scholarly journals A Local-in-Space-Timestep Approach to a Finite Element Discretization of the Heat Equation with a Posteriori Estimates

2009 ◽  
Vol 47 (4) ◽  
pp. 3109-3138 ◽  
Author(s):  
Stefano Berrone
1999 ◽  
Vol 09 (02) ◽  
pp. 261-286 ◽  
Author(s):  
SLIMANE ADJERID ◽  
JOSEPH E. FLAHERTY ◽  
IVO BABUŠKA

Babuška and Yu constructed a posteriori estimates for finite element discretization errors of linear elliptic problems utilizing a dichotomy principal stating that the errors of odd-order approximations arise near element edges as mesh spacing decreases while those of even-order approximations arise in element interiors. We construct similar a posteriori estimates for the spatial errors of finite element method-of-lines solutions of linear parabolic partial differential equations on square-element meshes. Error estimates computed in this manner are proven to be asymptotically correct; thus, they converge in strain energy under mesh refinement at the same rate as the actual errors.


2006 ◽  
Vol 16 (02) ◽  
pp. 233-263 ◽  
Author(s):  
Z. BELHACHMI ◽  
C. BERNARDI ◽  
S. DEPARIS ◽  
F. HECHT

We consider the Stokes problem in a three-dimensional axisymmetric domain and, by writing the Fourier expansion of its solution with respect to the angular variable, we observe that each Fourier coefficient satisfies a system of equations on the meridian domain. We propose a discretization of this problem which combines Fourier truncation and finite element methods applied to each of the two-dimensional systems. We give the detailed a priori and a posteriori analyses of the discretization and present some numerical experiments which are in good agreement with the analysis.


Acta Numerica ◽  
1996 ◽  
Vol 5 ◽  
pp. 1-43 ◽  
Author(s):  
Randolph E. Bank

In this work we present a brief introduction to hierarchical bases, and the important part they play in contemporary finite element calculations. In particular, we examine their role in a posteriori error estimation, and in the formulation of iterative methods for solving the large sparse sets of linear equations arising from finite element discretization.


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