A Posteriori Error Estimation and Adaptivity

Marc Laforest, École Polytechnique de Montréal
Serge Prudhomme, École Polytechnique de Montréal
The complexity of contemporary numerical models has reached such a level that all means of improving the accuracy to cost ratio is necessary in order to produce timely and relevant predictions. Moreover, predictions are only useful when their variance can be ascertained. A posteriori error estimation, and its adjuvant technique, namely mesh and model adaptivity, are now established methods to improve the accuracy of simulations, although much still remains to be done.

The objective of this mini-symposium is to bring together researchers interested in the field of error estimation in Computational Science and Engineering to discuss novel approaches and challenges towards the application of a posteriori error estimation methods, such as to
• nonlinear problems;
• time-dependent problems;
• adaptive model reduction;
• mesh refinement strategies;
• error estimation in a probabilistic setting; and
• modeling error estimation and adaptive modeling.
The organizers will be accepting abstracts on these topics, in particular those that give emphasis to engineering applications.