EconPapers    
Economics at your fingertips  
 

Higher order Galerkin–collocation time discretization with Nitsche’s method for the Navier–Stokes equations

Mathias Anselmann and Markus Bause

Mathematics and Computers in Simulation (MATCOM), 2021, vol. 189, issue C, 141-162

Abstract: We propose and study numerically the implicit approximation in time of the Navier–Stokes equations by a Galerkin–collocation method in time combined with inf–sup stable finite element methods in space. The conceptual basis of the Galerkin–collocation approach is the establishment of a direct connection between the Galerkin method and the classical collocation methods, with the perspective of achieving the accuracy of the former with reduced computational costs in terms of less complex algebraic systems of the latter. Regularity of higher order in time of the discrete solution is ensured further. As an additional ingredient, we employ Nitsche’s method to impose all boundary conditions in weak form with the perspective that evolving domains become feasible in the future. We carefully compare the performance properties of the Galerkin–collocation approach with a standard continuous Galerkin–Petrov method using piecewise linear polynomials in time, that is algebraically equivalent to the popular Crank–Nicholson scheme. The condition number of the arising linear systems after Newton linearization as well as the reliable approximation of the drag and lift coefficient for laminar flow around a cylinder (DFG flow benchmark with Re=100; cf. (Turek and Schäfer, 1996)) are investigated. The superiority of the Galerkin–collocation approach over the linear in time, continuous Galerkin–Petrov method is demonstrated therein.

Keywords: Navier–Stokes problem; Galerkin–collocation scheme; Nitsche’s method; Higher order approximation (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475420303827
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:189:y:2021:i:c:p:141-162

DOI: 10.1016/j.matcom.2020.10.027

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:matcom:v:189:y:2021:i:c:p:141-162