Mechanical error estimators for shallow ice flow models ...

We develop a posteriori ‘mechanical’ error estimators that are able to evaluate the solution discrepancy between two ice flow models. We first reformulate the classical shallow ice flow models by applying simplifications to the weak formulation of the Glen–Stokes model. This approach leads to a unif...

Full description

Bibliographic Details
Main Author: Jouvet, Guillaume
Format: Article in Journal/Newspaper
Language:English
Published: ETH Zurich 2016
Subjects:
Online Access:https://dx.doi.org/10.3929/ethz-b-000122284
http://hdl.handle.net/20.500.11850/122284
id ftdatacite:10.3929/ethz-b-000122284
record_format openpolar
spelling ftdatacite:10.3929/ethz-b-000122284 2024-04-28T08:24:56+00:00 Mechanical error estimators for shallow ice flow models ... Jouvet, Guillaume 2016 application/pdf https://dx.doi.org/10.3929/ethz-b-000122284 http://hdl.handle.net/20.500.11850/122284 en eng ETH Zurich Ice sheets Non-Newtonian flows Variational methods article-journal Text ScholarlyArticle Journal Article 2016 ftdatacite https://doi.org/10.3929/ethz-b-000122284 2024-04-02T12:32:08Z We develop a posteriori ‘mechanical’ error estimators that are able to evaluate the solution discrepancy between two ice flow models. We first reformulate the classical shallow ice flow models by applying simplifications to the weak formulation of the Glen–Stokes model. This approach leads to a unified hierarchical formulation which relates the Glen–Stokes model, the Blatter model, the shallow ice approximation and the shallow shelf approximation. Based on this formulation and on residual techniques commonly used to estimate numerical errors, we derive three a posteriori estimators, each of which compares a pair of models using measures of the velocity field from the simpler (shallower) model. Numerical experiments confirm that these estimators can be used to assess the validity of the shallow ice models that are commonly used in glacier and ice sheet modelling. ... : Journal of Fluid Mechanics, 807 ... Article in Journal/Newspaper Ice Sheet DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic Ice sheets
Non-Newtonian flows
Variational methods
spellingShingle Ice sheets
Non-Newtonian flows
Variational methods
Jouvet, Guillaume
Mechanical error estimators for shallow ice flow models ...
topic_facet Ice sheets
Non-Newtonian flows
Variational methods
description We develop a posteriori ‘mechanical’ error estimators that are able to evaluate the solution discrepancy between two ice flow models. We first reformulate the classical shallow ice flow models by applying simplifications to the weak formulation of the Glen–Stokes model. This approach leads to a unified hierarchical formulation which relates the Glen–Stokes model, the Blatter model, the shallow ice approximation and the shallow shelf approximation. Based on this formulation and on residual techniques commonly used to estimate numerical errors, we derive three a posteriori estimators, each of which compares a pair of models using measures of the velocity field from the simpler (shallower) model. Numerical experiments confirm that these estimators can be used to assess the validity of the shallow ice models that are commonly used in glacier and ice sheet modelling. ... : Journal of Fluid Mechanics, 807 ...
format Article in Journal/Newspaper
author Jouvet, Guillaume
author_facet Jouvet, Guillaume
author_sort Jouvet, Guillaume
title Mechanical error estimators for shallow ice flow models ...
title_short Mechanical error estimators for shallow ice flow models ...
title_full Mechanical error estimators for shallow ice flow models ...
title_fullStr Mechanical error estimators for shallow ice flow models ...
title_full_unstemmed Mechanical error estimators for shallow ice flow models ...
title_sort mechanical error estimators for shallow ice flow models ...
publisher ETH Zurich
publishDate 2016
url https://dx.doi.org/10.3929/ethz-b-000122284
http://hdl.handle.net/20.500.11850/122284
genre Ice Sheet
genre_facet Ice Sheet
op_doi https://doi.org/10.3929/ethz-b-000122284
_version_ 1797584925893853184