Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems
DOI10.1007/s00466-023-02296-warXiv2211.01873MaRDI QIDQ6164288
Francisco Chinesta, Quercus Hernández, Alberto Badías, Elias Cueto
Publication date: 27 July 2023
Published in: Computational Mechanics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2211.01873
port-Hamiltonian formalismscientific machine learningdouble thermoelastic pendulumthermodynamics principleviscoelastic beam interaction
Artificial neural networks and deep learning (68T07) Learning and adaptive systems in artificial intelligence (68T05) Rods (beams, columns, shafts, arches, rings, etc.) (74K10) Thermodynamics in solid mechanics (74A15) Thermal effects in solid mechanics (74F05) Numerical and other methods in solid mechanics (74S99)
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