Experimental and Numerical Simulation Study on Layer Casting Method for Composition Homogeneityon Ingot Casting

doi:10.11900/0412.1961.2017.00225

Acta Metall Sin

2018, Vol. 54

Issue (1): 118-128 DOI: 10.11900/0412.1961.2017.00225

Orginal Article

Current Issue | Archive | Adv Search

Experimental and Numerical Simulation Study on Layer Casting Method for Composition Homogeneityon Ingot Casting

Jun LI^1,²(

), Junge WANG¹, Fengli REN¹, Honghao GE¹, Qiaodan HU¹, Mingxu XIA¹, Jianguo LI¹

1 School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2 Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration, Shanghai Jiao Tong University, Shanghai 200240, China

Cite this article:

Jun LI, Junge WANG, Fengli REN, Honghao GE, Qiaodan HU, Mingxu XIA, Jianguo LI. Experimental and Numerical Simulation Study on Layer Casting Method for Composition Homogeneityon Ingot Casting. Acta Metall Sin, 2018, 54(1): 118-128.

Download:

HTML

PDF(852KB)
Export: BibTeX | EndNote (RIS)

Abstract

Macrosegregation, or compositional heterogeneity, is a very common and serious defect in large steel ingots, which is hard to remove in the following processing procedures. It not only decides the final properties of the product, but also restricts downstream hot working processing severely. This compositional heterogeneity occurs due to the relative motion between the liquid and solid phases during solidification. Therefore, it is necessary to develop an effective method to manufacture large ingots with less macrosegregation. In this work, a novel casting method was proposed to alleviate macrosegregation of large ingots, i.e., layer casting (LC). With this method, alloy melt will be poured into the mould step by step, so that the melt could be solidified layer by layer and the macrosegregation will be alleviated. Both experimental and numerical studies were carried out to verify the feasibility and effectiveness of LC method. Two small Al-4.0%Cu (mass fraction) ingots were cast using two casting methods, conventional casting method, in which melt was cast into mould in one stage, and LC method, in which melt was cast into mould in several stages. Each ingot was sectioned into two parts along the center line, and then the specimens were measured by optical emission spectrometry to obtain the compositional distribution of Cu. Both severe bottom negative segregation and top positive segregation zones were observed in the ingot fabricated by conventional casting method. More homogeneity of compositional distribution was observed in the ingot fabricated by LC method, and the max negative and positive macrosegregation along the center line decreased by 24.6% and 77.2%, respectively. At the same time, a mixed three-phase (equiaxed, columnar and liquid) solidification model was employed to study the solidification processing in large ingots. The macrosegregation formation processes of 100 t and 13 t steel ingots fabricated by both conventional casting and LC methods were numerically simulated. The simulation results indicated that LC method had the capability of alleviating macrosegregation of large steel ingots significantly, compared with conventional casting method. With the increment of ingot size and amount of ladles, LC method had more significant effect on the alleviation of macrosegregation in large ingots. The mechanism of macrosegregation alleviation of LC method was analyzed.

Key words: large ingot layer casting macrosegregation numerical simulation

Received: 09 June 2017

ZTFLH:

TG244.2

Fund: Supported by National Key Research and Development Program of China (No.2017YFB0305300), Joint Funds of the National Natural Science Foundation of China (No.U1660203), National Natural Science Foundation of China (No.51404152) and Shanghai Pujiang Program (No.14PJ1404800)

	Service

	E-mail this article
	Add to citation manager
	E-mail Alert
	RSS
	（）
	Articles by authors
	Jun LI
	Junge WANG
	Fengli REN
	Honghao GE
	Qiaodan HU
	Mingxu XIA
	Jianguo LI

URL:

https://www.ams.org.cn/EN/10.11900/0412.1961.2017.00225 OR https://www.ams.org.cn/EN/Y2018/V54/I1/118

Fig.1 Schematic of layer casting (LC) (c₁, c₂,, c_n—melt composition of each ladle; T₁, T₂,, T_n—pouring temperature of each ladle; t₁, t₂,, t_n—pouring time interval for each ladle)

Fig.2 Al-4.0%Cu ingots fabricated by conventional casting (a) and LC (b) methods (Blue dots indicate the sampling points for composition measurement)

Fig.3 Macrosegregation distributions of longitudinal sections of ingots fabricated by conventional casting (a) and LC (b) methods

Table 1 Macrosegregation distribution characteristics along the center line of ingots fabricated by conventional casting and LC methods

Fig.4 Macrosegregation distribution curves, on which the macrosegregation indexs and corresponding coordinates along the central line of some points are given, along the center line of ingots fabricated by conventional casting and LC methods

Fig.5 Schematic of boundary and initial conditions of 100 t steel ingot (H—heat transfer coefficient, T_w—wall temperature, T₀—initial temperature, c₀—initial concentration, g—gravitational acceleration)

Fig.6 Final macrosegregation contour maps of 100 t steel ingots fabricated by conventional casting method (a), LC method of 5 ladles (b) and 10 ladles (c), predicted by numerical simulations

Fig.7 Macrosegregation distribution curves, on which the macrosegregation indexs and corresponding coordinates along the central line of some points are given, along the center line of 100 t steel ingots fabricated by conventional casting method, LC method of 5 ladles and 10 ladles, predicted by numerical simulations

Table 2 Macrosegregation distribution characteristics along the center line of steel ingots fabricated by conventional casting and LC methods, predicted by numerical simulations

Fig.8 Macrosegregation distribution curves, on which the macrosegregation indexs and corresponding coordinates along the central line of some points are given, along the center line of 13 t steel ingots fabricated by conventional casting method and LC method of 10 ladles, predicted by numerical simulations

Fig.9 Velocity distributions (left half) and solidification conditions (right half) of ingots fabricated by conventional casting method (a), LC method of 5 ladles (b) and 10 ladles (c), after casting 0.5 h (

v l max

—maximum velocity of liquid metal, f_l—liquid volume fraction)

Fig.10 Velocity distributions of equiaxed grains (left half) and macrosegregation distributions (right half) of ingots fabricated by conventional casting method (a), LC method of 5 ladles (b) and 10 ladles (c), after casting 0.5 h (

v e max

—maximum velocity of equiaxed crystal)

[1]	Pickering E J.Macrosegregation in steel ingots: The applicability of modelling and characterisation techniques[J]. ISIJ Int., 2013, 53: 935
[2]	Du Q, Li D Z, Li Y Y.Quantitative prediction of macrosegregation formation caused by natural convection during solidification of steel casting[J]. Acta Metall. Sin., 2000, 36: 1197(杜强, 李殿中, 李依依. 铸钢件凝固过程中自然对流引起的宏观偏析模拟[J]. 金属学报, 2000, 36: 1197)
[3]	Han Z Q, Liu B C.Numerical simulation on 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)
[4]	Cao H F, Shen H F, Liu B C.Numerical simulation of segregation in channel during horizontal solidification[J]. Acta Metall. Sin., 2005, 41: 917(曹海峰, 沈厚发, 柳百成. 侧向凝固通道偏析的数值模拟[J]. 金属学报, 2005, 41: 917)
[5]	Wang T M, Yao S, Zhang X G, et al.Modelling of the thermosolutal convection, shrinkage flow and grain movement during globular equiaxed solidification in a multi-phase system I. Three-phase flow 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模拟I. 三相流模型[J]. 金属学报, 2006, 42: 584)
[6]	Pickering E J, Chesman C, Al-Bermani S, et al.A comprehensive case study of macrosegregation in a steel ingot[J]. Metall. Mater. Trans., 2015, 46B: 1860
[7]	Hebditch D J, Hunt J D.Observations of ingot macrosegregation on model systems[J]. Metall. Trans., 1974, 5: 1557
[8]	Maidorn C, Blind D.Solidification and segregation in heavy forging ingots[J]. Nucl. Eng. Des., 1985, 84: 285
[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]	Wang J Q.Prediction of the centerline shrinkage porosity and optimized design for the hundred-ton heavy ingots [D]. Shenyang: Institute of Metal Research, Chinese Academy of Sciences, 2012(王佳琪. 百吨级钢锭缩孔疏松预测与工艺优化 [D]. 沈阳: 中国科学院金属研究所, 2012)
[11]	Ma X P, Li D Z.Macrosegregation and its formation mechanism in steel ingot with designed local thermal control[J]. ISIJ Int., 2014, 54: 356
[12]	Beckermann C.Modelling of macrosegregation: Applications and future needs[J]. Int. Mater. Rev., 2002, 47: 243
[13]	Reddy A V, Beckermann C.Modeling of macrosegregation due to thermosolutal convection and contraction-driven flow in direct chill continuous casting of an Al-Cu round ingot[J]. Metall. Mater. Trans., 1997, 28B: 479
[14]	El-Bealy M, Fredriksson H.Modeling of the peritectic reaction and macro-segregation in casting of low carbon steel[J]. Metall. Mater. Trans., 1996, 27B: 999
[15]	Li W S, Shen H F, Liu B C.Numerical simulation of macrosegregation in steel ingots using a two-phase model[J]. Int. J. Miner. Metall. Mater., 2012, 19: 787
[16]	Jia B F.The numerical simulation of solidification process of polygonal ingot by water-cooled mold casting [D]. Hohhot: Inner Mongolia University of Technology, 2014(贾保峰. 水冷模模铸多边形钢锭凝固数值模拟 [D]. 呼和浩特: 内蒙古工业大学, 2014)
[17]	Dantzig J A, Rappaz M.Solidification [M]. Lausanne, Switzerland: EPFL Press, 2009: 568
[18]	Li X, Noeppel A, Saadi B, et al.Solidification of metallic alloys under magnetic fields[J]. Trans. Indian Inst. Met., 2009, 62: 465
[19]	Li J, Wu M, Hao J, et al.Simulation of channel segregation using a two-phase columnar solidification model-Part I: Model description and verification[J]. Comp. Mater. Sci., 2012, 55: 407
[20]	Li J, Wu M, Hao J, et al.Simulation of channel segregation using a two-phase columnar solidification model-Part II: Mechanism and parameter study[J]. Comp. Mater. Sci., 2012, 55: 419
[21]	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
[22]	Cao Y F, Chen Y, Li D Z.Formation mechanism of channel segregation in carbon steels by inclusion flotation: X-ray microtomography characterization and multi-phase flow modeling[J]. Acta Mater., 2016, 107: 325
[23]	Tang J J.The key technology of large scale casting based on electroslag remelt [D]. Nanchang: Nanchang University, 2011(唐建军. 基于电渣重熔的大型铸锭成型关键技术研究 [D]. 南昌: 南昌大学, 2011)
[24]	Wang H J.Study on a homogenized technology of large diameter ingot of 7075 aluminum alloy [D]. Beijing: University of Science and Technology Beijing, 2015(王海军. 7075合金大直径铸锭均质化技术研究 [D]. 北京: 北京科技大学, 2015)
[25]	Hu D Z, Zhou B S, Zhao W Z, et al.Study on the unidirectional solidification of large-sized ingot[J]. Wide Heavy Plate, 1995, 1(1): 11(胡德志, 周碧珊, 赵文忠等. 定向凝固大型铸锭研究[J]. 宽厚板, 1995, 1(1): 11)
[26]	Bikas H, Stavridis J, Stavropoulos P, et al.A design framework to replace conventional manufacturing processes with additive manufacturing for structural components: A formula student case study[J]. Procedia CIRP, 2016, 57: 710
[27]	Kruth J P, Froyen L, Van Vaerenbergh J, et al.Selective laser melting of iron-based powder[J]. J. Mater. Process. Technol., 2004, 149: 616
[28]	Sang B G, Kang X H, Li D Z.A novel technique for reducing macrosegregation in heavy steel ingots[J]. J. Mater. Process. Technol., 2010, 210: 703
[29]	Zhang Y T, Chen B, Liu K, et al.Development of low segregation technology[J]. Acta Metall. Sin., 2017, 53: 559(张玉妥, 陈波, 刘奎等. 低偏析技术的发展[J]. 金属学报, 2017, 53: 559)
[30]	Tanaka Y, Ishiguro T.Development of high-purity large-scale forgings for energy service[J]. Phys. Status Solidi, 1997, 160A: 305
[31]	Tanaka Y, Sato I.Development of high purity large forgings for nuclear power plants[J]. J. Nucl. Mater., 2011, 417: 854
[32]	Tu W T, Shen H F, Liu B C.Modelling of macrosegregation in a 231-ton steel ingot with multi-pouring process[J]. Mater. Res. Innov., 2015, 19: 60
[33]	Li J, Liu D R, Kang X H, et al.Numerical simulation of delayed pouring technique for a 360 t heavy steel ingot[J]. Mater. Sci. Eng., 2012, 33: 012092
[34]	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
[35]	Tu W T, Zhang X, Shen H F, et al.Numerical simulation on multiple pouring process for a 292 t steel ingot[J]. China Found., 2014, 11: 52
[36]	Doub V S, Romashkin A N, Malginov A N.Main trends in the development of technology for casting steel into ingots[J]. Metallurgist, 2013, 57: 487
[37]	Rappaz M.Modelling of microstructure formation in solidification processes[J]. Int. Mater. Rev., 1989, 34: 93
[38]	Wu M H, Ludwig A.A three-phase model for mixed columnar-equiaxed solidification[J]. Metall. Mater. Trans., 2006, 37A: 1613
[39]	Li J, Wu M H, Ludwig A, et al.Simulation of macrosegregation in a 2.45-ton steel ingot using a three-phase mixed columnar-equiaxed model[J]. Int. J. Heat Mass Trans., 2014, 72: 668
[40]	Li J, Ge H H, Wu M H, et al.A columnar & non-globular equiaxed mixed three-phase model based on thermosolutal convection and grain movement[J]. Acta Metall. Sin., 2016, 52: 1096(李军, 葛鸿浩, Wu M H等. 基于热溶质对流及晶粒运动的柱状晶-非球状等轴晶混合三相模型[J]. 金属学报, 2016, 52: 1096)
[41]	Ge H H, Li J, Han X J, et al.Dendritic model for macrosegregation prediction of large scale castings[J]. J. Mater. Process. Technol., 2015, 227: 308
[42]	Ma C W, Shen H F, Huang T Y, et al.Numerical simulation of macro-segregation with equiaxed grains movement[J]. Chin. J. Mater. Res., 2004, 18: 232(马长文, 沈厚发, 黄天佑等. 等轴晶移动对宏观偏析影响的数值模拟[J]. 材料研究学报, 2004, 18: 232)

[1]	BI Zhongnan, QIN Hailong, LIU Pei, SHI Songyi, XIE Jinli, ZHANG Ji. Research Progress Regarding Quantitative Characterization and Control Technology of Residual Stress in Superalloy Forgings[J]. 金属学报, 2023, 59(9): 1144-1158.
[2]	WANG Chongyang, HAN Shiwei, XIE Feng, HU Long, DENG Dean. Influence of Solid-State Phase Transformation and Softening Effect on Welding Residual Stress of Ultra-High Strength Steel[J]. 金属学报, 2023, 59(12): 1613-1623.
[3]	ZHANG Kaiyuan, DONG Wenchao, ZHAO Dong, LI Shijian, LU Shanping. Effect of Solid-State Phase Transformation on Stress and Distortion for Fe-Co-Ni Ultra-High Strength Steel Components During Welding and Vacuum Gas Quenching Processes[J]. 金属学报, 2023, 59(12): 1633-1643.
[4]	XIA Dahai, DENG Chengman, CHEN Ziguang, LI Tianshu, HU Wenbin. Modeling Localized Corrosion Propagation of Metallic Materials by Peridynamics: Progresses and Challenges[J]. 金属学报, 2022, 58(9): 1093-1107.
[5]	FENG Miaomiao, ZHANG Hongwei, SHAO Jingxia, LI Tie, LEI Hong, WANG Qiang. Prediction of Macrosegregation of Fe-C Peritectic Alloy Ingot Through Coupling with Thermodynamic Phase Transformation Path[J]. 金属学报, 2021, 57(8): 1057-1072.
[6]	HU Long, WANG Yifeng, LI Suo, ZHANG Chaohua, DENG Dean. Study on Computational Prediction About Microstructure and Hardness of Q345 Steel Welded Joint Based on SH-CCT Diagram[J]. 金属学报, 2021, 57(8): 1073-1086.
[7]	LI Zihan, XIN Jianwen, XIAO Xiao, WANG Huan, HUA Xueming, WU Dongsheng. The Arc Physical Characteristics and Molten Pool Dynamic Behaviors in Conduction Plasma Arc Welding[J]. 金属学报, 2021, 57(5): 693-702.
[8]	WANG Fuqiang, LIU Wei, WANG Zhaowen. Effect of Local Cathode Current Increasing on Bath-Metal Two-Phase Flow Field in Aluminum Reduction Cells[J]. 金属学报, 2020, 56(7): 1047-1056.
[9]	LIU Jizhao, HUANG Hefei, ZHU Zhenbo, LIU Awen, LI Yan. Numerical Simulation of Nanohardness in Hastelloy N Alloy After Xenon Ion Irradiation[J]. 金属学报, 2020, 56(5): 753-759.
[10]	WANG Bo,SHEN Shiyi,RUAN Yanwei,CHENG Shuyong,PENG Wangjun,ZHANG Jieyu. Simulation of Gas-Liquid Two-Phase Flow in Metallurgical Process[J]. 金属学报, 2020, 56(4): 619-632.
[11]	XU Qingyan,YANG Cong,YAN Xuewei,LIU Baicheng. Development of Numerical Simulation in Nickel-Based Superalloy Turbine Blade Directional Solidification[J]. 金属学报, 2019, 55(9): 1175-1184.
[12]	Peiyuan DAI,Xing HU,Shijie LU,Yifeng WANG,Dean DENG. Influence of Size Factor on Calculation Accuracy of Welding Residual Stress of Stainless Steel Pipe by 2D Axisymmetric Model[J]. 金属学报, 2019, 55(8): 1058-1066.
[13]	Chunlei WU,Dewei LI,Xiaowei ZHU,Qiang WANG. Influence of Electromagnetic Swirling Flow in Nozzle on Solidification Structure and Macrosegregation of Continuous Casting Square Billet[J]. 金属学报, 2019, 55(7): 875-884.
[14]	ZHANG Qingdong, LIN Xiao, LIU Jiyang, HU Shushan. Modelling of Q&P Steel Heat Treatment Process Based on Finite Element Method[J]. 金属学报, 2019, 55(12): 1569-1580.
[15]	LU Shijie, WANG Hu, DAI Peiyuan, DENG Dean. Effect of Creep on Prediction Accuracy and Calculating Efficiency of Residual Stress in Post Weld Heat Treatment[J]. 金属学报, 2019, 55(12): 1581-1592.

No Suggested Reading articles found!

Viewed

Full text

Abstract

Cited

Shared

Discussed