A framework using input convex neural networks to represent internal energy and dissipation potential for discovering thermomechanical constitutive models while guaranteeing thermodynamic admissibility by construction.
Kalina, Jörg Brummund, Brain Riemer, and Markus Kästner
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CE 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A Convex Route to Thermomechanics: Learning Internal Energy and Dissipation
A framework using input convex neural networks to represent internal energy and dissipation potential for discovering thermomechanical constitutive models while guaranteeing thermodynamic admissibility by construction.