Skip to main content
Log in

A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing

  • Original Paper
  • Published:
Computational Mechanics Aims and scope Submit manuscript

Abstract

In this paper, a parallelized 3D cellular automaton computational model is developed to predict grain morphology for solidification of metal during the additive manufacturing process. Solidification phenomena are characterized by highly localized events, such as the nucleation and growth of multiple grains. As a result, parallelization requires careful treatment of load balancing between processors as well as interprocess communication in order to maintain a high parallel efficiency. We give a detailed summary of the formulation of the model, as well as a description of the communication strategies implemented to ensure parallel efficiency. Scaling tests on a representative problem with about half a billion cells demonstrate parallel efficiency of more than 80% on 8 processors and around 50% on 64; loss of efficiency is attributable to load imbalance due to near-surface grain nucleation in this test problem. The model is further demonstrated through an additive manufacturing simulation with resulting grain structures showing reasonable agreement with those observed in experiments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Acharya R, Sharon JA, Staroselsky A (2017) Prediction of microstructure in laser powder bed fusion process. Acta Mater 124:360–371

    Article  Google Scholar 

  2. Antonysamy AA, Meyer J, Prangnell PB (2013) Effect of build geometry on the \(\beta \)-grain structure and texture in additive manufacture of Ti–6Al–4V by selective electron beam melting. Mater Charact 84:153–168

    Article  Google Scholar 

  3. Al-Bermani SS, Blackmore ML, Zhang W, Todd I (2010) The origin of microstructural diversity, texture, and mechanical properties in electron beam melted Ti–6Al–4V. Metall Mater Trans A 41(13):3422–3434

    Article  Google Scholar 

  4. Boettinger WJ, Warren JA, Beckermann C, Karma A (2002) Phase-field simulation of solidification. Ann Rev Mater Res 32(1):163–194

    Article  Google Scholar 

  5. Carozzani T, Gandin C-A, Digonnet H, Bellet M, Zaidat K, Fautrelle Y (2013) Direct simulation of a solidification benchmark experiment. Metall Mater Trans A Phys Metall Mater Sci 44(2):873–887

    Article  Google Scholar 

  6. Dantzig JA, Rappaz M (2016) Solidification. EPFL Press, Lausanne

    MATH  Google Scholar 

  7. Dezfoli ARA, Hwang W-S, Huang W-C, Tsai T-W (2017) Determination and controlling of grain structure of metals after laser incidence: theoretical approach. Sci Rep 7(41527):1–11

    Google Scholar 

  8. Ferreira AF, da Silva AJ, de Castro JA (2006) Simulation of the solidification of pure nickel via the phase-field method. Mater Res 9(4):349–356

    Article  Google Scholar 

  9. Gandin C-A, Rappaz M (1994) A coupled finite element cellular automaton model for the prediction of dentritic grain structures in solidification processes. Acta Metall Mater 42(7):2233–2246

    Article  Google Scholar 

  10. Gandin C-A, Desbiolles J-L, Rappaz M, Thevoz P (1999) A three-dimensional cellular automation-finite element model for the prediction of solidification grain structures. Metall Mater Trans A 30(12):3153–3165

    Article  Google Scholar 

  11. Gandin C-A, Rappaz M (1997) A 3D cellular automaton algorithm for the prediction of dendritic grain growth. Acta Mater 45(5):2187–2195

    Article  Google Scholar 

  12. Kim Y-T, Goldenfeld N, Dantzig J (2000) Computation of dendritic microstructures using a level set method. Phys Rev E 62(2):2471–2474

    Article  Google Scholar 

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

    Article  Google Scholar 

  14. Lipton J, Glicksman ME, Kurz W (1984) Dendritic growth into undercooled alloy melts. Mater Sci Eng 65:57–63

    Article  Google Scholar 

  15. Liu DR, Reinhart G, Mangelinck-Noel N, Gandin C-A, Nguyen-Thi H, Billia B (2014) Coupled cellular automaton (CA)–finite element (FE) modeling of directional solidification of Al-3.5 wt% Ni alloy: a comparison with X-ray synchrotron observations. ISIJ Int 54(2):392–400

    Article  Google Scholar 

  16. (2015) MPI: a message-passing interface standard. Version 3.1. http://mpi-forum.org/docs/mpi-3.1/mpi31-report.pdf

  17. Panwisawas C, Qiu C, Anderson MJ, Sovani Y, Turner RP, Attallah MM, Brooks JW, Basoalto HC (2017) Mesoscale modelling of selective laser melting: thermal fluid dynamics and microstructural evolution. Comput Mater Sci 126:479–490

    Article  Google Scholar 

  18. Rappaz M, Gandin C-A (1993) Probabilistic modelling of microstructure formation in solidification processes. Acta Metall Mater 41(2):345–360

    Article  Google Scholar 

  19. Rodgers TM, Madison JD, Tikare V, Maguire MC (2016) Predicting mesoscale microstructural evolution in electron beam welding. JOM 68(5):1419–1426

    Article  Google Scholar 

  20. Rodgers TM, Madison JD, Tikare V (2017) Simulation of metal additive manufacturing microstructures using kinetic Monte Carlo. Comput Mater Sci 135:78–89

    Article  Google Scholar 

  21. Scott TJ, Beaulieu TJ, Rothrock GD, O’Connor AC (2016) Economic analysis of technology infrastructure needs for advanced manufacturing: additive manufacturing. In: NIST GCR-16-006, NIST, Gaithersburg, MD

  22. Tan L, Zabaras N (2007) A level set simulation of dendritic solidification of multi-component alloys. J Comput Phys 221(1):9–40

    Article  MathSciNet  MATH  Google Scholar 

  23. Wheeler AA, McFadden GB, Boettinger WJ (1996) Phase-field model for solidification of a eutectic alloy. In: Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, vol 452, no 1946. The Royal Society, pp 495–525

  24. Yan W, Ge W, Qian Y, Lin S, Zhou B, Liu WK, Lin F, Wagner GJ (2017) Multi-physics modeling of single/multiple-track defect mechanisms in electron beam selective melting. Acta Mater 134:324–333

    Article  Google Scholar 

  25. Yin H, Felicelli SD (2010) Dendrite growth simulation during solidification in the LENS process. Acta Mater 58(4):1455–1465

    Article  Google Scholar 

  26. Zhang J, Liou F, Seufzer W, Taminger K (2016) A coupled finite element cellular automaton model to predict thermal history and grain morphology of Ti–6Al–4V during direct metal deposition (DMD). Addit Manuf 11:32–39

    Article  Google Scholar 

  27. Zhao C, Fezzaa K, Cunningham RW, Wen H, Carlo FD, Chen L, Rollett AD, Sun T (2017) Real-time monitoring of laser powder bed fusion process using high-speed X-ray imaging and diffraction. Sci Rep 7(3601):1–11

    Google Scholar 

  28. Zinoviev A, Zinovieva O, Ploshikhin V, Romanova V, Balokhonov R (2016) Evolution of grain structure during laser additive manufacturing. Simulation by a cellular automata method. Mater Des 106:321–329

    Article  Google Scholar 

Download references

Acknowledgements

Gregory J. Wagner and Wing Kam Liu acknowledge the support by the National Science Foundation (NSF) Cyber-Physical Systems (CPS) under Grant No. 359 CPS/CMMI-1646592. Yanping Lian, Wentao Yan, and Wing Kam Liu acknowledge the support by Center for Hierarchical Materials Design (CHiMaD) under Grant No. 70NANB14H012. Stephen Lin acknowledges the support by the NSF Graduate Research Fellowship under Grant No. DGE-1324585.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gregory J. Wagner.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lian, Y., Lin, S., Yan, W. et al. A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing. Comput Mech 61, 543–558 (2018). https://doi.org/10.1007/s00466-017-1535-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00466-017-1535-8

Keywords

Navigation