A Lagrangian Scheme for the Solution of Nonlinear Diffusion Equations Using Moving Simplex Meshes
A Lagrangian numerical scheme for solving nonlinear degenerate Fokker–Planck equations in space dimensions d ≥ 2 is presented. It applies to a large class of nonlinear diffusion equations, whose dynamics are driven by internal energies and given external potentials, e.g. the porous medium equation a...
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creator | Carrillo, José A. Düring, Bertram Matthes, Daniel McCormick, David S. |
description | A Lagrangian numerical scheme for solving nonlinear degenerate Fokker–Planck equations in space dimensions
d
≥
2
is presented. It applies to a large class of nonlinear diffusion equations, whose dynamics are driven by internal energies and given external potentials, e.g. the porous medium equation and the fast diffusion equation. The key ingredient in our approach is the gradient flow structure of the dynamics. For discretization of the Lagrangian map, we use a finite subspace of linear maps in space and a variational form of the implicit Euler method in time. Thanks to that time discretisation, the fully discrete solution inherits energy estimates from the original gradient flow, and these lead to weak compactness of the trajectories in the continuous limit. Consistency is analyzed in the planar situation,
d
=
2
. A variety of numerical experiments for the porous medium equation indicates that the scheme is well-adapted to track the growth of the solution’s support. |
doi_str_mv | 10.1007/s10915-017-0594-5 |
format | Article |
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d
≥
2
is presented. It applies to a large class of nonlinear diffusion equations, whose dynamics are driven by internal energies and given external potentials, e.g. the porous medium equation and the fast diffusion equation. The key ingredient in our approach is the gradient flow structure of the dynamics. For discretization of the Lagrangian map, we use a finite subspace of linear maps in space and a variational form of the implicit Euler method in time. Thanks to that time discretisation, the fully discrete solution inherits energy estimates from the original gradient flow, and these lead to weak compactness of the trajectories in the continuous limit. Consistency is analyzed in the planar situation,
d
=
2
. A variety of numerical experiments for the porous medium equation indicates that the scheme is well-adapted to track the growth of the solution’s support.</description><identifier>ISSN: 0885-7474</identifier><identifier>EISSN: 1573-7691</identifier><identifier>DOI: 10.1007/s10915-017-0594-5</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Algorithms ; Approximation ; Computational Mathematics and Numerical Analysis ; Diffusion ; Diffusion rate ; Discretization ; Entropy ; Finite volume method ; Fokker-Planck equation ; Gradient flow ; Mathematical analysis ; Mathematical and Computational Engineering ; Mathematical and Computational Physics ; Mathematics ; Mathematics and Statistics ; Porous media ; Theoretical ; Velocity</subject><ispartof>Journal of scientific computing, 2018-06, Vol.75 (3), p.1463-1499</ispartof><rights>The Author(s) 2017</rights><rights>The Author(s) 2017. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-b32ab9c189616b2083924ee844987c37650f71f4893e359a304368eee1d2be7d3</citedby><cites>FETCH-LOGICAL-c359t-b32ab9c189616b2083924ee844987c37650f71f4893e359a304368eee1d2be7d3</cites><orcidid>0000-0002-3601-2869 ; 0000-0001-8819-4660</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10915-017-0594-5$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2918312928?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,21367,27901,27902,33721,41464,42533,43781,51294</link.rule.ids></links><search><creatorcontrib>Carrillo, José A.</creatorcontrib><creatorcontrib>Düring, Bertram</creatorcontrib><creatorcontrib>Matthes, Daniel</creatorcontrib><creatorcontrib>McCormick, David S.</creatorcontrib><title>A Lagrangian Scheme for the Solution of Nonlinear Diffusion Equations Using Moving Simplex Meshes</title><title>Journal of scientific computing</title><addtitle>J Sci Comput</addtitle><description>A Lagrangian numerical scheme for solving nonlinear degenerate Fokker–Planck equations in space dimensions
d
≥
2
is presented. It applies to a large class of nonlinear diffusion equations, whose dynamics are driven by internal energies and given external potentials, e.g. the porous medium equation and the fast diffusion equation. The key ingredient in our approach is the gradient flow structure of the dynamics. For discretization of the Lagrangian map, we use a finite subspace of linear maps in space and a variational form of the implicit Euler method in time. Thanks to that time discretisation, the fully discrete solution inherits energy estimates from the original gradient flow, and these lead to weak compactness of the trajectories in the continuous limit. Consistency is analyzed in the planar situation,
d
=
2
. A variety of numerical experiments for the porous medium equation indicates that the scheme is well-adapted to track the growth of the solution’s support.</description><subject>Algorithms</subject><subject>Approximation</subject><subject>Computational Mathematics and Numerical Analysis</subject><subject>Diffusion</subject><subject>Diffusion rate</subject><subject>Discretization</subject><subject>Entropy</subject><subject>Finite volume method</subject><subject>Fokker-Planck equation</subject><subject>Gradient flow</subject><subject>Mathematical analysis</subject><subject>Mathematical and Computational Engineering</subject><subject>Mathematical and Computational Physics</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Porous media</subject><subject>Theoretical</subject><subject>Velocity</subject><issn>0885-7474</issn><issn>1573-7691</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>BENPR</sourceid><recordid>eNp1kMtOwzAQRS0EEqXwAewssTb4kcT2sirlIbWwKF1bTjpOU6VxaycI_p5EQWLFaqSZe-5IB6FbRu8ZpfIhMqpZSiiThKY6IekZmrBUCiIzzc7RhCqVEpnI5BJdxbinlGql-QTZGV7aMtimrGyD18UODoCdD7jdAV77umsr32Dv8Jtv6qoBG_Bj5VwXh_Xi1NnhHvEmVk2JV_5zGOvqcKzhC68g7iBeowtn6wg3v3OKNk-Lj_kLWb4_v85nS1KIVLckF9zmumBKZyzLOVVC8wRAJYlWshAyS6mTzCVKC-gBK2giMgUAbMtzkFsxRXdj7zH4UwexNXvfhaZ_abhmSjCuuepTbEwVwccYwJljqA42fBtGzWDSjCZNb9IMJk3aM3xkYp9tSgh_zf9DP82BdWg</recordid><startdate>20180601</startdate><enddate>20180601</enddate><creator>Carrillo, José A.</creator><creator>Düring, Bertram</creator><creator>Matthes, Daniel</creator><creator>McCormick, David S.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0002-3601-2869</orcidid><orcidid>https://orcid.org/0000-0001-8819-4660</orcidid></search><sort><creationdate>20180601</creationdate><title>A Lagrangian Scheme for the Solution of Nonlinear Diffusion Equations Using Moving Simplex Meshes</title><author>Carrillo, José A. ; Düring, Bertram ; Matthes, Daniel ; McCormick, David S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-b32ab9c189616b2083924ee844987c37650f71f4893e359a304368eee1d2be7d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Algorithms</topic><topic>Approximation</topic><topic>Computational Mathematics and Numerical Analysis</topic><topic>Diffusion</topic><topic>Diffusion rate</topic><topic>Discretization</topic><topic>Entropy</topic><topic>Finite volume method</topic><topic>Fokker-Planck equation</topic><topic>Gradient flow</topic><topic>Mathematical analysis</topic><topic>Mathematical and Computational Engineering</topic><topic>Mathematical and Computational Physics</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Porous media</topic><topic>Theoretical</topic><topic>Velocity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Carrillo, José A.</creatorcontrib><creatorcontrib>Düring, Bertram</creatorcontrib><creatorcontrib>Matthes, Daniel</creatorcontrib><creatorcontrib>McCormick, David S.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Journal of scientific computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Carrillo, José A.</au><au>Düring, Bertram</au><au>Matthes, Daniel</au><au>McCormick, David S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Lagrangian Scheme for the Solution of Nonlinear Diffusion Equations Using Moving Simplex Meshes</atitle><jtitle>Journal of scientific computing</jtitle><stitle>J Sci Comput</stitle><date>2018-06-01</date><risdate>2018</risdate><volume>75</volume><issue>3</issue><spage>1463</spage><epage>1499</epage><pages>1463-1499</pages><issn>0885-7474</issn><eissn>1573-7691</eissn><abstract>A Lagrangian numerical scheme for solving nonlinear degenerate Fokker–Planck equations in space dimensions
d
≥
2
is presented. It applies to a large class of nonlinear diffusion equations, whose dynamics are driven by internal energies and given external potentials, e.g. the porous medium equation and the fast diffusion equation. The key ingredient in our approach is the gradient flow structure of the dynamics. For discretization of the Lagrangian map, we use a finite subspace of linear maps in space and a variational form of the implicit Euler method in time. Thanks to that time discretisation, the fully discrete solution inherits energy estimates from the original gradient flow, and these lead to weak compactness of the trajectories in the continuous limit. Consistency is analyzed in the planar situation,
d
=
2
. A variety of numerical experiments for the porous medium equation indicates that the scheme is well-adapted to track the growth of the solution’s support.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10915-017-0594-5</doi><tpages>37</tpages><orcidid>https://orcid.org/0000-0002-3601-2869</orcidid><orcidid>https://orcid.org/0000-0001-8819-4660</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Approximation Computational Mathematics and Numerical Analysis Diffusion Diffusion rate Discretization Entropy Finite volume method Fokker-Planck equation Gradient flow Mathematical analysis Mathematical and Computational Engineering Mathematical and Computational Physics Mathematics Mathematics and Statistics Porous media Theoretical Velocity |
title | A Lagrangian Scheme for the Solution of Nonlinear Diffusion Equations Using Moving Simplex Meshes |
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