Plastic properties estimation of aluminum alloys using machine learning of ultrasonic and eddy current data-Reference-Cited by-同舟云学术

Plastic properties estimation of aluminum alloys using machine learning of ultrasonic and eddy current data

Published:2023-07 Issue: Volume:137 Page:102857
ISSN:0963-8695
Container-title:NDT & E International
language:en
Short-container-title:NDT & E International

Author:

Ryu Seongcheol,Park Seong-Hyun,Jhang Kyung-Young^ORCID

Funder

National Research Foundation of Korea

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Mechanical Engineering,Condensed Matter Physics,General Materials Science

Reference45 articles.

1. Application of Aluminum extrusions to automotive parts;Hashimoto;Kobelco Technol Rev,2017

2. Application trend of aluminum castings in automotive component;Jeon;J Korea Foundry Soc,2007

3. The development of material technology for weight reduction of automobile body and its applications;Lee,2002

4. Mechanical properties and formability of heat-treated 7000-Series high-strength aluminum alloy: experiments and finite element modeling;Lee;Met Mater Int,2019

5. Influence of chemical composition variation and heat treatment on microstructure and mechanical properties of 6xxx alloys;Mrówka-Nowotnik;Archives mater sci eng,2010

Cited by 6 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. Identifying grain size in ASTM A36 steel using ultrasonic backscattered signals and machine learning;NDT & E International;2024-10

2. A review of the microstructural contributions to the acoustic nonlinearity parameter measured with longitudinal and Rayleigh wave second harmonic generation in metals;NDT & E International;2024-03

3. Old but not obsolete: Dimensional analysis in nondestructive testing and evaluation;NDT & E International;2024-01

4. Intelligent Online Sensing of Defects Evolution in Metallic Materials during Plastic Deformation;Advanced Intelligent Systems;2023-12-26

5. Full-range stress–strain curve estimation of aluminum alloys using machine learning-aided ultrasound;Ultrasonics;2023-12