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Data-driven anisotropic plasticity via Input-Convex Neural Network and Equivalent Plastic Work
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DOI：10.1016/j.eml.2026.102483.png)
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Abstract
En 中文
• EPW–ICNN framework for anisotropic plasticity with globally convex yield function. • Numerical examples show consistent accuracy against FE reference. • Two–stage workflow for robust calibration with limited tests. • Closed-form elastoplastic tangent ensures stable and rapid convergence.
Keywords:
Anisotropic plasticity
Input-Convex Neural Network
Equivalent Plastic Work
Convex yield function
Numerical calibration
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