Modeling of Crack Susceptibility of Ni-Based Superalloy for Additive Manufacturing via Thermodynamic Calculation and Machine Learning
文献类型：期刊论文
| 作者 | Mu Yahang2,3; Zhang Xue2,3; Chen Ziming1; Sun Xiaofeng3; Liang Jingjing3; Li Jinguo3; Zhou Yizhou3 |
| 刊名 | ACTA METALLURGICA SINICA
 |
| 出版日期 | 2023-08-11 |
| 卷号 | 59期号:8页码:1075-1086 |
| 关键词 | Ni-based superalloy crack susceptibility additive manufacturing machine learning thermodynamic calculation |
| ISSN号 | 0412-1961 |
| DOI | 10.11900/0412.1961.2023.00050 |
| 通讯作者 | Sun Xiaofeng(xfsun@imr.ac.cn) ; Liang Jingjing(jjliang@imr.ac.cn) |
| 英文摘要 | The rapid development of aeroengines has led to high demand heat resistant blades. As a result, fabricating techniques and designing materials have taken center stage in producing aeroengines. Additive manufacturing (AM), which integrates design and manufacturing, has advantages in preparing blades with complex cavity structures. However, commercial Ni-based superalloys have poor additive manufacturability and are prone to defects such as cracks, severely hindering the development of the AM of superalloy blades. Therefore, finding a high-performance superalloy with excellent additive manufacturability is necessary. To alleviate this problem, many crack susceptibility criteria and test methods have recently been proposed to evaluate the crack susceptibility of alloys from a compositional and/or process point of view. However, the rapid prediction of the crack susceptibility of superalloys remains a challenge, hindering the widespread screening and designing of superalloys for AM. Nevertheless, using machine learning (ML) in conjunction with thermodynamic calculation may effectively predict the properties of alloys, and this combination is anticipated to grow as an important tool for designing alloys with low crack susceptibility for AM. Based on the aforementioned context, this study reports the development of an ML prediction model after combining experimental data and thermodynamic calculations to establish a Ni-based alloy crack susceptibility database. This ML model has an excellent prediction effect (R-2 = 0.96 on the training set and R-2 = 0.81 on the validation set) and enables accurate prediction of the crack susceptibility of the experimental alloys and published alloys. It is verified that a hot crack is the most typical type of crack in Ni-based superalloys during AM. The influence of elements on crack susceptibility is also analyzed using the SHapley Additive exPlanation method. Precipitation-strengthening (Al and Ti) and trace (C and B) elements greatly influence crack susceptibility. A small amount of Re can inhibit cracks, but excessive amounts produce a topologically close-packed phase, deteriorating the crack susceptibility and mechanical properties. The influence of other alloying elements on crack susceptibility is roughly ranked as follows: Re, W, Cr, Mo, Ta, and Co, which can provide a screening method for the composition design of subsequent AMed superalloys. |
| 资助项目 | National Science and Technology Major Project[Y2019-VII-0011-0151] ; National Science and Technology Major Project[P2022-C-IV-002-001] |
| WOS研究方向 | Metallurgy & Metallurgical Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001035775200010 |
| 出版者 | SCIENCE PRESS |
| 资助机构 | National Science and Technology Major Project |
| 源URL | [http://ir.imr.ac.cn/handle/321006/178801]  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 通讯作者 | Sun Xiaofeng; Liang Jingjing |
| 作者单位 | 1.Univ Sci & Technol Beijing, Sch Intelligence Sci & Technol, Beijing 100083, Peoples R China 2.Univ Sci & Technol China, Sch Mat Sci & Engn, Shenyang 110016, Peoples R China 3.Chinese Acad Sci, Inst Met Res, Shi Changxu Innovat Ctr Adv Mat, Shenyang 110016, Peoples R China |
| 推荐引用方式 GB/T 7714 | Mu Yahang,Zhang Xue,Chen Ziming,et al. Modeling of Crack Susceptibility of Ni-Based Superalloy for Additive Manufacturing via Thermodynamic Calculation and Machine Learning[J]. ACTA METALLURGICA SINICA,2023,59(8):1075-1086. |
| APA | Mu Yahang.,Zhang Xue.,Chen Ziming.,Sun Xiaofeng.,Liang Jingjing.,...&Zhou Yizhou.(2023).Modeling of Crack Susceptibility of Ni-Based Superalloy for Additive Manufacturing via Thermodynamic Calculation and Machine Learning.ACTA METALLURGICA SINICA,59(8),1075-1086. |
| MLA | Mu Yahang,et al."Modeling of Crack Susceptibility of Ni-Based Superalloy for Additive Manufacturing via Thermodynamic Calculation and Machine Learning".ACTA METALLURGICA SINICA 59.8(2023):1075-1086. |
入库方式： OAI收割
来源：金属研究所
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