Application of Machine Learning in Composition and Process Design of Aluminum Matrix Composites

DU Xiaoshuang; QU Nan; ZHANG Xuexi; LIU Yong; ZHU Jingchuan

Volume 39 Issue 3

Jun. 2024

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Development and Application of Materials > 2024 > 39(3): 1-9.

DU Xiaoshuang, QU Nan, ZHANG Xuexi, LIU Yong, ZHU Jingchuan. Application of Machine Learning in Composition and Process Design of Aluminum Matrix Composites[J]. Development and Application of Materials, 2024, 39(3): 1-9.

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Application of Machine Learning in Composition and Process Design of Aluminum Matrix Composites

1. School of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China;
2. National Key Laboratory of Science and Technology on Precision Heat Processing of Metals, Harbin Institute of Technology, Harbin 150001, China

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Received Date: August 01, 2023
Available Online: July 22, 2024

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Abstract

Abstract

Aluminum matrix composites have excellent mechanical properties and have been applied in aviation, aerospace, national defense, automobile and other fields. Machine learning has great potential in the composition and process design of aluminum matrix composites. In this paper, the concept and common algorithms of machine learning are introduced, and then the application progress of machine learning in the research and development of aluminum matrix composites is discussed in detail from perspectives of performance prediction, component design, process design, and integrated design of material system and process. Finally, the future development and application of machine learning in the field of aluminum matrix composites are summarized and prospected.
- machine learning,
- aluminum matrix composites,
- performance prediction,
- component design,
- process design

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