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Machine learning corrects indentation size effect in steels with small datasets

作者 PulseAugur 编辑部 · [3 个来源] ·

Researchers have developed a data-efficient method for correcting the indentation size effect (ISE) in steels using machine learning and physics-guided augmentation. By augmenting a dataset of approximately 700 experimental indentations, they trained a constrained neural network to predict reference hardness, achieving high accuracy ($R^2 > 0.98$) and stable estimates even in the shallow indentation regime. This approach offers a pathway for data-efficient mechanical characterization of volume-constrained materials. AI

影响 Provides a novel data-efficient workflow for materials characterization, potentially applicable beyond steels.

排序理由 Academic paper detailing a new machine learning methodology for materials science.

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Machine learning corrects indentation size effect in steels with small datasets

报道来源 [3]

  1. arXiv cs.LG TIER_1 English(EN) · Radmir Karamov, Tagir Karamov ·

    Data-Efficient Indentation Size Effect Correction in Steels Using Machine Learning and Physics-Guided Augmentation

    arXiv:2604.27775v1 Announce Type: cross Abstract: Shallow nanoindentation enables mechanical characterization of thin films, individual phases and other volume-constrained materials, but measured hardness is often inflated by the indentation size effect (ISE), contact-area errors…

  2. arXiv cs.LG TIER_1 English(EN) · Tagir Karamov ·

    Data-Efficient Indentation Size Effect Correction in Steels Using Machine Learning and Physics-Guided Augmentation

    Shallow nanoindentation enables mechanical characterization of thin films, individual phases and other volume-constrained materials, but measured hardness is often inflated by the indentation size effect (ISE), contact-area errors and tip-geometry artifacts. Classical ISE correct…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    Data-Efficient Indentation Size Effect Correction in Steels Using Machine Learning and Physics-Guided Augmentation

    Shallow nanoindentation enables mechanical characterization of thin films, individual phases and other volume-constrained materials, but measured hardness is often inflated by the indentation size effect (ISE), contact-area errors and tip-geometry artifacts. Classical ISE correct…

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