A thermodynamics-constrained ML framework learns robust, consistent constitutive models for inelastic materials from macroscopic stress-strain data and generalizes to unseen paths.
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Learning inelastic constitutive models from stress-strain data under hard thermodynamic constraints
A thermodynamics-constrained ML framework learns robust, consistent constitutive models for inelastic materials from macroscopic stress-strain data and generalizes to unseen paths.