Saddle point least squares discretization for convection-diffusion

被引:1
|
作者
Bacuta, Constantin [1 ]
Hayes, Daniel [1 ]
O'Grady, Tyler [1 ]
机构
[1] Univ Delaware, Dept Math Sci, Newark, DE 19716 USA
关键词
Least squares; saddle point systems; up-winding Petrov Galerkin; optimal stability norm; convection dominated problem; FINITE-ELEMENT METHODS; DPG METHOD; STABILIZATION; CONVERGENCE; STABILITY; SPACES;
D O I
10.1080/00036811.2023.2291511
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We consider a model convection-diffusion problem and present our recent analysis and numerical results regarding mixed finite element formulation and discretization in the singular perturbed case when the convection term dominates the problem. Using the concepts of optimal norm and saddle point reformulation, we found new error estimates for the case of uniform meshes. We compare the standard linear Galerkin discretization to a saddle point least square discretization that uses quadratic test functions, and explain the non-physical oscillations of the discrete solutions. We also relate a known upwinding Petrov-Galerkin method and the stream-line diffusion discretization method, by emphasizing the resulting linear systems and by comparing appropriate error norms. The results can be extended to the multidimensional case in order to find efficient approximations for more general singular perturbed problems including convection dominated models.
引用
收藏
页码:2241 / 2268
页数:28
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