Data-Efficient Indentation Size Effect Mitigation in Steels Using Machine Learning and a Physics-Constrained Neural Network

arXiv:2604.27775 · cond-mat.mtrl-sci, cs.LG · Submitted 2026-04-30 · Read on arXiv

cond-mat.mtrl-sci, cs.LG

Submitted: 2026-04-30

Updated: 2026-10-19

Comments: v3: revised results. 32 pages (27 + 5-page supplement), 8 figures, 9 tables, 10 supplementary figures. Data and code: https://doi.org/10.5281/zenodo.23472790

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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