A posteriori estimation of the linearization error for strongly monotone nonlinear operators

We investigate the a posteriori estimation of the modeling (or linearization) error which arises when a nonlinear problem is replaced by a linear model. Using the context of strongly monotone operators, we construct a computable upper estimator for this error, and also provide an estimator that give...

Full description

Saved in:
Bibliographic Details
Published in:Journal of computational and applied mathematics 2007-08, Vol.205 (1), p.72-87
Main Authors: Chaillou, Alexandra, Suri, Manil
Format: Article
Language:English
Subjects:
A posteriori
Estimator
Exact sciences and technology
Linearization
Mathematical analysis
Mathematics
Nonlinear elasticity
Numerical analysis
Numerical analysis. Scientific computation
Operator theory
Sciences and techniques of general use
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We investigate the a posteriori estimation of the modeling (or linearization) error which arises when a nonlinear problem is replaced by a linear model. Using the context of strongly monotone operators, we construct a computable upper estimator for this error, and also provide an estimator that gives a lower bound. Several numerical results illustrating our theory are provided.
ISSN:0377-0427
1879-1778
DOI:10.1016/j.cam.2006.04.041