Combined Regularization and Discretization of Equilibrium Problems and Primal-Dual Gap Estimators
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The present work aims at the application of finite element discretizations to a class of equilibrium problems involving moving constraints. Therefore, a Moreau–Yosida based regularization technique, controlled by a parameter, is discussed and, using a generalized Γ-convergence concept, a priori convergence results are derived. The latter technique is applied to the discretization of the regularized problems and is used to prove the convergence to the orginal equilibrium problem, when both – regularization and discretization – are imposed simultaneously. In addition, a primal-dual gap technique is used for the derivation of error estimators suitable for adaptive mesh refinement. A strategy for balancing between a refinement of the mesh and an update of the regularization parameter is established, too. The theoretical findings are illustrated for the obstacle problem as well as numerical experiments are performed for two quasi-variational inequalities with application to thermoforming and biomedicine, respectively.
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