the results of theoretical analysis and show the accuracy and effectiveness of the BDF OSC method. Numerical experiments also exhibit the optimal error estimates in the L2, L and H1-norms.

2010 MSC SUBJECT CLASSIFICATIONS:

Acknowledgements

The authors thank the anonymous reviewers for their invaluable comments and suggestions, and thank Prof. Graeme Fairweather for stimulating discussions and for his constant encouragement and support.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work was supported by the National Natural Science Foundation of China [grant numbers 11601144, 11626096]; the Scientific Research Fund of Hunan Provincial Education Department [grant numbers 16K026, 15C0388, 15C0390, YB2016B033]; and the China Postdoctoral Science Foundation [grant number 2016M600964].

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.