The overall effectiveness of finite element methods may be limited by solutions that
lack smoothness on a relatively small subset of the domain. In particular, standard
least squares finite element methods applied to problems with singular solutions may
exhibit slow convergence or, in some cases, may fail to converge. By enhancing the
norm used in the least squares functional with weight functions chosen according to a
coarse-scale approximation, it is possible to recover near-optimal convergence
rates without relying on exotic finite element spaces or specialized meshing
strategies. In this paper we describe an adaptive algorithm where appropriate
weight functions are generated from a coarse-scale approximate solution.
Several numerical tests, both linear and nonlinear, illustrate the robustness of
the adaptively weighted approach compared with the analogous standard
least
squares finite element approach.
Keywords
adaptive finite element methods, weighted norm
minimization, singularities