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

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2 沉积态下4#合金(Ni-8Co-10Cr-8W-4.5Al-1Ti-5Ta)试样中的微观组织SEM像，TCP相的BSE像、TEM像及EDS元素面分布图

Fig.2 Low (a) and high (b) magnified SEM images of cracks in as-built 4# (Ni-8Co-10Cr-8W-4.5Al-1Ti-5Ta) sample, corresponding BSE image of TCP phase (c), bright field TEM image and EDS elemental maps of TCP phase (d) (TCP—topologically close-packed)