A generalizable framework of solution-guided machine learning with application to nanoindentation of free-standing thin films-Reference-Cited by-同舟云学术

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A generalizable framework of solution-guided machine learning with application to nanoindentation of free-standing thin films

Published:2024-07 Issue: Volume:200 Page:111984
ISSN:0263-8231
Container-title:Thin-Walled Structures
language:en
Short-container-title:Thin-Walled Structures

Author:

Wang Ruijin,Ying Tianquan^ORCID,Chen Yang,Zhu Fangyan^ORCID,Leng Jiantao^ORCID,Chang Tienchong^ORCID,Zhang Tongyi,Gao Huajian

Funder

NSFC

Publisher

Elsevier BV

Reference76 articles.

1. A machine learning perspective on the inverse indentation problem: uniqueness, surrogate modeling, and learning elasto-plastic properties from pile-up;Jiao;J. Mech. Phys. Solids,2024

2. Unified machine-learning-based design method for normal and high strength steel I-section beam–columns;Su;Thin-Walled Struct.,2024

3. Extrapolative prediction of small-data molecular property using quantum mechanics-assisted machine learning;Shimakawa;Npj Comput. Mater.,2024

4. Prediction of shear capacity of steel channel sections using machine learning algorithms;Dissanayake;Thin-Walled Struct.,2022

5. Machine learning assisted prediction and analysis of in-plane elastic modulus of hybrid hierarchical square honeycombs;Yang;Thin-Walled Struct.,2024

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fracture Mechanisms and Crack Propagation in Monolayer Ti₃C₂T_x under Nanoindentation: The Influence of Surface Terminations and Vacancy Defects;ACS Applied Materials & Interfaces;2024-08-31

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