Title
Efficiency Based Adaptive Local Refinement for First-Order System Least-Squares Formulations
Abstract
In this paper, we propose new adaptive local refinement (ALR) strategies for first-order system least-squares finite elements in conjunction with algebraic multigrid methods in the context of nested iteration. The goal is to reach a certain error tolerance with the least amount of computational cost and nearly uniform distribution of the error over all elements. To accomplish this, the refinement decision at each refinement level is determined based on optimizing efficiency measures that take into account both error reduction and computational cost. Two efficiency measures are discussed: predicted error reduction and predicted computational cost. These methods are first applied to a two-dimensional (2D) Poisson problem with steep gradients, and the results are compared with the threshold-based methods described in [W. Dörfler, SIAM J. Numer. Anal., 33 (1996), pp. 1106-1124]. Next, these methods are applied to a 2D reduced model of the incompressible, resistive magnetohydrodynamic equations. These equations are used to simulate instabilities in a large aspect-ratio tokamak. We show that, by using the new ALR strategies on this system, we are able to resolve the physics using only 10 percent of the computational cost used to approximate the solutions on a uniformly refined mesh within the same error tolerance.
Year
DOI
Venue
2011
10.1137/100786897
SIAM J. Scientific Computing
Keywords
Field
DocType
first-order system least-squares formulations,refinement decision,efficiency measure,certain error tolerance,error reduction,adaptive local refinement,error tolerance,refinement level,computational cost,first-order system,new alr strategy,new adaptive local refinement,algebraic multigrid,magnetohydrodynamics
Least squares,Compressibility,Magnetohydrodynamic drive,Mathematical optimization,Resistive touchscreen,Uniform distribution (continuous),Algorithm,Finite element method,Nested iteration,Mathematics,Multigrid method
Journal
Volume
Issue
ISSN
33
1
1064-8275
Citations 
PageRank 
References 
14
0.92
11
Authors
6
Name
Order
Citations
PageRank
J. H. Adler15610.02
T. A. Manteuffel227838.19
S. F. McCormick326638.47
J. W. Nolting4140.92
J. Ruge529333.76
L. Tang6262.55