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...
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Online Access: | https://dx.doi.org/10.3929/ethz-b-000122284 http://hdl.handle.net/20.500.11850/122284 |
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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) |
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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 |