Phase-field simulation of austenite growth behavior: Insights into the austenite memory phenomenon

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• 作者：Pengcheng Song^a ; ^b ; ^{songpc11@mails.tsinghua.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Yanzhou Ji^b ; ^{yxj135@psu.edu" class="auth_mail" title="E-mail the corresponding author} ; Lei Chen^b ; ^c ; Wenbo Liu^a ; Chi Zhang^a ; Long-Qing Chen^b ; Zhigang Yang^a
• 关键词：Austenite memory ; Reverse austenitic transformation ; Crystallography ; Bain grouping ; Phase-field modeling
• 刊名：Computational Materials Science
• 出版年：2016
• 出版时间：May 2016
• 年：2016
• 卷：117
• 期：Complete
• 页码：139-150
• 全文大小：3653 K

文摘

Austenite memory phenomenon impedes the application of reverse austenitic transformation to refine grains in steels. In this work, a phase-field model is employed to understand the austenite memory mechanism in terms of austenite growth behaviors under different mechanical boundary conditions, using the Fe–23Ni (wt.%) alloy as an example. The effect of defects formed during martensitic transformation on reverse austenitic transformation is considered by introducing a “stored energy” term. Kurdjumov–Sachs (K–S) variants of each phase are divided into three groups based on the crystallography analysis. Results show that different combinations of mechanical boundary conditions during the austenite → martensite → austenite transformation cycle have different effects on the austenite memory phenomenon, which can be attributed to the minimization of strain energy induced by phase transformations, as well as the inhomogeneous distribution of stored energy (energy of defects).