288 research outputs found
Convergence and optimality of the adaptive nonconforming linear element method for the Stokes problem
In this paper, we analyze the convergence and optimality of a standard
adaptive nonconforming linear element method for the Stokes problem. After
establishing a special quasi--orthogonality property for both the velocity and
the pressure in this saddle point problem, we introduce a new prolongation
operator to carry through the discrete reliability analysis for the error
estimator. We then use a specially defined interpolation operator to prove
that, up to oscillation, the error can be bounded by the approximation error
within a properly defined nonlinear approximate class. Finally, by introducing
a new parameter-dependent error estimator, we prove the convergence and
optimality estimates
Instance optimal Crouzeix-Raviart adaptive finite element methods for the Poisson and Stokes problems
We extend the ideas of Diening, Kreuzer, and Stevenson [Instance optimality
of the adaptive maximum strategy, Found. Comput. Math. (2015)], from conforming
approximations of the Poisson problem to nonconforming Crouzeix-Raviart
approximations of the Poisson and the Stokes problem in 2D. As a consequence,
we obtain instance optimality of an AFEM with a modified maximum marking
strategy
Convergence and optimality of the adaptive Morley element method
This paper is devoted to the convergence and optimality analysis of the
adaptive Morley element method for the fourth order elliptic problem. A new
technique is developed to establish a quasi-orthogonality which is crucial for
the convergence analysis of the adaptive nonconforming method. By introducing a
new parameter-dependent error estimator and further establishing a discrete
reliability property, sharp convergence and optimality estimates are then fully
proved for the fourth order elliptic problem
Convergence and optimality of an adaptive modified weak Galerkin finite element method
An adaptive modified weak Galerkin method (AmWG) for an elliptic problem is
studied in this paper, in addition to its convergence and optimality. The weak
Galerkin bilinear form is simplified without the need of the skeletal variable,
and the approximation space is chosen as the discontinuous polynomial space as
in the discontinuous Galerkin method. Upon a reliable residual-based a
posteriori error estimator, an adaptive algorithm is proposed together with its
convergence and quasi-optimality proved for the lowest order case. The major
tool is to bridge the connection between weak Galerkin method and the
Crouzeix-Raviart nonconforming finite element. Unlike the traditional
convergence analysis for methods with a discontinuous polynomial approximation
space, the convergence of AmWG is penalty parameter free
Adaptive Nonconforming Finite Element Approximation of Eigenvalue Clusters
This paper analyses an adaptive nonconforming finite element method for eigenvalue clusters of self-adjoint operators and proves optimal convergence rates (with respect to the concept of nonlinear approximation classes) for the approximation of the invariant subspace spanned by the eigenfunctions of the eigenvalue cluster. Applications include eigenvalues of the Laplacian and of the Stokes system
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