Simulation of microstructures for Alloy 718 blade forging using 3D FEM simulator

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1 Journal of Materials Processing Technology 141 (2003) Simulation of microstructures for Alloy 718 blade forging using 3D FEM simulator Young-Sang Na a,, Jong-Taek Yeom a, Nho-Kwang Park a, Jai-Young Lee b a Metal Working and Plasticity Group, Korea Institute of Machinery and Materials, 66 Sangnam-Dong, Changwon, Kyungnam , South Korea b Department of Materials Science and Engineering, KAIST, Kusong-Dong, Yusong-Gu, Daejon , South Korea Received 9 August 2001; received in revised form 20 March 2002; accepted 10 February 2003 Abstract Mechanical properties of Ni Cr Fe-based Alloy 718 depend very much on the grain size, as well as the presence of strengthening phases, and. The grain size of superalloy parts can be controlled by the thermo-mechanical processes, including heating, forging and cooling sequences. In order to predict the evolution of grain size in Alloy 718 blade forging, a series of constitutive equations for dynamic recrystallization, meta-dynamic recrystallization and grain growth were developed and implemented into a 3D FE simulator. The evolution of grain structure in the process of two-step blade forging of Alloy 718 was simulated using the 3D FE simulator combined with a microstructure module. The microstructure prediction tool was validated by comparing the simulated grain structure with that of the experimental blade-type forging Elsevier Science B.V. All rights reserved. Keywords: Microstructure control; Blade forging; Dynamic recrystallization; Meta-dynamic recrystallization; Alloy Introduction As the demand for cost-effective and highly efficient turbine engine increases, importance of the ability to predict and control the microstructure of a superalloy forging also increases. With the development of computer-hardware and numerical processing technology, there have been many efforts for predicting microstructural change during deformation processing, which includes the incorporation of microstructure prediction module in the conventional FE code for metal flow simulation [1] as well as the Bayesian neural networks and Gaussian process [2 4]. In this research, a microstructure prediction module is implemented into a conventional FE code based on the analytical understanding of the microstructural change in wrought superalloy Alloy 718 during deformation processing and post-heat treatment. Constitutive models were used for the prediction of grain structure in forged Alloy 718. Grain growth, dynamic recrystallization and meta-dynamic recrystallization were taken into account. Some of the microstructure simulation results were validated by comparing the simulated microstructure with that of the actual forgings. Corresponding author. address: nys1664@kmail.kimm.re.kr (Y.-S. Na). 2. Experimental procedure The material used in this study was the nickel-based Alloy 718 billet of 5.4 wt.% Nb + Ta. In order to formulate the microstructural change during hot deformation, a series of isothermal compression tests were carried out up to an axial strain of 0.7 within the temperature range C and strain rate range to 10 s 1 under the constant strain rate condition. The detailed compression test procedure has been presented elsewhere [5]. To investigate the meta-dynamic recrystallization, hold times were given to the compressed specimens up to 60 s after releasing the compression load. The specimens were quenched by purged N 2 gas as soon as the compression tests with or without the hold time were completed. The initial average grain size, m was chosen to investigate its effect on dynamic and meta-dynamic recrystallization. Simple-shaped blades were forged using a 1800 t screw press. A two-step blade forging route was employed, i.e. upsetting of the cylindrical billets with a tapered end in the first step, and the finish forging of a blade in the second step. In order to reduce die friction and get smooth deformation, graphite lubricant was spread onto the upper die and the lower die. The forging temperature was 1010 C. The transfer and preparation time of the workpiece was less than 10 s /$ see front matter 2003 Elsevier Science B.V. All rights reserved. doi: /s (03)

2 338 Y.-S. Na et al. / Journal of Materials Processing Technology 141 (2003) Table 1 Materials property data used for FEM analysis Workpiece, Alloy 718 Die, SKD61 (AISI H-13) Mechanical properties Young s modulus (MPa) Rigid Poisson s ratio 0.37 Rigid Flow stress Material DB in FE code Rigid Thermal properties Thermal expansion coefficient ( C) Thermal conductivity (N/(s C)) Heat capacity (N/(mm 2 C)) Emissivity For the deformation and microstructure simulation, heat dissipation of the workpiece during the transfer from the furnace to the die and dwell-on-it was considered and the resultant temperature values of the nodal points for the workpiece elements were used as an initial temperature distribution for the simulation. Both heat transfer and deformation were considered during the forging simulation. For the microstructure simulation, user-defined subroutines, which include the constitutive equations for grain growth, dynamic recrystallization and meta-dynamic recrystallization, were implemented into the commercial FE code. A non-isothermal rigid-plastic FE code was employed for the simulation of the forging processes. Some details regarding FE simulation are given in Table 1. The initial solid elements of the workpiece were around and automatic remeshing system was adopted during simulation. A friction factor of 0.3 and a die temperature of 300 C were used as input parameters. The state variables obtained from the FE simulations based on large deformation were used for the simulation of the grain distribution of the forged parts. The average grain size, measured from the samples heated and held in furnace for the following forging process was selected as initial grain size for microstructure simulation. Dynamic recrystallization varies from element to element depending on the strain rate and temperature. So dynamic recrystallization module starts to operate when the effective true strain of an element becomes larger than the critical strain for dynamic recrystallization. 3. Results and discussions 3.1. Constitutive models for microstructural change From the true stress vs. true strain curves obtained under various strain rates and temperatures, one can obtain the variation of hardening rate (dσ/dε) with strain. The critical strain (ε c ) for the onset of dynamic recrystallization can be obtained from the inflection point in the curves. The detailed approach is presented elsewhere [5]. The critical strain is about 0.8 times the peak strain, which corresponds to the peak stress in the plot of the true strain vs. true stress [6]. The constitutive equations for the critical strain are expressed as functions of initial grain size (d 0 ) and Zener Holloman parameter (Z) in Table 2. Dynamic recrystallization occurs typically near grain boundaries, forming a necklace microstructure as shown in Fig. 1. The variations of the volume fraction of dynamically recrystallized grains (X dyn ) with strain were fitted to an Avrami-type equation as shown in Fig. 2. The dynamic recrystallization shows different behavior below and above 1038 C that is the dissolution temperature of phase acting as an obstacle against grain boundary movement. Table 2 Mathematical models for the microstructure evolution of Alloy 718 forging Critical strain ε c = d0 0.2Z0.099 when ε 0.01 s 1 ε c = d Z when ε<0.01 s 1 Meta-dynamic recrystallization ( ( ) ) t 1 ( ) X mdyn = 1 exp ln 2, t 0.5 = d0 0.5 t ε 2.0 ε 0.08 exp 0.5 T d mdyn = 8.28 d ε 0.14 Z 0.03 Dynamic recrystallization ( ( ) ) ε 1.68 X dyn = 1 exp ln 2 ε 0.5 ( ( ) ) ε 1.90 X dyn = 1 exp ln 2 ε 0.5 when T 1038 C,ε 0.5 = d Z0.058 when T>1038 C,ε 0.5 = d Z0.058 d dyn = Z Grain growth ( ) d 3 d0 3 = t exp RT

3 Y.-S. Na et al. / Journal of Materials Processing Technology 141 (2003) Fig. 1. Dynamic recrystallization occurring near given boundary after compression tests at: (a) 954 C, 5 s 1 ; (b) 1066 C, 5 s 1. Fig. 2. Variation of the volume fraction of dynamically recrystallized grains with strain. Dynamically recrystallized grain size (d dyn ) was expressed as a function of Zener Holloman parameter as suggested by Shen et al. [1,7]. The formulated equations for dynamic recrystallization are given in Table 2. Meta-dynamic recrystallization takes place at a high rate during the high temperature holding after compression test. An example of microstructure change during holding time of 5 s is shown in Fig. 3. Fig. 4 shows that the recrystallization fraction increases with increasing hold time. The volume fraction (X mdyn ) and the average diameter (d mdyn )of meta-dynamically recrystallized grains also depend on initial grain size, accumulated strain, temperature and strain rate. The meta-dynamic recrystallization models constructed in the present study are tabulated in Table 2. Itishowever to be noted that the meta-dynamic recrystallization was neglected in simulating the microstructure of the conventional blade forging since the forged blade did not experience post-forging heat treatment. Experimental data and constitutive model for grain growth are also presented in Fig. 5 and Table 2, respectively. Fig. 3. Occurrence of meta-dynamic recrystallization after 5 s holding: (a) 1020 C, 1 s 1 and 0 s holding; (b) 1020 C, 1 s 1 and 5 s holding.

4 340 Y.-S. Na et al. / Journal of Materials Processing Technology 141 (2003) Fig. 4. Variation of meta-dynamic recrystallization fraction with the holding time. Fig. 5. Experimental data and calculation for grain growth Blade forging and its microstructure simulation A two-step forging route was employed for the blade forging as shown in Fig. 6. Before upsetting and finish forging, the workpiece was heated to the forging temperature and held for about min depending on the thickness of the workpiece. The grain structure after the upset forging is presented in Fig. 7. The typical microstructure of each part, together with the simulated microstructure contour is presented for comparison. After upsetting, the grain structure of part (A) in Fig. 7 was found to be completely different from that of the other regions. The recrystallized volume fraction Fig. 6. Two-step forging route for blade forging. and average grain size were measured by analyzing all the optical micrographs taken from the forgings. Average grain size (D ave ) was calculated by applying the additive rule, i.e. D ave = D drx f drx + D 0 (1 f drx ), where D drx, D 0 and f drx are the dynamically recrystallized grain size, the initial grain size just before forging and the fraction of dynamic recrystallization, respectively. In the upset forging, complete dynamic recrystallization occurred in part (A), while almost no dynamic recrystallization occurred in part (B). This is because the effective strain in part (B) was lower than the critical strain for the onset of dynamic recrystallization. The average grain size of part (A) is about 6 m, while it is about 37 m in part (B). Even if the recrystallization was concentrated to the blade platform region (part (A)) in the upset forging, the grain size of the workpiece for finish forging became uniform due to grain growth during holding at the forging temperature for 30 min. Thus, the microstructure of the finish forging was not significantly affected by the upset microstructure because of the grain growth occurring during reheating of the preform. Typical grain structure of the finish forging is shown in Fig. 8, together with the simulated microstructure contour, too. Center part (A) of the airfoil section shows a fully recrystallized grain structure, while surface area (B) shows a partially recrystallized necklace structure due to low temperature and limited strain. The root and platform area in the finish forging indicated that dynamic recrystallization did not occur because the applied strain was not enough in the finish forging. The dynamically recrystallized grain size and the recrystallization fraction are very similar to the calculated results as shown in Figs. 7 and 8. However the observed grain sizes tend to be slightly larger than the calculated ones within the unrecrystallized or the partially recrystallized region. It is difficult to measure the tiny recrystallized grain sizes existing near the original grain boundaries, i.e., the actual average grain size can be smaller than the measured one. Some overestimation of the average grain size will take place in the region where the calculated recrystallization fraction is lower than 0.3. The inhomogeneous distribution of strain and temperature leads to a different grain structure depending on the location within the finish forging. Most of the blade airfoil shows a highly recrystallized structure. At the center, the fully recrystallized structure was predicted which is shown in Fig. 8. On the other hand, the simulation indicates that the recrystallized fraction is just about 0.2 near the surface of the blade airfoil as observed in Fig. 8. Simulation also indicates that dynamic recrystallization did not take place in the platform area, and this is experimentally validated. The average grain size is almost the same as the predicted one. If minor errors are allowed in microstructure simulation, the 3D microstructure simulation module will be a useful tool for the blade forging process design. In this research, a uniform grain structure was not obtained in as-forged part. It can however be possible to get more uniform structure via

5 Y.-S. Na et al. / Journal of Materials Processing Technology 141 (2003) Fig. 7. Actual grain structure and simulated microstructure contour of the upset forging: (a) recrystallization fraction; (b) recrystallized grain size ( m); (c) average grain size ( m). Fig. 8. Actual grain structure and simulated microstructure contour of the finish forging: (a) recrystallization fraction; (b) recrystallized grain size ( m); (c) average grain size ( m). post-heat treatment using the driving force for meta-dynamic recrystallization. 4. Conclusions 1. Dynamic recrystallization and meta-dynamic recrystallization were modeled for Alloy 718 in the present study. The critical strain indicating the beginning of dynamic recrystallization can be expressed in the numerical form as a function of strain rate, strain and temperature. 2. Numerical equations for the critical strain, dynamic recrystallization, meta-dynamic recrystallization and grain growth have been implemented into FE code to predict microstructure changes during the deformation processes. The strain and temperature distribution simulated by FE code together with the implemented microstructure module can be effectively used to predict the evolution of microstructures of the workpiece. 3. The comparison of the present 3D FE module with the actual microstructure of two-step forged blade has

6 342 Y.-S. Na et al. / Journal of Materials Processing Technology 141 (2003) successfully validated its effectiveness in the prediction of microstructures. References [1] G. Shen, J. Rollins, D. Furrer, Microstructure modeling of forged waspaloy discs, in: R.D. Kissinger (Ed.), Superalloys 1996, TMS, Warrendale, PA, 1996, pp [2] C.A.L. Bailer-Jones, T.J. Sabin, D.J.C. MacKay, P.J. Withers, Prediction of deformed and annealed microstructures using Bayesian neural networks and Gaussian processes, in: T. Chandra (Ed.), Proceedings of the IPMM 97, vol. 2, Gold Coast, Australia, July 14 17, 1997, pp [3] T.J. Sabin, C.A.L. Bailer-Jones, S.M. Roberts, D.J.C. MacKay, P.J. Withers, Modelling the evolution of microstructures in cold-worked and annealed aluminium alloy, in: T. Chandra (Ed.), Proceedings of the THERMEC 97, TMS, Warrendale, PA, 1997, pp [4] T.J. Sabin, S.M. Roberts, P.J. Withers, C.A.L. Bailer-Jones, Gaussian process modelling of the evolution of microstructure in cold-worked aluminium magnesium alloys, in: Proceedings of the International Conference on Forging and Related Technology (ICFT 98), National Motorcycle Museum, Birmingham, UK, April 27 28, 1998, pp [5] N.-K. Park, J.-T. Yeom, Y.-S. Na, I.S. Kim, D.H. Kim, S.J. Choe, Two step forging of Alloy 718, in: Proceedings of the International Symposium on Superalloys 718, 625, 706 and Various Derivatives, June 15 18, 1997, TMS, Pittsburgh, USA. [6] G. Krauss (Ed.), Deformation, Processing, and Structure, ASM, St. Louis, Missouri, October 23, [7] G. Shen, S.L. Semiatin, R. Shivpuri, Modeling microstructural development during the forging of waspaloy, Met. Trans. A 26 (1995)