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Parameters Determination of grain Microstructure Prediction for a Single Crystal Casting Simulation and Its Experimental Validation

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Abstract

Microstructure prediction is very important in single crystal casting simulation. In order to predict microstructure accurately, both grain nucleation and dendrite growth have to be modeled properly beside the correct setups on geometry, alloy chemistry, thermal/fluid, and processing conditions. For nucleation, the classic normal Gaussian distribution nucleation model was used. An extended KGT model was applied to predict the dendrite growth of multicomponent alloy castings. There are several parameters for both nucleation and growth models which are difficult to measure experimentally. The growth coefficients in the growth model are normally chemistry dependent. All parameters are critical to assure the reliability of the simulation. The current paper shows how to determine those parameters with the comprehensive knowledge of physics and its implementation behind the simulation model. It is intended to shed some light for the readers to better apply this model in their grain structure simulations, particularly on DC and single crystal castings, in the future by applying the presented methodology of the parameter determination in this paper. An even more important one is that a large amount of experiments have been performed. Excellent agreement has been reached statistically between experiment and simulation in terms of grain mis-orientation.

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References

  1. J. Guo, M. Samonds, Modeling of microstructures and mechanical properties of α + β Ti based alloys. Mater. Sci. Technol. 3, 41–50 (2005)

    Google Scholar 

  2. P. Carter, D.C. Cox, C.A. Gandin, R.C. Reed, Process modelling of grain selection during the solidification of single crystal superalloy castings. Mater. Sci. Eng. A 280(2, 31), 233–246 (2000)

    Article  Google Scholar 

  3. X.L. Yang, H.B. Dong, W. Wang, P.D. Lee, Microscale simulation of stray grain formation in investment cast turbine blades. Mater. Sci. Eng. A 386(1–2), 129–139 (2004)

    Article  Google Scholar 

  4. N. D’Souza, M.G. Ardakani, M. McLean, B.A. Shollock, Directional and single-crystal solidification of Ni-base superalloys: Part I. The role of curved isotherms on grain selection. Metall. Mater. Trans. A 31(11), 2877–2886 (2000)

    Article  Google Scholar 

  5. H. Esaka, K. Shinozuka, M. Tamura, Analysis of single crystal casting process taking into account the shape of pigtail. Mater. Sci. Eng. A 413–414(15), 151–155 (2005)

    Article  Google Scholar 

  6. N. Wang et al., Simulation of grain selection during single crystal casting of a Ni-base superalloy. J. Alloys Compd. 586(15), 220–229 (2014)

    Article  CAS  Google Scholar 

  7. F. Wang et al., A high thermal gradient directional solidification method for growing superalloy single crystals. J. Mater. Process. Technol. 214(12), 3112–3121 (2014)

    Article  CAS  Google Scholar 

  8. D. Szeliga, K. Kubiak, G. Jarczyk, The influence of the radiation baffle on predicted temperature gradient in single crystal cmsx-4 castings. Int. J. Metalcast. 7, 17–23 (2013)

    Article  Google Scholar 

  9. ProCAST user manual, ESI Group, (2016)

  10. M. Rappaz, P. Thevoz, Solute diffusion model for equiaxed dendritic growth. Acta Metall. 35, 1487–1497 (1987)

    Article  CAS  Google Scholar 

  11. M. Rappaz, P. Thevoz, Solute diffusion model for equiaxed dendritic growth: analytical solution. Acta Metall. 35, 2929–2933 (1987)

    Article  CAS  Google Scholar 

  12. P. Thevoz, J.L. Desbiolles, M. Rappaz, Modeling of equiaxed microstructure formation in casting. Metall. Trans. A 20, 311–322 (1989)

    Article  Google Scholar 

  13. W. Kurz, B. Giovanola, R. Trivedi, Theory of microstructural development during rapid solidification. Acta Metall. 34(5), 823–830 (1986)

    Article  CAS  Google Scholar 

  14. M. Rappaz, W. Boettinger, On dendritic solidification of multicomponent alloys with unequal liquid diffusion coefficients. Acta Mater. 47(11), 3205–3219 (1999)

    Article  CAS  Google Scholar 

  15. Standard test method for determining the orientation of a metal crystal. ASTM E82/E82 M - 1 (2014)

Download references

Acknowledgements

The authors gratefully acknowledge financial support received through the Science and Technology Innovation Commission of Shenzhen Municipality on Shenzhen Peacock Plan and the Research of the Key Technologies of High Strength High Temperature Alloys and Its Powder Manufacturing (JSGG20150731142227736).

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Correspondence to Z. Liu.

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Liu, Z., Sun, H., Xu, F. et al. Parameters Determination of grain Microstructure Prediction for a Single Crystal Casting Simulation and Its Experimental Validation. Inter Metalcast 12, 861–869 (2018). https://doi.org/10.1007/s40962-018-0220-9

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  • DOI: https://doi.org/10.1007/s40962-018-0220-9

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