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Author

L. Scheunemann

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Open access Sep 2026

Physics‐Informed Fourier Neural Operator for Predicting the Full‐Field Stress and Strain Response of Polycrystalline Microstructures

We develop a physics‐informed Fourier Neural Operator (PINO) for the surrogate modeling of full‐field responses in polycrystalline microstructures. Reference stress and strain fields are generated using an FFT‐based full‐field solver under prescribed macroscopic loading. The model maps the crystallographic orientatio...

Ahmad Awad, L. Scheunemann · 0 citations
#machine learning Preprint Sep 2026

Learning the Constitutive Behavior of Materials via Neural Operators and Causal Attention: Case Studies in Plasticity and Damage

A data-driven constitutive modeling framework based on the concept of a material operator is proposed, which treats a deforming material as a functional mapping from its entire strain history to the corresponding stress response, and demonstrates accurate and robust predictions of irreversible deformation mechanisms wh...

Rishabh Arora, L. Scheunemann, T. Brepols et al. · 0 citations

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