We review and extend the theory and methodology of a posteriori error estimation and adaptivity for modeling error for certain classes of problems in linear and
nonlinear mechanics. The basic idea is that for a given collection of physical phenomena a rich class of mathematical models can be identified, including models that
are sufficiently refined and validated that they satisfactorily capture the events of interest. These fine models may be intractable, too complex to solve by existing means.
Coarser models are therefore used. Moreover, as is frequently the case in applications, there are specific quantities of interest that are sought which are functionals
of the solution of the fine model. In this paper, techniques for estimating modeling
errors in such quantities of interest are developed. Applications to solid and fluid
mechanics are presented.
%0 Journal Article
%1 citeulike:3415660
%A Oden, J. Tinsley
%A Prudhomme, Serge
%D 2002
%J Journal of Computational Physics
%K 93a13-hierarchical-systems 74b20-nonlinear-elasticity 65n15-pdes-bvps-error-bounds 74s05-finite-element-methods-for-solid-mechanics
%N 2
%P 496--515
%R 10.1006/jcph.2002.7183
%T Estimation of Modeling Error in Computational Mechanics
%U http://dx.doi.org/10.1006/jcph.2002.7183
%V 182
%X We review and extend the theory and methodology of a posteriori error estimation and adaptivity for modeling error for certain classes of problems in linear and
nonlinear mechanics. The basic idea is that for a given collection of physical phenomena a rich class of mathematical models can be identified, including models that
are sufficiently refined and validated that they satisfactorily capture the events of interest. These fine models may be intractable, too complex to solve by existing means.
Coarser models are therefore used. Moreover, as is frequently the case in applications, there are specific quantities of interest that are sought which are functionals
of the solution of the fine model. In this paper, techniques for estimating modeling
errors in such quantities of interest are developed. Applications to solid and fluid
mechanics are presented.
@article{citeulike:3415660,
abstract = {{We review and extend the theory and methodology of a posteriori error estimation and adaptivity for modeling error for certain classes of problems in linear and
nonlinear mechanics. The basic idea is that for a given collection of physical phenomena a rich class of mathematical models can be identified, including models that
are sufficiently refined and validated that they satisfactorily capture the events of interest. These fine models may be intractable, too complex to solve by existing means.
Coarser models are therefore used. Moreover, as is frequently the case in applications, there are specific quantities of interest that are sought which are functionals
of the solution of the fine model. In this paper, techniques for estimating modeling
errors in such quantities of interest are developed. Applications to solid and fluid
mechanics are presented.}},
added-at = {2017-06-29T07:13:07.000+0200},
author = {Oden, J. Tinsley and Prudhomme, Serge},
biburl = {https://www.bibsonomy.org/bibtex/2ead7ff673ff3c0670b9d1143dc2ea161/gdmcbain},
citeulike-article-id = {3415660},
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citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=637627.637633},
citeulike-linkout-1 = {http://dx.doi.org/10.1006/jcph.2002.7183},
day = 01,
doi = {10.1006/jcph.2002.7183},
file = {oden_02_estimation_1085546.pdf},
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issn = {00219991},
journal = {Journal of Computational Physics},
keywords = {93a13-hierarchical-systems 74b20-nonlinear-elasticity 65n15-pdes-bvps-error-bounds 74s05-finite-element-methods-for-solid-mechanics},
month = nov,
number = 2,
pages = {496--515},
posted-at = {2016-10-04 04:40:14},
priority = {2},
timestamp = {2019-04-16T07:26:49.000+0200},
title = {{Estimation of Modeling Error in Computational Mechanics}},
url = {http://dx.doi.org/10.1006/jcph.2002.7183},
volume = 182,
year = 2002
}