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Adaptive moving mesh algorithm based on local reaction rate

An empirical mesh adaption algorithm is introduced for modeling one-dimensional reaction-diffusion systems with large moving gradients. Our new algorithm is based on the revelation, that in reaction-diffusion systems the high moving concentration gradients appear nearby to the region where the rate...

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Detalles Bibliográficos
Autores principales: Koncz, Viktória, Izsák, Ferenc, Noszticzius, Zoltán, Kály-Kullai, Kristóf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820511/
https://www.ncbi.nlm.nih.gov/pubmed/33521342
http://dx.doi.org/10.1016/j.heliyon.2020.e05842
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author Koncz, Viktória
Izsák, Ferenc
Noszticzius, Zoltán
Kály-Kullai, Kristóf
author_facet Koncz, Viktória
Izsák, Ferenc
Noszticzius, Zoltán
Kály-Kullai, Kristóf
author_sort Koncz, Viktória
collection PubMed
description An empirical mesh adaption algorithm is introduced for modeling one-dimensional reaction-diffusion systems with large moving gradients. Our new algorithm is based on the revelation, that in reaction-diffusion systems the high moving concentration gradients appear nearby to the region where the rate of reaction is maximal, thus the local reaction rate can be used to control the mesh adaption. We found, that the main advantage of such a method is its simplicity and easy implementation. As an example we study an acid-base diode, where large moving gradients appear. The mathematical model of the diode contains several parabolic PDEs, coupled with one elliptic PDE. An r-refinement technique is used and attached to the commercial finite element solver COMSOL. We investigated the time-dependent salt effects of the diode with our developed algorithm. Our mesh adaption method is advantageous for modeling of any reaction-diffusion systems with localized high concentration gradients.
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spelling pubmed-78205112021-01-29 Adaptive moving mesh algorithm based on local reaction rate Koncz, Viktória Izsák, Ferenc Noszticzius, Zoltán Kály-Kullai, Kristóf Heliyon Research Article An empirical mesh adaption algorithm is introduced for modeling one-dimensional reaction-diffusion systems with large moving gradients. Our new algorithm is based on the revelation, that in reaction-diffusion systems the high moving concentration gradients appear nearby to the region where the rate of reaction is maximal, thus the local reaction rate can be used to control the mesh adaption. We found, that the main advantage of such a method is its simplicity and easy implementation. As an example we study an acid-base diode, where large moving gradients appear. The mathematical model of the diode contains several parabolic PDEs, coupled with one elliptic PDE. An r-refinement technique is used and attached to the commercial finite element solver COMSOL. We investigated the time-dependent salt effects of the diode with our developed algorithm. Our mesh adaption method is advantageous for modeling of any reaction-diffusion systems with localized high concentration gradients. Elsevier 2021-01-19 /pmc/articles/PMC7820511/ /pubmed/33521342 http://dx.doi.org/10.1016/j.heliyon.2020.e05842 Text en © 2020 Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Koncz, Viktória
Izsák, Ferenc
Noszticzius, Zoltán
Kály-Kullai, Kristóf
Adaptive moving mesh algorithm based on local reaction rate
title Adaptive moving mesh algorithm based on local reaction rate
title_full Adaptive moving mesh algorithm based on local reaction rate
title_fullStr Adaptive moving mesh algorithm based on local reaction rate
title_full_unstemmed Adaptive moving mesh algorithm based on local reaction rate
title_short Adaptive moving mesh algorithm based on local reaction rate
title_sort adaptive moving mesh algorithm based on local reaction rate
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820511/
https://www.ncbi.nlm.nih.gov/pubmed/33521342
http://dx.doi.org/10.1016/j.heliyon.2020.e05842
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