Materials Transactions Online

Materials Transactions, Vol.47 No.01 (2006) pp.198-206
© 2006 The Japan Institute of Metals

Prediction and Improvement of Mechanical Properties of Corrosion Resistant Superalloy K44 with Adjusting Minor Additions C, B and Hf

Jianting Guo1,, Jieshan Hou1,, Lanzhang Zhou1 and Hengqiang Ye2

1Department of Superalloys, Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, P. R. China
2Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, P. R. China

The neural network (NN) method is applied to predict the influence of minor additions C, B and Hf on mechanical properties of cast superalloy K44 with heat treatment parameters considered. Furthermore, the influence of minor additions C, B and Hf on phase stability is estimated using d-electrons theory. The results from these two methods indicate that decreasing C content, increasing B content and doping 0.2--0.3 mass% Hf can balance the desired mechanical properties and phase stability in K44 alloy, which also is confirmed experimentally through the relation between mechanical properties and phase stability of base/modified K44 alloys.

(Received 2005/1/27; Accepted 2005/10/6; Published 2006/1/15)

Keywords: superalloy K44, neural network, d-electrons theory, mechanical properties, phase stability

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