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Acta Metall Sin  2014, Vol. 50 Issue (3): 345-354    DOI: 10.3724/SP.J.1037.2013.00496
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NUMERICAL SIMULATION OF DENDRITE GRAIN GROWTH OF DD6 SUPERALLOY DURING DIRECTIONAL SOLIDIFICATION PROCESS
ZHANG Hang1, XU Qingyan1(), SHI Zhenxue2, LIU Baicheng1
1 Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, School of Materials Sciences and Engineering, Tsinghua University, Beijing 100084
2 National Key Laboratory of Science and Technology on Advanced High Temperature Structural Materials,Beijing Institute of Aeronautical Materials, Beijing 100095
Cite this article: 

ZHANG Hang, XU Qingyan, SHI Zhenxue, LIU Baicheng. NUMERICAL SIMULATION OF DENDRITE GRAIN GROWTH OF DD6 SUPERALLOY DURING DIRECTIONAL SOLIDIFICATION PROCESS. Acta Metall Sin, 2014, 50(3): 345-354.

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Abstract  

Modern aero and power industry needs high-performance gas turbine. Directional solidification (DS) columnar grain and single crystal (SX) blade as key parts of gas turbine serve in heavy stress and high temperature conditions. The DS and SX blade are mainly produced by high rapid solidification (HRS) method, and HRS is one of useful DS technology, which has a property that the heat dissipating ways are changing during the process and the temperature gradients will vary correspondingly. The dendrite grain arrays were the substructure of a DS or SX blade. The structure of the dendrite grain arrays influences the mechanical property of the final casting very much, but is seriously affected by the solidification parameters, such as temperature gradient. In this work, the dendrite grain growth of DD6 superalloy was studied based on cellular automaton-finite difference (CA-FD) model concerning the HRS method's macro solidification parameters. Mathematic models for dendrite grain growth controlled by temperature field and solute field were built to describe the competitive growth and morphology evolution of dendrite grains. Then the dendrite calculation model was coupled with the models of DS process calculation, and some HRS solidification parameters were included, such as withdrawal rate, pouring temperature, etc. The coupled models were used to predict the dendrite grain competitive growth of DD6 superalloy during the DS process. The variation of solute distribution and the dynamic adjustment of dendritic spacing during the process could be predicted by simulating calculation. The DS experiment was carried out with a cylinder sample, and dendrite grains' distribution in the transverse and longitude section was observed by OM and SEM. Then the simulated dendritic morphology was compared with that by experiment. The primary and secondary dendritic spacing by experiment and simulation were measured, and the compared results revealed that as the DS process going on the temperature gradient decreased gradually and the primary dendritic spacing was increasing. So simulation results of the DS dendritic competitive growth were validated by the experiment results, and the proposed models could predict the dendrite grain morphology and the adjustments of DS dendritic spacing of DD6 superalloy very well.

Key words:  CA      DD6 superalloy      directional solidification      dendrite grain growth      numerical simulation     
Received:  18 August 2013     
ZTFLH:  TG132.3  
Fund: Supported by National Basic Research Program of China (No.2011CB706801), National Natural Science Foundation of China (No.51171089) and National Science and Technology Major Project (Nos.2011ZX04014-052 and 2012ZX04012-011)

URL: 

https://www.ams.org.cn/EN/10.3724/SP.J.1037.2013.00496     OR     https://www.ams.org.cn/EN/Y2014/V50/I3/345

Fig.1  

定向凝固炉简化结构示意图

Fig.2  

宏微观耦合计算模型示意图

Fig.3  Schematic of linear interpolation method (x, y, z—macro grids coordinates; l, m, n—micro grids coordinates in x, y and z directions, respectively; TMac , TMacx +1, TMacy +1 and TMacz +1—temperature values of the macro grid present, macro grid of x+1, macro grid of y+1 and macro grid of z+1, respectively; Gx , Gy and Gz —temperature gradients in x, y and z directions, respectively; λx , λy and λz —micro grid lengths in x, y and z directions, respectively)
Fig.4  

DD6合金棒状试样组模图

Parameter Unit Value
Liquidus K 1672[42]
Solidus K 1615[42]
Thermal conductivity kJ/(m·s·K) 0.0332[42]
Specific heat kJ/(kg·K) 0.773[42]
Density kg/m3 8780[42]
Latent heat kJ/kg 99[42]
Mass fraction % 39.006*
Partition 0.788*
Liquidus slope ℃/% -3.95*
Diffusion coefficient in liquid (DL) m2/s 3.6×10-9
Diffusion coefficient in solid (DS) m2/s 1.0×10-12
Gibbs -Thomson coefficient (G) k·m 3.65×10-7[17]
Anisotropy intensity coefficient (g) 0.04
Table 1  Simulating parameters of DD6 superalloy
Fig.5  

DD6合金棒状试样的耦合计算过程

Fig.6  

DD6高温合金枝晶定向生长过程模拟

Fig.7  

DD6高温合金枝晶定向生长溶质分布

Fig.8  

DD6高温合金枝晶定向生长横截面形貌的模拟与实验对比

Fig.9  

DD6高温合金枝晶竞争生长的实验与模拟对比图

Fig.10  

DD6高温合金枝晶定向凝固纵向二次臂形貌的实验与模拟对比结果

Height
mm
1st arm spacing λ 1 / μm 2nd arm spacing λ 2 / μm G
K·mm-1
Exp Simul Exp Simul
10 128.1 133.6 49.4 40.1 4.77
14 206.6 196.6 62.7 49.5 4.10
18 211.0 208.4 58.8 45.5 3.30
26 223.9 201.2 57.6 51.2 2.26
Table 2  Experimental and simulated results of dendritic arm spacing of DD6 superalloy
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