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The gradient discretisation method
This monograph presents the Gradient Discretisation Method (GDM), which is a unified convergence analysis framework for numerical methods for elliptic and parabolic partial differential equations. The results obtained by the GDM cover both stationary and transient models; error estimates are provide...
Autores principales: | , , , , |
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Lenguaje: | eng |
Publicado: |
Springer
2018
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-3-319-79042-8 http://cds.cern.ch/record/2633932 |
_version_ | 1780959664773529600 |
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author | Droniou, Jérôme Eymard, Robert Gallouët, Thierry Guichard, Cindy Herbin, Raphaèle |
author_facet | Droniou, Jérôme Eymard, Robert Gallouët, Thierry Guichard, Cindy Herbin, Raphaèle |
author_sort | Droniou, Jérôme |
collection | CERN |
description | This monograph presents the Gradient Discretisation Method (GDM), which is a unified convergence analysis framework for numerical methods for elliptic and parabolic partial differential equations. The results obtained by the GDM cover both stationary and transient models; error estimates are provided for linear (and some non-linear) equations, and convergence is established for a wide range of fully non-linear models (e.g. Leray–Lions equations and degenerate parabolic equations such as the Stefan or Richards models). The GDM applies to a diverse range of methods, both classical (conforming, non-conforming, mixed finite elements, discontinuous Galerkin) and modern (mimetic finite differences, hybrid and mixed finite volume, MPFA-O finite volume), some of which can be built on very general meshes.<span style="font-family:" ms="" mincho";mso-bidi-font-family:="" the="" core="" properties="" and="" analytical="" tools="" required="" to="" work="" within="" gdm="" are="" stressed,="" it="" is="" shown="" that="" scheme="" convergence="" can="" often="" be="" established="" by="" verifying="" a="" small="" number="" of="" properties.="" scope="" some="" featured="" techniques="" results,="" such="" as="" time-space="" compactness="" theorems="" (discrete="" aubin–simon,="" discontinuous="" ascoli–arzela),="" goes="" beyond="" gdm,="" making="" them="" potentially="" applicable="" numerical="" schemes="" not="" (yet)="" known="" fit="" into="" this="" framework.<span style="font-family:" ms="" mincho";mso-bidi-font-family:="" this="" monograph="" is="" intended="" for="" graduate="" students,="" researchers="" and="" experts="" in="" the="" field="" of="" numerical="" analysis="" partial="" differential="" equations. |
id | cern-2633932 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2018 |
publisher | Springer |
record_format | invenio |
spelling | cern-26339322021-04-21T18:44:55Zdoi:10.1007/978-3-319-79042-8http://cds.cern.ch/record/2633932engDroniou, JérômeEymard, RobertGallouët, ThierryGuichard, CindyHerbin, RaphaèleThe gradient discretisation methodMathematical Physics and MathematicsThis monograph presents the Gradient Discretisation Method (GDM), which is a unified convergence analysis framework for numerical methods for elliptic and parabolic partial differential equations. The results obtained by the GDM cover both stationary and transient models; error estimates are provided for linear (and some non-linear) equations, and convergence is established for a wide range of fully non-linear models (e.g. Leray–Lions equations and degenerate parabolic equations such as the Stefan or Richards models). The GDM applies to a diverse range of methods, both classical (conforming, non-conforming, mixed finite elements, discontinuous Galerkin) and modern (mimetic finite differences, hybrid and mixed finite volume, MPFA-O finite volume), some of which can be built on very general meshes.<span style="font-family:" ms="" mincho";mso-bidi-font-family:="" the="" core="" properties="" and="" analytical="" tools="" required="" to="" work="" within="" gdm="" are="" stressed,="" it="" is="" shown="" that="" scheme="" convergence="" can="" often="" be="" established="" by="" verifying="" a="" small="" number="" of="" properties.="" scope="" some="" featured="" techniques="" results,="" such="" as="" time-space="" compactness="" theorems="" (discrete="" aubin–simon,="" discontinuous="" ascoli–arzela),="" goes="" beyond="" gdm,="" making="" them="" potentially="" applicable="" numerical="" schemes="" not="" (yet)="" known="" fit="" into="" this="" framework.<span style="font-family:" ms="" mincho";mso-bidi-font-family:="" this="" monograph="" is="" intended="" for="" graduate="" students,="" researchers="" and="" experts="" in="" the="" field="" of="" numerical="" analysis="" partial="" differential="" equations.Springeroai:cds.cern.ch:26339322018 |
spellingShingle | Mathematical Physics and Mathematics Droniou, Jérôme Eymard, Robert Gallouët, Thierry Guichard, Cindy Herbin, Raphaèle The gradient discretisation method |
title | The gradient discretisation method |
title_full | The gradient discretisation method |
title_fullStr | The gradient discretisation method |
title_full_unstemmed | The gradient discretisation method |
title_short | The gradient discretisation method |
title_sort | gradient discretisation method |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-3-319-79042-8 http://cds.cern.ch/record/2633932 |
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