[1]王海伟,叶波,冯晶,等.机器学习在钢铁材料研究中的应用综述[J].中国材料进展,2023,42(10):806-813.[doi:10.7502/j.issn.1674-3962.202112020]
　WANG Haiwei,YE Bo,FENG Jing,et al.Application of Machine Learning in Steel Materials: A Survey[J].MATERIALS CHINA,2023,42(10):806-813.[doi:10.7502/j.issn.1674-3962.202112020]
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机器学习在钢铁材料研究中的应用综述()
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中国材料进展[ISSN:1674-3962/CN:61-1473/TG]

卷:
42
期数:
2023年第10期
页码:
806-813
栏目:
出版日期:
2023-10-31

文章信息/Info

Title:
Application of Machine Learning in Steel Materials: A Survey
文章编号:
1674-3962(2023)10-0806-08
作者:
王海伟1; 2; 叶波1; 2; 冯晶3; 4; 种晓宇3; 4
1. 昆明理工大学信息工程与自动化学院，云南 昆明 650500 2. 昆明理工大学 云南省人工智能重点实验室，云南 昆明 650500 3. 昆明理工大学材料科学与工程学院，云南 昆明 650093 4. 昆明理工大学 材料基因工程重点实验室，云南 昆明 650093
Author(s):
WANG Haiwei1; 2;  YE Bo1; 2; FENG Jing3; 4;  CHONG Xiaoyu3; 4
1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China 2. Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming 650500, China 3. Faculty of Materials Science and Engineering, Kunming University of Science and Technology, Kunming 650093 China 4. Key Laboratory of Materials Genetic Engineering, Kunming University of Science and Technology, Kunming 650093, China
关键词:
钢铁; 机器学习; 特征选择; 性能预测; 材料设计
Keywords:
steels;  machine learning;  feature selection;  performance prediction;  materials design
分类号:
TP181
DOI:
10.7502/j.issn.1674-3962.202112020
文献标志码:
A
摘要:
钢铁是当今世界处于核心地位的金属材料，时代的快速发展对钢铁材料的性能有了新的要求。然而目前钢材的设计具有超过百万种元素和工艺参数的组合，通过传统实验试错法进行钢铁材料的设计与研发缓慢而昂贵。机器学习技术已广泛应用于指导材料设计中，成为材料研究的新兴方法和热门领域。对机器学习在钢铁材料研究中的应用进展进行综述，介绍了机器学习的工作流程和常用模型与算法，阐述了机器学习在钢铁材料特征选择、成分-工艺-性能预测、服役行为预测以及逆向设计方面的研究进展。最后，分析了机器学习技术在钢铁材料领域面临的问题并展望了其发展前景。
Abstract:
Steel is the core metal material in the world, and the rapid development of the times has new requirements for the properties of steel materials. However, the design of steel materials currently involves combinations of over millions of elements and process parameters, leading the design and development of steel materials by traditional trial-and-error method slower and more expensive.Machine learning technology has been widely used to guide the development and design of materials, which has emerged as a novel methodology and a trending domain in the field of materials research. In this paper, the application progress of machine learning in the research of steel materials were summarized, the working process and common algorithms of machine learning were introduced. Meanwhile, the research progress of machine learning in steel materials feature selection, composition-processperformance prediction, service behavior prediction and reverse design were reviewed. Finally, the problems of machine learning technology in the field of steel materials were analyzed and the development prospects were forecasted.

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备注/Memo

备注/Memo:
收稿日期：2021-12-26修回日期：2022-01-16 基金项目：国家自然科学基金资助项目（52001150） 第一作者：王海伟，男，1995年生，硕士 通讯作者：叶波，男，1978年生，教授，博士生导师， Email:yeripple@hotmail.com 种晓宇，男，1989年生，教授，博士生导师, Email:chongxiaoyu007@163.com
更新日期/Last Update: 2023-09-28