Modeling of Crack Susceptibility of Ni-Based Superalloy for Additive Manufacturing via Thermodynamic Calculation and Machine Learning
Received date: 2023-02-10
Revised date: 2023-04-21
Online published: 2023-05-05
Supported by
National Science and Technology Major Project(Y2019-VII-0011-0151);National Science and Technology Major Project(P2022-C-IV-002-001)
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 (R2 = 0.96 on the training set and R2 = 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.
MU Yahang , ZHANG Xue , CHEN Ziming , SUN Xiaofeng , LIANG Jingjing , LI Jinguo , ZHOU Yizhou . Modeling of Crack Susceptibility of Ni-Based Superalloy for Additive Manufacturing via Thermodynamic Calculation and Machine Learning[J]. Acta Metall Sin, 2023 , 59(8) : 1075 -1086 . DOI: 10.11900/0412.1961.2023.00050
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