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Acta Metall Sin  2018, Vol. 54 Issue (3): 393-403    DOI: 10.11900/0412.1961.2017.00284
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Finite Element Simulation of the Temperature Field and Residual Stress in GH536 Superalloy Treated by Selective Laser Melting
Shu WEN1, Anping DONG1,2(), Yanling LU3, Guoliang ZHU1,2, Da SHU1,2, Baode SUN1,2,4
1 School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2 Shanghai Key Lab of Advanced High-Temperature Materials and Precision Forming, Shanghai Jiao Tong University, Shanghai 200240, China
3 Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
4 State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China
Cite this article: 

Shu WEN, Anping DONG, Yanling LU, Guoliang ZHU, Da SHU, Baode SUN. Finite Element Simulation of the Temperature Field and Residual Stress in GH536 Superalloy Treated by Selective Laser Melting. Acta Metall Sin, 2018, 54(3): 393-403.

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Abstract  

In the aerospace industry, due to the increasing hardness and tensile strength of nickel-based superalloys, the traditional manufacturing methods are difficult to produce, which limits the freedom of part design and process. Selective laser melting (SLM) has great potential in this field with its additive manufacturing concept and full melting during the process. Although the dense part can be easily obtained in SLM, the residual stresses and micro-cracks in the machining process still affect the dimensional accuracy and reliability of the parts. In SLM process, rapid and complex changes of temperature and stress are observed in the vicinity of the molten pool. Understanding these changes will help to improve the quality of the process. In this work, a finite element model (FEM) is established to calculate the temperature and residual stress distribution near the weld pool during the SLM of Hastelloy X superalloy, The model uses a composite Gauss heat source to consider the influence of optical penetration depth, and implements the transformation of powder, molten pool and solid metal by changing the material properties with temperature. Comparison with the test results shows that the model can simulate the distribution of temperature field and the residual stress in SLM process well. The simulation results show that with the increase of laser power, the width, length and depth of melting pool were enlarged, the cooling rate decreases; with the increase of the scanning speed, the width and depth of melting pool decreases, the length remained unchanged, the cooling rate increase. After cooling, there is a large tensile stress on the surface of the model. As the depth increases, the tensile stress decreases rapidly and eventually becomes compressive stress.

Key words:  GH536 superalloy      selective laser melting      residual stress      finite element simulation     
Received:  07 July 2017     
Fund: Supported by National Natural Science Foundation of China (Nos.51771118, U1760110 and 51674237) and Aeronautical Science Foundation of China (No.2015ZE57011)

URL: 

https://www.ams.org.cn/EN/10.11900/0412.1961.2017.00284     OR     https://www.ams.org.cn/EN/Y2018/V54/I3/393

Fig.1  Finite element model of the selective laser melting (SLM) process
Process parameter Value Unit
Powder bed thickness h 40 μm
Hatch spacing Hs 90 μm
Laser spot size D 100 μm
Scanning speed v 900, 1100, 1300 mms-1
Initial temperature T0 20
Power P 150, 200, 250 W
Table 1  Process parameters for simulation
Fig.2  Low magnified OM (a) and high magnified SEM (b) images show the melt pool morphologies of GH536 superalloy treated by SLM under P=200 W and v=1100 mm/s
Fig.3  Predicted profile temperature contours (a, b) and predicted top surface temperature contours (c, d) at node 1 (a, c) and node 6 (b, d) in Fig.1 under P=200 W and v=1100 mm/s
Fig.4  Predicted profile temperature contours (a, b) and top surface temperature contours (c, d) at node 6 in Fig.1 under P=150 W (a, c) and P=250 W (b, d)
Fig.5  Predicted melt pool size (a) and the ratio of length to width (b) as function of laser power
Fig.6  Predicted profile temperature contours (a, b) and top surface temperature contours (c, d) at node 6 in Fig.1 under v=900 mm/s (a, c) and v=1300 mm/s (b, d)
Fig.7  Predicted melt pool size (a) and the ratio of length to width (b) as function of scanning speed
Fig.8  Cyclic heating and cooling curves at the nodes 2, 3, 4 and 5 in Fig.1 under P=200 W and v=1100 mm/s (Tm—melting point)
Fig.9  Cyclic heating and cooling curves at the node 3 in Fig.1 under v=1100 mm/s and different P
Fig.10  Cyclic heating and cooling curves at the node 3 under P=200 W and different v
Fig.11  Sample for stress test prepared by SLM under P=200 W and v=1100 mm/s
Fig.12  Equivalent residual stress σMises along depth direction with different parameters of v=1100 mm/s (a) and P=200 W (b)
Fig.13  Distributions of residual stress along line 1 in Fig.1 with different parameters(a) x direction and v=1100 mm/s(b) x direction and P=200 W(c) y direction and v=1100 mm/s(d) y direction and P=200 W
Fig.14  Distributions of residual stress along line 2 in Fig.1 with different parameters(a) x direction and v=1100 mm/s(b) x direction and P=200 W(c) y direction and v=1100 mm/s(d) y direction and P=200 W
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