Investment casting of nozzle guide vanes from nickel-based superalloys: part II – grain structure prediction
Source abstract
Abstract
Abstract The control of grain structure, which develops during solidification processes in investment casting of nozzle guide vanes (NGVs), is a key issue for optimization of their mechanical properties. The main objective of this part of the work was to develop a simulation tool for predicting grain structure in the new generation NGVs made from MAR-M247 Ni-based superalloy. A cellular automata - finite element (CAFE) module is employed to predict the three-dimensional (3D) grain structure in the as-cast NGV. The grain structure in the critical sections of the experimentally cast NGV is carefully analyzed, the experimental results are compared with the modeling outcomes, and the model is calibrated via tuning parameters which govern grain nucleation and growth. The grain structures predicted by the calibrated model show a very good accordance with the real ones observed in the critical sections of the as-cast NGV. It is demonstrated that the calibrated CAFE model is a reliable tool for the foundry industry to predict grain structure of the as-cast NGVs with very high accuracy.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Aluminum Alloy Microstructure Properties · Solidification and crystal growth phenomena · Metallurgy and Material Forming
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (31)
Show source-provided references
1. Janssens KGF, Raabe D, Miodownik Y, Kozeschnik MA, Nestler B: Computational Materials Engineering. Elsevier Academic Press, Burlington, MA, USA; 2007.
2. Penrose O, Fife PC: Thermodynamically consistent models of phase-field type for the kinetic of phase transitions. Phys D 1990, 43: 44–62. doi:10.1016/0167–27890167–2789(90)90015-H10.1016/0167-2789(90)90015-H ↗
3. Wang SL, Sekerka RF, Wheeler AA, Coriell SR, Murray BT, Braun RJ, McFadden GB: Thermodynamically-consistent phase-field models for solidification. Phys D 1993, 69: 189–200. doi:10.1016/0167–27890167–2789(93)90189–810.1016/0167-2789(93)90189-8 ↗
4. Caginalp G, Fife PC: Phase field methods of interfacial boundaries. Phys Rev B 1986, 33: 7792–7794. doi:10.1103/PhysRevB.33.779210.1103/PhysRevB.33.7792 ↗
5. Lowen H, Bechoefer J, Tuckerman LS: Crystal growth at long times: critical behavior at the crossover from diffusion to kinetics-limited regimes. Phys Rev A 1992, 45: 2399–2415. doi:10.1103/PhysRevA.45.239910.1103/PhysRevA.45.2399 ↗
6. Warren JA, Boettinger WJ: Prediction of dendritic growth and microsegregation patterns in a binary alloy using the phase-field method. Acta Metall Mater 1994, 43: 689–703. doi:10.1016/0956–7151(94)00285-P10.1016/0956-7151(94)00285-P ↗
7. Kobayashi R: Modeling and numerical simulations of dendritic crystal-growth. Phys D 1993, 63: 410–423. doi:10.1016/0167–2789(93)90120-P10.1016/0167-2789(93)90120-P ↗
8. Wheeler AA, Murray BT, Schaefer RJ: Computation of dendrites using a phase field model. Phys D 1993, 66: 243–262. doi:10.1016/0167–27890167–2789(93)90242-S10.1016/0167-2789(93)90242-S ↗
9. Wang SL, Sekerka RF: Algorithms for phase eld computations of the dendritic operating state at large su-. percoolings. J Comp Phys 1996, 127: 110–117. 10.1006/jcph.1996.016110.1006/jcph.1996.0161 ↗
10. Provatas N, Goldenfeld N, Dantzig J: Efficient computation of dendritic microstructures using adaptive mesh refinement. Phys Rev Lett 1998, 80: 3308–3311. doi:10.1103/PhysRevLett.80.330810.1103/PhysRevLett.80.3308 ↗
11. Chen LQ, Young W: Computer simulation of the domain dynamics of a quenched system with a large number of nonconserved order parameters: the grain-growth kinetics. Phys Rev B 1994, 50: 15752–15756. doi:10.1103/PhysRevB.50.1575210.1103/PhysRevB.50.15752 ↗
12. Chen LQ: A novel computer simulation technique for modeling grain growth. Scr Metall Mater 1995, 32: 115–120. doi:10.1016/S0956–716X(99)80022–310.1016/S0956-716X(99)80022-3 ↗
13. Steinbach I, Pezzolla F, Nestler B, Seesselberg M, Schmitz GJ, Rezende J: A phase field concept for multiphase systems. Phys D 1996, 94: 135–147. doi:10.1016/0167–27890167–2789(95)00298–710.1016/0167-2789(95)00298-7 ↗
14. Nestler B, Wheeler AA: Anisotropic multi-phase-field model: interfaces and junctions. Phys Rev E 1998, 57: 2602–2609. doi:10.1103/PhysRevE.57.260210.1103/PhysRevE.57.2602 ↗
15. Kobayashi R, Warren JA, Carter WC: Vector-valued phase field model for crystallization and grain boundary formation. Phys D 1998, 119: 415–423. doi:10.1016/S0167–2789(98)00026–810.1016/S0167-2789(98)00026-8 ↗
16. Garcke H, Nestler B, Stoth B: On anisotropic order parameter models for multi-phase systems and their sharp interface limits. Phys D 1998, 115: 87–108. doi:10.1016/S0167–2789(97)00227–310.1016/S0167-2789(97)00227-3 ↗
17. Boettinger WJ, Warren JA: The phase-field method: simulation of alloy dendritic solidification during recalescence. Metall Mater Trans A 1996, 27: 657–669. doi:10.1007/BF0264895310.1007/BF02648953 ↗
18. Hesselbarth HW, Göbel IR: Simulation of recrystallization by cellular automata. Acta Metall 1991, 39: 2135–2143. 10.1016/0956-7151(91)90183-210.1016/0956-7151(91)90183-2 ↗
19. Wang W, Kermanpur A, Lee PD, McLean M: Simulation of dendritic growth in the platform region of single crystal superalloy turbine blades. J Mater Sci 2003, 38: 4385–4391. doi:10.1023/A:102630372054410.1023/A:1026303720544 ↗
20. Wang W, Lee PD, McLean M: A model of solidification microstructures in nickel based superalloys: predicting primary dendrite spacing selection. Acta Mater 2003, 51: 2971–2987. doi:10.1016/S1359–6454(03)00110–110.1016/S1359-6454(03)00110-1 ↗
21. Rappaz M, Gandin CA: Probabilistic modelling of microstructure formation in solidification processes. Acta Metall Mater 1993, 41: 345–360. doi:10.1016/0956–7151(93)90065-Z10.1016/0956-7151(93)90065-Z ↗
22. Gandin CA, Rappaz M: A coupled finite element-cellular automaton model for the prediction of dendritic grain structures in solidification processes. Acta Metall Mater 1994, 42: 2233–2246. doi:10.1016/0956–7151(94)90302–610.1016/0956-7151(94)90302-6 ↗
23. Gandin CA, Rappaz M: A 3D cellular automaton algorithm for the prediction of dendritic grain growth. Acta Mater 1997, 45: 2187–2195. doi:10.1016/S1359–6454(96)00303–510.1016/S1359-6454(96)00303-5 ↗
24. Kurz W, Giovanola B, Trivedi R: Theory of microstructural development during rapid solidification. Acta Metall 1986, 34: 823–830. doi:10.1016/0001–6160(86)90056–810.1016/0001-6160(86)90056-8 ↗
25. Gandin CA, Rappaz M, Desbiolles JL, Lopez R, Swierkosz M, Thevoz PH (1997) 3D modeling of dendritic grain structures in turbine blade investment cast parts. In: Loria EA (ed) Proceedings of the TMS Meeting. TMS, p 12110.7449/1997/Superalloys_1997_121_130 ↗
26. Seo SM, Kim IS, Jo CY, Ogi K: Grain structure prediction of Ni-base superalloy castings using the cellular automaton-finite element method. Mater Sci Eng A 2007, 449–451: 713–716. doi:10.1016/j.msea.2006.02.40010.1016/j.msea.2006.02.400 ↗
27. Wang N, Liu L, Gao S, Zhao X, Huang T, Zhang J, Fu H: Simulation of grain selection during single crystal casting of a Ni-base superalloy. J Alloys Compd 2014, 586: 220–229. doi:10.1016/j.jallcom.2013.10.03610.1016/j.jallcom.2013.10.036 ↗
28. Gandin CA, Desbiolles JL, Rappaz M, Thevoz P: A three-dimensional cellular automation-finite element model for the prediction of solidification grain structures. Metall Mater Trans A 1999, 30: 3153–3165. doi:10.1007/s11661–999–0226–210.1007/s11661-999-0226-2 ↗
29. Lipton J, Glicksman ME, Kurz W: Equiaxed dendrite growth in alloys at small supercooling. Metall Trans A 1987, 18: 341–345. doi:10.1007/BF0282571610.1007/BF02825716 ↗
30. ProCast user Manual & Technical Reference:Technical Reference (2007). Version 6.1. ESI software, France; 2007.
31. Qingyan X, Baicheng L, Dong P, Jing Y: Progress on modeling and simulation of directional solidification of superalloy turbine blade casting. Res Develop 2012, 2: 69–77.