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.
Reduced and all-at-once approaches for model calibration and discovery in computational solid mechanics.Applied Mechanics Reviews, 77(4):040801, 05 2025
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.