In this article, we derive an a posteriori error estimator for various discontinuous Galerkin (DG) methods that are proposed in (Wang, Han and Cheng, SIAM J. Numer. Anal., 48:708-733, 2010) for an elliptic obstacle problem. Using a key property of DG methods, we perform the analysis in a general framework. The error estimator we have obtained for DG methods is comparable with the estimator for the conforming Galerkin (CG) finite element method. In the analysis, we construct a non-linear smoothing function mapping DG finite element space to CG finite element space and use it as a key tool. The error estimator consists of a discrete Lagrange multiplier associated with the obstacle constraint. It is shown for non-over-penalized DG methods that the discrete Lagrange multiplier is uniformly stable on non-uniform meshes. Finally, numerical results demonstrating the performance of the error estimator are presented.

A reliable and efficient a posteriori error estimator is derived for a class of discontinuous Galerkin (DG) methods for the Signorini problem. A common property shared by many DG methods leads to a unified error analysis with the help of a constraint preserving enriching map. The error estimator of DG methods is comparable with the error estimator of the conforming methods. Numerical experiments illustrate the performance of the error estimator.

We revisit the a posteriori error analysis of discontinuous Galerkin methods for the obstacle problem derived in [25]. Under a mild assumption on the trace of obstacle, we derive a reliable a posteriori error estimator which does not involve min/max functions. A key in this approach is an auxiliary problem with discrete obstacle. Applications to various discontinuous Galerkin finite element methods are presented. Numerical experiments show that the new estimator obtained in this article performs better.2010 Mathematical subject classification: 65N30, 65N15.

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A residual based a posteriori error estimator is derived for a quadratic finite element method (fem) for the elliptic obstacle problem. The error estimator involves various residuals consisting the data of the problem, discrete solution and a Lagrange multiplier related to the obstacle constraint. A priori error estimates for the Lagrange multiplier have been derived and further under an assumption that the contact set does not degenerate to a curve in any part of the domain, optimal order a priori error estimates have been derived whenever the data and the solution are sufficiently regular, precisely, under the sufficient conditions required for quadratic fem in the case of linear elliptic problem. The numerical experiments of adaptive fem for a model problem satisfying the above condition on contact set show optimal order convergence. This demonstrates that the quadratic fem for obstacle problem can exhibit optimal performance. 1991 Mathematics Subject Classification. 65N30, 65N15. Key words and phrases. finite element, quadratic fem, a posteriori error estimate, obstacle problem, optimal error estimates, variational inequalities, Lagrange multiplier.