Please wait a minute...
金属学报  2018, Vol. 54 Issue (2): 151-160    DOI: 10.11900/0412.1961.2017.00431
  本期目录 | 过刊浏览 |
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
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[J]. Acta Metall Sin, 2018, 54(2): 151-160.

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

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]
[1] Economics Committee of World Steel Association. Steel Statistical Yearbook 2016[M]. World Steel Association, 2016: 7
[2] Liu B C.The role and prospect of modeling and simulation in equipment manufacturing[J]. Aeron. Manuf. Technol., 2008, (3): 26(柳百成. 建模与仿真在装备制造中的作用与前景[J]. 航空制造技术, 2008, (3): 26)
[3] Flemings M C, Nereo G E.Macrosegregation: Part I[J]. Trans. Met. Soc. AIME, 1967, 239: 49
[4] Flemings M C, Mehrabian R, Nereo G E.Macrosegregation: Part II[J]. Trans. Met. Soc. AIME, 1968, 242: 41
[5] Flemings M C, Nereo G E.Macrosegregation: Part III[J]. Trans. Met. Soc. AIME, 1968, 242: 50
[6] Beckermann C.Modelling of macrosegregation: Applications and future needs[J]. Int. Mater. Rev., 2002, 47: 243
[7] Pickering E J.Macrosegregation in steel ingots: The applicability of modelling and characterization techniques[J]. ISIJ Int., 2013, 53: 935
[8] Flemings M C.Our understanding of macrosegregation: Past and present[J]. ISIJ Int., 2000, 40: 833
[9] Li D Z, Chen X Q, Fu P X, et al.Inclusion flotation-driven channel segregation in solidifying steels[J]. Nat. Commun., 2014, 5: 5572
[10] Wu M H, Ludwig A, Kharicha A.A four phase model for the macrosegregation and shrinkage cavity during solidification of steel ingot[J]. Appl. Math. Model., 2017, 41: 102
[11] Fujii T, Poirier D R, Flemings M C.Macrosegregation in a multicomponent low alloy steel[J]. Metall. Trans., 1979, 10B: 331
[12] Bennon W D, Incropera F P.A continuum model for momentum, heat and species transport in binary solid-liquid phase change systems-I. Model formulation[J]. Int. J. Heat Mass Transfer, 1987, 30: 2161
[13] Beckermann C, Viskanta R.Double-diffusive convection during dendritic solidification of a binary mixture[J]. Physicochem. Hydrodynam., 1988, 10: 195
[14] Ni J, Beckermann C.A volume-averaged two-phase model for transport phenomena during solidification[J]. Metall. Trans., 1991, 22B: 349
[15] Wang C Y, Beckermann C.Equiaxed dendritic solidification with convection: Part I. Multiscale/multiphase modeling[J]. Metall. Mater. Trans., 1996, 27A: 2754
[16] Wang C Y, Beckermann C.Equiaxed dendritic solidification with convection: Part II. Numerical simulations for an A1-4 wt pct Cu alloy[J]. Metall. Mater. Trans., 1996, 27A: 2765
[17] Ludwig A, Gruber-Pretzler M, Wu M H, et al.About the formation of macrosegregations during continuous casting of Sn-Bronze[J]. Fluid Dyn. Mater. Process., 2005, 1: 285
[18] Combeau H, Zalo?nik M, Hans S, et al.Prediction of macrosegregation in steel ingots: Influence of the motion and the morphology of equiaxed grains[J]. Metall. Mater. Trans., 2009, 40B: 289
[19] Han Z Q, Liu B C.Numerical simulation of channel segregation in vertically unidirectional solidification process[J]. Acta. Metall. Sin., 2003, 39: 140(韩志强, 柳百成. 垂直定向凝固条件下通道偏析形成过程的数值模拟[J]. 金属学报, 2003, 39: 140)
[20] Wu M, Fjeld A, Ludwig A.Modelling mixed columnar-equiaxed solidification with melt convection and grain sedimentation—Part I: Model description[J]. Comp. Mater. Sci., 2010, 50: 32
[21] Chiang K C, Tsai H L.Interaction between shrinkage-induced fluid flow and natural convection during alloy solidification[J]. Int. J. Heat Mass Transfer, 1992, 35: 1771
[22] Krane M J M, Incropera F P. Analysis of the effect of shrinkage on macrosegregation in alloy solidification[J]. Metall. Mater. Trans., 1995, 26A: 2329
[23] Carlson K D, Lin Z P, Beckermann C.Modeling the effect of finite-rate hydrogen diffusion on porosity formation in aluminum alloys[J]. Metall. Mater. Trans., 2007, 38B: 541
[24] Zhang S L, Yanke J, Johnson D R, et al.Modeling defects in castings using a volume of fluid method[J]. Int. J. Numer. Methods Heat Fluid Flow, 2014, 24: 468
[25] Wang T M, Yao S, Zhang X G, et al.Modelling of the thermo-solutal convection, shrinkage flow and grain movement during globular equiaxed solidification in a multi-phase system I. Three phase model[J]. Acta Metall. Sin., 2006, 42: 584(王同敏, 姚山, 张兴国等. 等轴球晶凝固多相体系内热溶质对流、补缩流及晶粒运动的数值建模: I. 三相流模型[J]. 金属学报, 2006, 42: 584)
[26] Wang T M, Li T J, Cao Z Q, et al.Modelling of the thermo-solutal convection, shrinkage flow and grain movement during globular equiaxed solidification in a multi-phase system II. Application of model[J]. Acta Metall. Sin., 2006, 42: 591(王同敏, 李廷举, 曹志强等. 等轴球晶凝固多相体系内热溶质对流, 补缩流及晶粒运动的数值建模: II. 模型的应用[J]. 金属学报, 2006, 42: 591)
[27] Le Corre S, Bellet M, Bay F, et al.Two-phase approach for solidification problems: Modelling the mushy zone deformation [A]. Proceeding 10th International Conference on Modeling of Casting, Welding and Advanced Solidification Processes[C]. Warrendale: The Minerals, Metals & Materials Society (TMS), 2003: 345
[28] Corre S L, Bellet M.Two-phase modeling of metals solidification: A numerical approach for the thermo-mechanical problem [A]. Proceeding 8th International Conference on Numerical Methods in Industrial Forming Processes[C]. New York: American Institute of Physics, 2004: 1185
[29] Bellet M, Fachinotti V D.A two-phase two-dimensional finite element thermomechanics and macrosegregation model of mushy zone. Application to continuous casting [A]. Proceeding 11th International Conference on Modeling of Casting, Welding and Advanced Solidification Processes[C]. Warrendale: The Minerals, Metals & Materials Society (TMS), 2006: 169
[30] Fachinotti V D, Le Corre S, Triolet N, et al.Two-phase thermo-mechanical and macrosegregation modelling of binary alloys solidification with emphasis on the secondary cooling stage of steel slab continuous casting processes[J]. Int. J. Numer. Meth. Eng., 2006, 67: 1341
[31] Bellet M.Two-phase multiscale FEM modelling of macrosegregation formation in steel slabs [A]. Proceeding 9th International Conference on Numerical Methods in Industrial Forming Processes[C]. New York: American Institute of Physics, 2007: 1369
[32] Koshikawa T, Bellet M, Gandin C A, et al.Experimental study and two-phase numerical modeling of macrosegregation induced by solid deformation during punch pressing of solidifying steel ingots[J]. Acta Mater., 2017, 124: 513
[33] Koshikawa T, Bellet M, Gandin C A, et al.Study of hot tearing and macrosegregation through ingot bending test and its numerical simulation [A]. IOP Conference Series: Materials Science and Engineering[C], 2015: 012096
[34] Koshikawa T, Bellet M, Gandin C A, et al.Study of hot tearing during steel solidification through ingot punching test and its numerical simulation[J]. Metall. Mater. Trans., 2016, 47A: 4053
[35] Liu D R, Sang B G, Kang X H, et al.Numerical simulation of macrosegregation in large multiconcentration poured steel ingot[J]. Int. J Cast Met. Res., 2010, 23: 354
[36] Xu W, Zhou J X, Pang S Y, et al. Numerical simulation of macrosegregation formation in binary alloy solidification processing based on modified projection method [J]. Adv. Mater. Res., 2011, 314-316: 369
[37] Cao Y F, Chen Y, Fu P X, et al.The experimental characterization and numerical simulation of A-segregates in 27SiMn steel[J]. Metall. Mater. Trans., 2017, 48A: 2260
[38] Ge H H, Ren F L, Li J, et al.Four-phase dendritic model for the prediction of macrosegregation, shrinkage cavity, and porosity in a 55-ton ingot[J]. Metall. Mater. Trans., 2017, 48A: 1139
[39] Li W S, Shen H F, Liu B C.Simulation of macrosegregation due to melt convection and grain sedimentation in steel ingots using a mixture model [A]. EPD Congress 2011[C]. Warrendale: The Minerals, Metals & Materials Society (TMS), 2011: 747
[40] Li W S, Shen H F, Liu B C.Numerical simulation of macrosegregation in steel ingots using a two-phase model[J]. Int. J. Min. Met. Mater., 2012, 19: 787
[41] Tu W T, Duan Z H, Shen B Z, et al.Three-dimensional simulation of macrosegregation in a 36-ton steel ingot using a multicomponent multiphase model[J]. JOM, 2016, 68: 3116
[42] Duan Z H, Tu W T, Shen B Z, et al.Experimental measurements for numerical simulation of macrosegregation in a 36-ton steel ingot[J]. Metall. Mater. Trans., 2016, 47A: 3597
[43] Tu W T, Zhang X, Shen H F, et al.Numerical simulation on multiple pouring process for a 292 t steel ingot[J]. China Foundry, 2014, 11: 52
[44] Pardeshi R, Dutta P, Singh A K.Modeling of convection and macrosegregation through appropriate consideration of multiphase/multiscale phenomena during alloy solidification[J]. Ind. Eng. Chem. Res., 2009, 48: 8789
[45] Ludwig A, Kharicha A, Wu M H.Modeling of multiscale and multiphase phenomena in material processing[J]. Metall. Mater. Trans., 2014, 45B: 36
[46] Ludwig A, Wu M H, Kharicha A.Recent developments and future perspectives in simulation of metallurgical processes[J]. BHM, 2015, 160: 507
[47] Combeau H, Zalo?nik M, Bedel M.Predictive capabilities of multiphysics and multiscale models in modeling solidification of steel ingots and DC casting of aluminum[J]. JOM, 2016, 68: 2198
[1] 马德新, 赵运兴, 徐维台, 王富. 重力对高温合金定向凝固组织的影响[J]. 金属学报, 2023, 59(9): 1279-1290.
[2] 张健, 王莉, 谢光, 王栋, 申健, 卢玉章, 黄亚奇, 李亚微. 镍基单晶高温合金的研发进展[J]. 金属学报, 2023, 59(9): 1109-1124.
[3] 毕中南, 秦海龙, 刘沛, 史松宜, 谢锦丽, 张继. 高温合金锻件残余应力量化表征及控制技术研究进展[J]. 金属学报, 2023, 59(9): 1144-1158.
[4] 刘继浩, 周健, 武会宾, 马党参, 徐辉霞, 马志俊. 喷射成形M3高速钢偏析成因及凝固机理[J]. 金属学报, 2023, 59(5): 599-610.
[5] 侯娟, 代斌斌, 闵师领, 刘慧, 蒋梦蕾, 杨帆. 尺寸设计对选区激光熔化304L不锈钢显微组织与性能的影响[J]. 金属学报, 2023, 59(5): 623-635.
[6] 苏震奇, 张丛江, 袁笑坦, 胡兴金, 芦可可, 任维丽, 丁彪, 郑天祥, 沈喆, 钟云波, 王晖, 王秋良. 纵向静磁场下单晶高温合金定向凝固籽晶回熔界面杂晶的形成与演化[J]. 金属学报, 2023, 59(12): 1568-1580.
[7] 张开元, 董文超, 赵栋, 李世键, 陆善平. 固态相变对Fe-Co-Ni超高强度钢长臂梁构件焊接-淬火过程应力和变形的影响[J]. 金属学报, 2023, 59(12): 1633-1643.
[8] 张利民, 李宁, 朱龙飞, 殷鹏飞, 王建元, 吴宏景. 交流电脉冲对过共晶Al-Si合金中初生Si相偏析的作用机制[J]. 金属学报, 2023, 59(12): 1624-1632.
[9] 王重阳, 韩世伟, 谢峰, 胡龙, 邓德安. 固态相变和软化效应对超高强钢焊接残余应力的影响[J]. 金属学报, 2023, 59(12): 1613-1623.
[10] 周小宾, 赵占山, 汪万行, 徐建国, 岳强. 渣-金界面气泡夹带行为数值物理模拟[J]. 金属学报, 2023, 59(11): 1523-1532.
[11] 夏大海, 邓成满, 陈子光, 李天书, 胡文彬. 金属材料局部腐蚀损伤过程的近场动力学模拟:进展与挑战[J]. 金属学报, 2022, 58(9): 1093-1107.
[12] 梁琛, 王小娟, 王海鹏. 快速凝固Ti-Al-Nb合金B2相形成机制与显微力学性能[J]. 金属学报, 2022, 58(9): 1169-1178.
[13] 李闪闪, 陈云, 巩桐兆, 陈星秋, 傅排先, 李殿中. 冷速对高碳铬轴承钢液析碳化物凝固析出机制的影响[J]. 金属学报, 2022, 58(8): 1024-1034.
[14] 刘仁慈, 王鹏, 曹如心, 倪明杰, 刘冬, 崔玉友, 杨锐. 700℃热暴露对 β 凝固 γ-TiAl合金表面组织及形貌的影响[J]. 金属学报, 2022, 58(8): 1003-1012.
[15] 李彦强, 赵九洲, 江鸿翔, 何杰. Pb-Al合金定向凝固组织形成过程[J]. 金属学报, 2022, 58(8): 1072-1082.