Goal-oriented error estimation and iteration errors estimates for p-Laplace problems

DI Bernhard Endtmayer BSc

Dec. 5, 2017, 3:30 p.m. S2 416-1

In this presentation, we design a posteriori error estimates and mesh adaptivity for multiple
goal functionals for nonlinear problems. We use a dual-weighted residual approach in which
localization is achieved in a variational form using a partition-of-unity. The key advantage is
that the method is simple to implement and backward integration by parts is not required.
The adjoint to the adjoint problem as it has to be computed in [1], is required in the dual
weighted residual method is as in [2] anyway. Our algorithmic developments are substantiated
for p-Laplace problems in terms of some different numerical tests that cover various types of
challenges, such as singularities, different boundary conditions, and diverse goal functionals.