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金属学报  2018, Vol. 54 Issue (2): 151-160    DOI: 10.11900/0412.1961.2017.00431
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钢锭铸造过程宏观偏析数值模拟
沈厚发(), 陈康欣, 柳百成
清华大学材料学院先进成形制造教育部重点实验室 北京 100084
Numerical Simulation of Macrosegregation inSteel Ingot Casting
Houfa SHEN(), Kangxin CHEN, Baicheng LIU
Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
全文: PDF(2995 KB)   HTML
摘要: 

本文以宏观偏析数学模型在钢锭铸造过程中的应用为主,阐明了宏观偏析的机理及影响因素,归纳了已有的几类宏观偏析模型,介绍了近年来宏观偏析模型的新发展。还介绍了本课题组进行的大型钢锭宏观偏析数值模拟研究工作,包括开发的多元多相宏观偏析数学模型在36 t钢锭铸造中的应用,以及多包变成分合浇工艺的数值模拟。对36 t钢锭进行全截面解剖,结果表明,模拟结果与实测吻合较好,进而说明所开发的多元多相宏观偏析模型能够较准确地预测钢锭中产生的宏观偏析。此外,模拟结果显示,多包变成分合浇工艺可得到与凝固后实际偏析形式相反的初始溶质分布,这也证明了多包变成分合浇工艺在宏观偏析控制上的应用能力。

关键词 钢锭凝固宏观偏析数值模拟    
Abstract

Many key forging components of heavy equipment are manufactured by large steel ingots. Macrosegregation in steel ingots is a key defect formed during the solidification process. Over the past few decades, numerical modeling has played a more and more important role in the study of macrosegregation. Various models have been developed and applied to different ingot casting processes. This paper focused on the application of macrosegregation models to the steel ingot. Firstly, the formation mechanism and influencing factors of macrosegregation were introduced. Then, the existing macrosegregation models and their recent development were summarized. Macrosegregation models accounting for such mechanisms as solidification shrinkage-induced flow and mushy zone deformation were analyzed, respectfully. To model macrosegregation due to solidification shrinkage, the key was to solve the free surface. A simple derivation showed that the multi-phase (including gas phase) models were equivalent to the VOF-based segregation models in dealing with the shrinkage-induced flow. Finally, our recent research work on numerical modeling of macrosegregation in steel ingots was illustrated, including application of the developed multi-component and multi-phase macrosegregation model to a 36 t steel ingot, and numerical simulation of multiple pouring process. The carbon and sulphur concentrations at about 1800 sampling points, covering the full section of a 36 t ingot, were measured. By detailed temperature recording, accurate heat transfer conditions between the ingot and mould were obtained. Typical macrosegregation patterns, including the bottom-located negative segregation and the pushpin-like positive segregation zone in the top riser, have been reproduced both in the measurements and the predictions. The carbon and sulphur concentrations predicted by the three dimensional multi-component and multi-phase macrosegregation models agreed well with the measurements, thus proving that the model can well predict the macrosegregation formation in steel ingots. As for the multi-pouring process simulation, the results show a high concentration of carbon at the bottom and a low concentration of carbon at the top of the mould after the multi-pouring process with carbon content high in the first ladle and low in the last ladle. Therefore, the multiple pouring process could get the initial solute distribution with the opposite form of segregation. Such carbon concentration distribution would reduce the negative segregation at the bottom and the positive segregation at the top of the solidified ingot, thus proving the ability of the multiple pouring process for the control of macrosegregation.

Key wordsingot    solidification    macrosegregation    numerical modeling
收稿日期: 2017-10-16     
基金资助:国家自然科学基金-辽宁联合基金项目No.U1508215
作者简介:

作者简介 沈厚发,男,1964年生,教授,博士

引用本文:

沈厚发, 陈康欣, 柳百成. 钢锭铸造过程宏观偏析数值模拟[J]. 金属学报, 2018, 54(2): 151-160.
Houfa SHEN, Kangxin CHEN, Baicheng LIU. Numerical Simulation of Macrosegregation inSteel Ingot Casting. Acta Metall Sin, 2018, 54(2): 151-160.

链接本文:

https://www.ams.org.cn/CN/10.11900/0412.1961.2017.00431      或      https://www.ams.org.cn/CN/Y2018/V54/I2/151

图1  2006年~2015年世界及中国钢锭产量
图2  大型钢锭中典型宏观偏析形式
图3  合金宏、微观尺度凝固现象
图4  36 t钢锭凝固过程中固相分数、C成分分布变化
图5  36 t钢锭凝固结束C元素分布的预测结果、实测结果及偏析特征[41]
图6  36 t钢锭不同特征位置的C、S成分分布[41]
图7  多包合浇过程中间包出口C成分变化[43]
图8  钢锭模中不同时间C成分分布变化[43]
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