Comparative Assessment of Physics-Based Computational Models on the NIST Benchmark Study of Molten Pool Dimensions and Microstructure for Selective Laser Melting of Inconel 625


This work presents a comparative assessment of different computation models with considering varying degrees of physics for the challenges within the National Institute of Standards and Technology (NIST) Additive Manufacturing benchmark problem AMB2018-02. The melt pool geometry, cooling rates, and dendritic microstructure of the single laser scan tracks on bare Inconel 625 plates are predicted by three types of computational models, namely the high fidelity welding model, fluid model, and conduction model for two cases without and with the formation of keyholes. The molten pool geometry in terms of its depth, width, and length as well as the cooling rates at the surface is used for comparing simulated results of various approaches against the NIST experimental results from the two testbeds, which are referred to as the additive manufacturing metrology test bed and commercial build machine (CBM) cases. A comparison of the spatial distribution of cooling rates is also presented to illustrate the importance of using a high fidelity welding model. The thermal gradient and the growth rate of the solid-to-liquid interface are used to predict the primary dendrite arm spacing. It is identified that the high fidelity welding model played a pivotal role in achieving accurate predictions of the CBM cases. The CBM cases with a higher laser energy density resulted in keyhole formation, which led to a high aspect ratio of the molten pool shape. Neglecting the keyhole model leads to large under-predictions of the molten pool depth. Additionally, the correct primary dendrite arm spacing prediction of the CBM cases is only possible with the keyhole model.

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  1. 1.

    Fotovvati B, Wayne SF, Lewis G, Asadi E (2018) A review on melt-pool characteristics in laser welding of metals. Adv Mater Sci Eng 2018:1–18.

    CAS  Article  Google Scholar 

  2. 2.

    Lampa C, Kaplan AF, Powell J, Magnusson C (1997) An analytical thermodynamic model of laser welding. J Phys D Appl Phys 30(9):1293

    CAS  Article  Google Scholar 

  3. 3.

    De A, Maiti SK, Walsh CA, Bhadeshia HKDH (2003) Finite element simulation of laser spot welding. Sci Technol Weld Join 8(5):377–384

    Article  Google Scholar 

  4. 4.

    Ye XH, Chen X (2002) Three-dimensional modelling of heat transfer and fluid flow in laser full-penetration welding. J Phys D Appl Phys 35(10):1049

    CAS  Article  Google Scholar 

  5. 5.

    Lei YP, Murakawa H, Shi YW, Li XY (2001) Numerical analysis of the competitive influence of marangoni flow and evaporation on heat surface temperature and molten pool shape in laser surface remelting. Comput Mater Sci 21(3):276–290

    CAS  Article  Google Scholar 

  6. 6.

    NIST (2018) Additive manufacturing benchmark test series (AM-Bench) AMB2018-02 description. Accessed 15 Mar 2020

  7. 7.

    Levine L, Lane B, Heigel J, Migler K, Stoudt M, Phan T, Ricker R, Strantza M, Hill M, Zhang F, Seppala J (2020) Outcomes and conclusions from the 2018 AM-Bench measurements, challenge problems, modeling submissions, and conference. Integr Mater Manuf Innov 9(1):1–15

    Article  Google Scholar 

  8. 8.

    Fan Z, Li B (2019) Meshfree simulations for additive manufacturing process of metals. Integr Mater Manuf Innov 8(2):144–153

    Article  Google Scholar 

  9. 9.

    Gan Z, Lian Y, Lin SE, Jones KK, Liu WK, Wagner GJ (2019) Benchmark study of thermal behavior, surface topography, and dendritic microstructure in selective laser melting of Inconel 625. Integr Mater Manuf Innov 8(2):178–193

    Article  Google Scholar 

  10. 10.

    Kollmannsberger S, Carraturo M, Reali A, Auricchio F (2019) Accurate prediction of melt pool shapes in laser powder bed fusion by the non-linear temperature equation including phase changes. Integr Mater Manuf Innov 8(2):167–177

    Article  Google Scholar 

  11. 11.

    Robichaud J, Vincent T, Schultheis B, Chaudhary A (2019) Integrated computational materials engineering to predict melt-pool dimensions and 3D grain structures for selective laser melting of inconel 625. Integr Mater Manuf Innov 8(3):305–317

    Article  Google Scholar 

  12. 12.

    Ribic BD (2011) Modeling of plasma and thermo-fluid transport in hybrid welding. Pennsylvania State University.

  13. 13.

    Lane B, Heigel J, Ricker R, Zhirnov I, Khromschenko V, Weaver J, Phan T, Stoudt M, Mekhontsev S, Levine L (2020) Measurements of melt pool geometry and cooling rates of individual laser traces on IN625 bare plates. Integr Mater Manuf Innov 9(1):15–30.

    Article  Google Scholar 

  14. 14.

    Tan W, Bailey NS, Shin YC (2013) Investigation of keyhole plume and molten pool based on a three-dimensional dynamic model with sharp interface formulation. J Phys D Appl Phys 46(5):055501

    Article  Google Scholar 

  15. 15.

    Hong KM, Shin YC (2016) Analysis of microstructure and mechanical properties change in laser welding of Ti6Al4V with a multi-physics prediction model. J Mater Process Technol 237:420–429

    CAS  Article  Google Scholar 

  16. 16.

    Semak V, Matsunawa A (1997) The role of recoil pressure in energy balance during laser materials processing. J Phys D Appl Phys 30(18):2541

    CAS  Article  Google Scholar 

  17. 17.

    Matsunawa A, Katayama S, Susuki A, Ariyasu T (1986) Laser production of metallic ultra-fine particles. Trans JWRI 15(2):61–72

    Google Scholar 

  18. 18.

    Ordal MA, Bell RJ, Alexander RW, Long LL, Querry MR (1987) Optical properties of Au, Ni, and Pb at submillimeter wavelengths. Appl Opt 26(4):744–752

    CAS  Article  Google Scholar 

  19. 19.

    Rakić AD, Djurišić AB, Elazar JM, Majewski ML (1998) Optical properties of metallic films for vertical-cavity optoelectronic devices. Appl Opt 37(22):5271–5283

    Article  Google Scholar 

  20. 20.

    Ordal MA, Bell RJ, Alexander RW, Long LL, Querry MR (1985) Optical properties of fourteen metals in the infrared and far infrared: Al Co, Cu, Au, Fe, Pb, Mo, Ni, Pd, Pt, Ag, Ti, V, and W. Appl Opt 24(24):4493–4499

    CAS  Article  Google Scholar 

  21. 21.

    Capriccioli A, Frosi P (2009) Multipurpose ANSYS FE procedure for welding processes simulation. Fusion Eng Des 84(2–6):546–553

    CAS  Article  Google Scholar 

  22. 22.

    Pawel RE, Williams RK (1985) Survey of physical property data for several alloys (No. ORNL/TM--9616). Oak Ridge National Lab.

  23. 23.

    Sabau AS, Yuan L, Raghavan N, Bement M, Simunovic S, Turner JA, Gupta VK (2020) Fluid dynamics effects on microstructure prediction in single-laser tracks for additive manufacturing of IN625. Metall Mater Trans B 51(3):1–19

    Article  Google Scholar 

  24. 24.

    Sainte-Catherine C, Jeandin M, Kechemair D, Ricaud JP, Sabatier L (1991) Study of dynamic absorptivity at 10.6 µm (CO2) and 1.06 µm (Nd-YAG) wavelengths as a function of temperature. Le J de Phys IV. 1(7):151–157

    Google Scholar 

  25. 25.

    Zhao D, Chaudhury PK, Frank RB, Jackman LA (1994) Flow behavior of three 625 type alloys during high temperature deformation. In: Superalloys 718, 625, 706 and various derivatives, pp. 625–706

  26. 26.

    Stoudt MR, Williams ME, Levine LE, Creuziger A, Young SA, Heigel JC, Lane BM, Phan TQ (2020) Location-specific microstructure characterization within In625 additive manufacturing benchmark test artifacts. Integr Mater Manuf Innov 9(1):1–16.

    Article  Google Scholar 

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K.H. was supported by the fund from the Donald A. & Nancy G. Roach Professorship at Purdue University during the course of this research. This research was supported, in part, by the National Science Foundation Graduate Research Fellowship Program under Grant No. 1842166 for C.G. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Correspondence to Yung C. Shin.

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Hong, KM., Grohol, C.M. & Shin, Y.C. Comparative Assessment of Physics-Based Computational Models on the NIST Benchmark Study of Molten Pool Dimensions and Microstructure for Selective Laser Melting of Inconel 625. Integr Mater Manuf Innov 10, 58–71 (2021).

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  • Additive manufacturing
  • Modeling
  • Inconel 625
  • Benchmarking