Hammering at the entropy: A GENERIC-guided approach to learning polymeric rheological constitutive equations using PINNs

We present a versatile framework that employs Physics-Informed Neural Networks (PINNs) to discover the entropic contribution that leads to the constitutive equation for the extra-stress in rheological models of polymer solutions. In this framework the training of the Neural Network is guided by an e...

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Veröffentlicht in:	arXiv.org 2024-09
Hauptverfasser:	David Nieto Simavilla, Bonfanti, Andrea, Imanol García de Beristain, Español, Pep, Ellero, Marco
Format:	Artikel
Sprache:	eng
Schlagworte:	Constitutive equations Constitutive models Constitutive relationships Equilibrium flow Exact solutions Mathematical models Neural networks Predictions Rheological properties Rheology Rheometry Steady state models Tensors Topology
Online-Zugang:	Volltext
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