Data-Driven GENERIC Modeling of Poroviscoelastic Materials

Biphasic soft materials are challenging to model by nature. Ongoing efforts are targeting their effective modeling and simulation. This work uses experimental atomic force nanoindentation of thick hydrogels to identify the indentation forces are a function of the indentation depth. Later on, the ato...

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Autores principales: Ghnatios, Chady, Alfaro, Iciar, González, David, Chinesta, Francisco, Cueto, Elias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514510/
http://dx.doi.org/10.3390/e21121165
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author Ghnatios, Chady
Alfaro, Iciar
González, David
Chinesta, Francisco
Cueto, Elias
author_facet Ghnatios, Chady
Alfaro, Iciar
González, David
Chinesta, Francisco
Cueto, Elias
author_sort Ghnatios, Chady
collection PubMed
description Biphasic soft materials are challenging to model by nature. Ongoing efforts are targeting their effective modeling and simulation. This work uses experimental atomic force nanoindentation of thick hydrogels to identify the indentation forces are a function of the indentation depth. Later on, the atomic force microscopy results are used in a GENERIC general equation for non-equilibrium reversible–irreversible coupling (GENERIC) formalism to identify the best model conserving basic thermodynamic laws. The data-driven GENERIC analysis identifies the material behavior with high fidelity for both data fitting and prediction.
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spelling pubmed-75145102020-11-09 Data-Driven GENERIC Modeling of Poroviscoelastic Materials Ghnatios, Chady Alfaro, Iciar González, David Chinesta, Francisco Cueto, Elias Entropy (Basel) Article Biphasic soft materials are challenging to model by nature. Ongoing efforts are targeting their effective modeling and simulation. This work uses experimental atomic force nanoindentation of thick hydrogels to identify the indentation forces are a function of the indentation depth. Later on, the atomic force microscopy results are used in a GENERIC general equation for non-equilibrium reversible–irreversible coupling (GENERIC) formalism to identify the best model conserving basic thermodynamic laws. The data-driven GENERIC analysis identifies the material behavior with high fidelity for both data fitting and prediction. MDPI 2019-11-28 /pmc/articles/PMC7514510/ http://dx.doi.org/10.3390/e21121165 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ghnatios, Chady
Alfaro, Iciar
González, David
Chinesta, Francisco
Cueto, Elias
Data-Driven GENERIC Modeling of Poroviscoelastic Materials
title Data-Driven GENERIC Modeling of Poroviscoelastic Materials
title_full Data-Driven GENERIC Modeling of Poroviscoelastic Materials
title_fullStr Data-Driven GENERIC Modeling of Poroviscoelastic Materials
title_full_unstemmed Data-Driven GENERIC Modeling of Poroviscoelastic Materials
title_short Data-Driven GENERIC Modeling of Poroviscoelastic Materials
title_sort data-driven generic modeling of poroviscoelastic materials
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514510/
http://dx.doi.org/10.3390/e21121165
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AT chinestafrancisco datadrivengenericmodelingofporoviscoelasticmaterials
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