Computable error estimators for the approximation of nonlinear
problems by linearized models
Alexandra Chaillou and Manil Suri
In the modeling of nonlinear phenomena, a nonlinear model may often be
replaced by a linear one, giving rise to a modeling or linearization
error. This is in addition to the discretization error introduced
when this linear model is solved, using, e.g, the finite element method.
We investigate the a posteriori estimation of these errors for a
general class of problems characterized by strongly monotone operators.
Our results lead to the construction of guaranteed computable
upper estimators for the total error, with identifiable components
from each of the these error sources. Several numerical tests
evaluating the efficiency of our estimators are provided.