基于热力学计算与机器学习的增材制造镍基高温合金裂纹敏感性预测模型
Modeling of Crack Susceptibility of Ni-Based Superalloy for Additive Manufacturing via Thermodynamic Calculation and Machine Learning
基于热力学计算与机器学习的增材制造镍基高温合金裂纹敏感性预测模型 |
| 穆亚航, 张雪, 陈梓名, 孙晓峰, 梁静静, 李金国, 周亦胄 |
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Modeling of Crack Susceptibility of Ni-Based Superalloy for Additive Manufacturing via Thermodynamic Calculation and Machine Learning |
| MU Yahang, ZHANG Xue, CHEN Ziming, SUN Xiaofeng, LIANG Jingjing, LI Jinguo, ZHOU Yizhou |
| 图10 机器学习裂纹敏感性预测模型特征参数的重要性评估 |
| Fig.10 SHAP values of ten elements for FR (a), CSC (b), HSC (c), and SCI (d) for each data; ranked mean absolute value of SHAP values of ten selected features for crack susceptibility (e) (SHAP—SHapley Additive exPlanation) |
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