Deep learning of thermodynamics-aware reduced-order models from data

3 July 2020

Papers citing "Deep learning of thermodynamics-aware reduced-order models from data"

9 / 9 papers shown

Title
Efficiently Parameterized Neural Metriplectic Systems Anthony Gruber Kookjin Lee Haksoo Lim Noseong Park Nathaniel Trask 65 1 0 28 Jan 2025
Predicting and explaining nonlinear material response using deep Physically Guided Neural Networks with Internal Variables Javier Orera-Echeverria J. Ayensa-Jiménez Manuel Doblaré 25 1 0 07 Aug 2023
A graph convolutional autoencoder approach to model order reduction for parametrized PDEs F. Pichi B. Moya J. Hesthaven AI4CE 38 52 0 15 May 2023
Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 27 13 0 03 Nov 2022
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks Valentin Duruisseaux J. Burby Q. Tang 33 11 0 11 Oct 2022
Evolution TANN and the identification of internal variables and evolution equations in solid mechanics Filippo Masi I. Stefanou AI4CE 24 30 0 27 Sep 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
Thermodynamics-informed graph neural networks Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto AI4CE PINN 32 31 0 03 Mar 2022
The mixed deep energy method for resolving concentration features in finite strain hyperelasticity J. Fuhg N. Bouklas PINN AI4CE 28 90 0 15 Apr 2021