Data-Driven Anisotropic Biomembrane Simulation Based on the Laplace Stretch

Data-driven simulations are gaining popularity in mechanics of biomaterials since they do not require explicit form of constitutive relations. Data-driven modeling based on neural networks lacks interpretability. In this study, we propose an interpretable data-driven finite element modeling for hype...

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Main Authors: Alexey Liogky, Victoria Salamatova
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Computation
Subjects:
Online Access:https://www.mdpi.com/2079-3197/12/3/39
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author Alexey Liogky
Victoria Salamatova
author_facet Alexey Liogky
Victoria Salamatova
author_sort Alexey Liogky
collection DOAJ
description Data-driven simulations are gaining popularity in mechanics of biomaterials since they do not require explicit form of constitutive relations. Data-driven modeling based on neural networks lacks interpretability. In this study, we propose an interpretable data-driven finite element modeling for hyperelastic materials. This approach employs the Laplace stretch as the strain measure and utilizes response functions to define constitutive equations. To validate the proposed method, we apply it to inflation of anisotropic membranes on the basis of synthetic data for porcine skin represented by Holzapfel-Gasser-Ogden model. Our results demonstrate applicability of the method and show good agreement with reference displacements, although some discrepancies are observed in the stress calculations. Despite these discrepancies, the proposed method demonstrates its potential usefulness for simulation of hyperelastic biomaterials.
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spelling doaj.art-25094de1591946729aedcf7fe41992862024-03-27T13:31:53ZengMDPI AGComputation2079-31972024-02-011233910.3390/computation12030039Data-Driven Anisotropic Biomembrane Simulation Based on the Laplace StretchAlexey Liogky0Victoria Salamatova1Scientific Center for Information Technology and Artificial Intelligence, Sirius University of Science and Technology, 1 Olympiyskii pr., Sochi 354340, RussiaScientific Center for Information Technology and Artificial Intelligence, Sirius University of Science and Technology, 1 Olympiyskii pr., Sochi 354340, RussiaData-driven simulations are gaining popularity in mechanics of biomaterials since they do not require explicit form of constitutive relations. Data-driven modeling based on neural networks lacks interpretability. In this study, we propose an interpretable data-driven finite element modeling for hyperelastic materials. This approach employs the Laplace stretch as the strain measure and utilizes response functions to define constitutive equations. To validate the proposed method, we apply it to inflation of anisotropic membranes on the basis of synthetic data for porcine skin represented by Holzapfel-Gasser-Ogden model. Our results demonstrate applicability of the method and show good agreement with reference displacements, although some discrepancies are observed in the stress calculations. Despite these discrepancies, the proposed method demonstrates its potential usefulness for simulation of hyperelastic biomaterials.https://www.mdpi.com/2079-3197/12/3/39data-driven hyperelasticityLaplace stretchmembrane
spellingShingle Alexey Liogky
Victoria Salamatova
Data-Driven Anisotropic Biomembrane Simulation Based on the Laplace Stretch
Computation
data-driven hyperelasticity
Laplace stretch
membrane
title Data-Driven Anisotropic Biomembrane Simulation Based on the Laplace Stretch
title_full Data-Driven Anisotropic Biomembrane Simulation Based on the Laplace Stretch
title_fullStr Data-Driven Anisotropic Biomembrane Simulation Based on the Laplace Stretch
title_full_unstemmed Data-Driven Anisotropic Biomembrane Simulation Based on the Laplace Stretch
title_short Data-Driven Anisotropic Biomembrane Simulation Based on the Laplace Stretch
title_sort data driven anisotropic biomembrane simulation based on the laplace stretch
topic data-driven hyperelasticity
Laplace stretch
membrane
url https://www.mdpi.com/2079-3197/12/3/39
work_keys_str_mv AT alexeyliogky datadrivenanisotropicbiomembranesimulationbasedonthelaplacestretch
AT victoriasalamatova datadrivenanisotropicbiomembranesimulationbasedonthelaplacestretch