Abstract
Dendrites are one of the most widely observed patterns in nature, and occur across a wide spectrum of physical phenomena—from snow flakes to river basins; from bacterial colonies to lungs and vascular systems; and in solidification and growth patterns in metals and crystals. The ubiquitous occurrence of these “tree-like” structures can be attributed to their excellent space-filling properties, and at times, dendritic structures also spatially manifest fractal-like distributions. As is the case with many fractal-like geometries, the complex multi-level branching structures in dendrites pose a modeling challenge, and a full resolution of dendritic structures is computationally very demanding. In the literature, extensive theoretical models of dendritic formation and evolution, essentially as extensions of the classical moving boundary Stefan problem exist. Much of this understanding is from the analysis of dendrites occurring during the solidification of metallic alloys, as this is critical for understanding microstructure evolution during metal manufacturing processes that involve solidification of a liquid melt. Motivated by the problem of modeling microstructure evolution from liquid melts of pure metals and metallic alloys during metal additive manufacturing, we developed a comprehensive numerical framework for modeling a large variety of dendritic structures that are relevant to metal solidification. In this work, we present a numerical framework encompassing the modeling of Stefan problem formulations relevant to dendritic evolution using a phase-field approach and a finite element method implementation. Using this framework, we model numerous complex dendritic morphologies that are physically relevant to the solidification of pure melts and binary alloys. The distinguishing aspects of this work are—a unified treatment of both pure metals and alloys; novel numerical error estimates of dendritic tip velocity; and the study of error convergence of the primal fields of temperature and the order parameter with respect to numerical discretization. To the best of our knowledge, this is a first of its kind study of numerical convergence of the phase-field equations of dendritic growth in a finite element method setting. Further, using this numerical framework, various types of physically relevant dendritic solidification patterns like single equiaxed, multi-equiaxed, single columnar and multi-columnar dendrites are modeled in two-dimensional and three-dimensional computational domains.
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References
Rubinstein LI (1971) The stefan problem, transl. math. Monographs 27:327–3
Meyer Gunter H (1978) The numerical solution of stefan problems with front-tracking and smoothing methods. Appl Math Comput 4(4):283–306
Marshall G (1986) A front tracking method for one-dimensional moving boundary problems. SIAM J Sci Stat Comput 7(1):252–263
Dantzig Jonathan A, Michel R (2016) Solidification: -revised & expanded. EPFL press, Lausanne
Chen S, Merriman B, Osher S, Smereka P (1997) A simple level set method for solving stefan problems. J Comput Phys 135(1):8–29
Fix G (1983) Phase field method for free boundary problems. In: Fasanao, Primicerio M (eds) Free boundary problems. Pit-mann, London
Collins JB, Levine H (1985) Diffuse interface model of diffusion-limited crystal growth. Phys Rev B 31(9):6119
Caginalp G (1986) An analysis of a phase field model of a free boundary. Arch Ration Mech Anal 92(3):205–245
Caginalp G (1989) Stefan and hele-shaw type models as asymptotic limits of the phase-field equations. Phys Rev A 39(11):5887
Kobayashi R (1993) Modeling and numerical simulations of dendritic crystal growth. Phys D 63(3–4):410–423
Karma A, Rappel W-J (1996) Phase-field method for computationally efficient modeling of solidification with arbitrary interface kinetics. Phys Rev E 53(4):R3017
Karma A, Rappel W-J (1999) Phase-field model of dendritic sidebranching with thermal noise. Phys Rev E 60(4):3614
Plapp M, Karma A (2000) Multiscale finite-difference-diffusion-monte-carlo method for simulating dendritic solidification. J Comput Phys 165(2):592–619
Warren JA, Boettinger WJ (1995) Prediction of dendritic growth and microsegregation patterns in a binary alloy using the phase-field method. Acta Metall Mater 43(2):689–703
Loginova I, Amberg G, Ågren J (2001) Phase-field simulations of non-isothermal binary alloy solidification. Acta Mater 49(4):573–581
Karma A (2001) Phase-field formulation for quantitative modeling of alloy solidification. Phys Rev Lett 87(11):115701
Ramirez JC, Beckermann C, Karma A, Diepers H-J (2004) Phase-field modeling of binary alloy solidification with coupled heat and solute diffusion. Phys Rev E 69(5):051607
Echebarria B, Folch R, Karma A, Plapp M (2004) Quantitative phase-field model of alloy solidification. Phys Rev E 70(6):061604
Almgren RF (1999) Second-order phase field asymptotics for unequal conductivities. SIAM J Appl Math 59(6):2086–2107
Ohno M, Matsuura K (2009) Quantitative phase-field modeling for dilute alloy solidification involving diffusion in the solid. Phys Rev E 79(3):031603
Feng X, Prohl A (2004) Analysis of a fully discrete finite element method for the phase field model and approximation of its sharp interface limits. Math Comput 73(246):541–567
Gonzalez-Ferreiro B, Gómez H, Romero I (2014) A thermodynamically consistent numerical method for a phase field model of solidification. Commun Nonlinear Sci Numer Simul 19(7):2309–2323
Chen C, Yang X (2019) Efficient numerical scheme for a dendritic solidification phase field model with melt convection. J Comput Phys 388:41–62
Kessler D, Scheid J-F (2002) A priori error estimates of a finite-element method for an isothermal phase-field model related to the solidification process of a binary alloy. IMA J Numer Anal 22(2):281–305
Xianliang H, Li R, Tang T (2009) A multi-mesh adaptive finite element approximation to phase field models. Commun Comput Phys 5(5):1012–1029
Rosam J, Jimack PK, Mullis A (2007) A fully implicit, fully adaptive time and space discretisation method for phase-field simulation of binary alloy solidification. J Comput Phys 225(2):1271–1287
Damien T, Hong L, Javier LL (2022) Phase-field modeling of microstructure evolution: recent applications, perspectives and challenges. Progress Mater Sci 123:100810
Wang Z, Li J, Wang J, Zhou Y (2012) Phase field modeling the selection mechanism of primary dendritic spacing in directional solidification. Acta Mater 60(5):1957–1964
Fallah V, Amoorezaei M, Provatas N, Corbin SF, Khajepour A (2012) Phase-field simulation of solidification morphology in laser powder deposition of ti-nb alloys. Acta Mater 60(4):1633–1646
Tourret D, Karma A (2015) Growth competition of columnar dendritic grains: a phase-field study. Acta Mater 82:64–83
Takaki T, Ohno M, Shimokawabe T, Aoki T (2014) Two-dimensional phase-field simulations of dendrite competitive growth during the directional solidification of a binary alloy bicrystal. Acta Mater 81:272–283
Geng S, Jiang P, Shao X, Mi G, Han W, Ai Y, Wang C, Han C, Chen R, Liu W et al (2018) Effects of back-diffusion on solidification cracking susceptibility of al-mg alloys during welding: a phase-field study. Acta Mater 160:85–96
Farzadi A, Minh Do-Quang S, Serajzadeh AHK, Amberg G (2008) Phase-field simulation of weld solidification microstructure in an al-cu alloy. Modell Simul Mater Sci Eng 16(6):065005
Wang X, Liu PW, Ji Y, Liu Y, Horstemeyer MH, Chen L (2019) Investigation on microsegregation of in718 alloy during additive manufacturing via integrated phase-field and finite-element modeling. J Mater Eng Perform 28(2):657–665
Rolchigo MR, Mendoza MY, Samimi P, Brice DA, Martin B, Collins PC, LeSar R (2017) Modeling of ti-w solidification microstructures under additive manufacturing conditions. Metall and Mater Trans A 48(7):3606–3622
Ghosh S, Ma L, Ofori-Opoku N, Guyer JE (2017) On the primary spacing and microsegregation of cellular dendrites in laser deposited ni-nb alloys. Modell Simul Mater Sci Eng 25(6):065002
Gong X, Chou K (2015) Phase-field modeling of microstructure evolution in electron beam additive manufacturing. JOM 67(5):1176–1182
Sahoo S, Chou K (2016) Phase-field simulation of microstructure evolution of ti-6al-4v in electron beam additive manufacturing process. Addit Manuf 9:14–24
Keller T, Lindwall G, Ghosh S, Ma L, Lane BM, Zhang F, Kattner UR, Lass EA, Heigel JC, Idell Y et al (2017) Application of finite element, phase-field, and calphad-based methods to additive manufacturing of ni-based superalloys. Acta Mater 139:244–253
Vladimir S, Stefka D, Oleg I (2003) Phase-field method for 2d dendritic growth. In: International conference on large-scale scientific computing. Springer, pp 404–411
Boettinger WJ, Warren JA, Beckermann C, Karma A (2002) Phase-field simulation of solidification. Annu Rev Mater Res 32(1):163–194
Karma A, Rappel W-J (1998) Quantitative phase-field modeling of dendritic growth in two and three dimensions. Phys Rev E 57(4):4323
Hieram NH (2017) Phase-field modeling of solidification and coarsening effects in dendrite morphology evolution and fragmentation. PhD thesis, Technical University of Dresden, Dresden, Technical University of Dresden, Dresden, 8 2017. An optional note
Daniel A, Wolfgang B, Bruno B, Marc F, Rene G, Timo H, Luca H, Uwe K, Martin K, Matthias M, Peter M, Jean-Paul P, Sebastian P, Konrad S, Bruno T, David W, Jiaqi Z (2021) The deal.II library, version 9.3. J Numer Math 29(3):171–186
Calo VM, Collier N, Dalcin L (2013) PetIGA: high-performance isogeometric analysis. arXiv:1305.4452
Wang Z, Rudraraju S, Garikipati K (2016) A three dimensional field formulation, and isogeometric solutions to point and line defects using toupin’s theory of gradient elasticity at finite strains. J Mech Phys Solids 94:336–361
Tonghu J, Shiva R, Roy A, Van der Ven A, Garikipati K, Falk ML (2016) Multiphysics simulations of lithiation-induced stress in \(li_{1+x}ti_2o_4\) electrode particles. J Phys Chem C 120(49):27871–27881
Rudraraju S, Moulton DE, Chirat R, Goriely A, Garikipati K (2019) A computational framework for the morpho-elastic development of molluskan shells by surface and volume growth. PLoS Comput Biol 15(7):e1007213
Bhagat K (2022) Phase-field based dendritic modeling. https://github.com/cmmg/dendriticGrowth
Zhu C, Sheng X, Feng L, Han D, Wang K (2019) Phase-field model simulations of alloy directional solidification and seaweed-like microstructure evolution based on adaptive finite element method. Comput Mater Sci 160:53–61
VisIt: an end-user tool for visualizing and analyzing very large data. https://visit.llnl.gov. Accessed Oct 2012
Gibou F, Fedkiw R, Caflisch R, Osher S (2003) A level set approach for the numerical simulation of dendritic growth. J Sci Comput 19(1):183–199
Bieterman M, Babuška I (1982) The finite element method for parabolic equations. Numer Math 40(3):373–406
Stephen DW, Shiva R, David M, Beck AW, Katsuyo T (2020) Prisms-pf: a general framework for phase-field modeling with a matrix-free finite element method. NPJ Comput Mater 6(1):1–12
Acknowledgements
The authors would like to thank Prof. Dan Thoma (University of Wisconsin-Madison) and Dr. Kaila Bertsch (University of Wisconsin-Madison; now at Lawrence Livermore National Laboratory) for very useful discussions on dendritic growth and microstructure evolution in the context of additive manufacturing of metallic alloys.
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Bhagat, K., Rudraraju, S. Modeling of dendritic solidification and numerical analysis of the phase-field approach to model complex morphologies in alloys. Engineering with Computers 39, 2345–2363 (2023). https://doi.org/10.1007/s00366-022-01767-7
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DOI: https://doi.org/10.1007/s00366-022-01767-7