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Digital/virtual microstructures in application to metals engineering – A review

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EN
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EN
Recent progress in application of digital/virtual microstructure models in the area of metals engineering science is presented within the paper. First, various approaches to digital reconstruction of microstructure morphology of investigated materials is presented. Possibilities of generation of both: exact replicas of morphology, as well as, synthetic microstructures are discussed. Advantages and limitations in the case of two and three-dimensional problems are highlighted in that section. Then, the state of the art in the evaluation of material properties at the microstructure scale is addressed. Various experimental techniques, characterized by different levels of complexity, which are capable of providing information on materials hardening behavior at the micro scale level are presented. Finally, possibilities of introduction of microstructure morphology with specific properties into the finite element solution are described. The work is complemented by series of practical applications of the digital/virtual microstructure models to show their capabilities and present directions for further development.
Rocznik
Strony
839--854
Opis fizyczny
Bibliogr. 95 poz., rys., wykr.
Twórcy
autor
  • AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland
Bibliografia
  • [1] M. Pietrzyk, L. Madej, L. Rauch, D. Szeliga, Computational Materials Engineering: Achieving High Accuracy and Efficiency in Metals Processing Simulations, Butterworth- Heinemann Elsevier, 2015.
  • [2] J. Gawad, R. Kuziak, L. Madej, D. Szeliga, M. Pietrzyk, Identification of rheological parameters on the basis of various types of compression and tension tests, Steel Research International 2/3 (2005) 131–137.
  • [3] D. Szeliga, J. Gawad, M. Pietrzyk, Inverse analysis for identification of rheological and friction models in metal forming, Computer Methods in Applied Mechanics and Engineering 195 (2006) 6778–6798.
  • [4] G. Lacroix, Q. Furnemont, P.J. Jacques, T. Pardoen, Mechanisms of damage and fracture in TRIP assisted multiphase steels, Fracture of Nano and Engineering Materials and Structures (2006) 819–820.
  • [5] Y. Estrin, A. Vinogradov, Extreme grain refinement by severe plastic deformation: a wealth of challenging science, Acta Materialia 61 (2013) 782–817.
  • [6] E. Pereloma, H. Beladi, L. Zhang, I. Timokhina, Understanding the behavior of advanced high-strength steels using atom probe tomography, Metallurgical and Materials Transactions A 43A (2012) 3958–3971.
  • [7] K. Muszka, M. Lopez-Pedrosa, K. Raszka, M. Thomas, W.M. Rainforth, B.P. Wynne, The impact of strain reversal on microstructure evolution and orientation relationships in Ti- 6Al-4V with an initial alpha colony microstructure, Metallurgical and Materials Transactions A 45 (2014) 5997– 6007.
  • [8] F. Vollertsen, Z. Hu, H. Schulze Niehoff, C. Theiler, State of the art in micro forming and investigations into micro deep drawing, Journal of Materials Processing Technology 151 (2004) 70–79.
  • [9] E. Egerer, U. Engel, Process characterization and material flow in microforming at elevated temperatures, Journal of Manufacturing Processes 6 (2004) 1–6.
  • [10] H.E. Deve, R.J. Asaro, The development of plastic failure modes in crystalline materials: shear bands in FCC polycrystals, Metallurgical Transactions A 20A (1989) 579–593.
  • [11] A. Asgari, P.D. Hodgson, V. Lemiale, C. Yang, B. Rolfe, Multiscale particle-in-cell modelling for advanced high strength steels, Advanced Materials Research 32 (2008) 285–288.
  • [12] S. Ayyar, N. Chawla, Microstructure-based modeling of crack growth in particle reinforced composites, Composites Science and Technology 66 (2006) 1980–1994.
  • [13] F. Ballani, D.J. Daley, D. Stoyan, Modelling the microstructure of concrete with spherical grains, Computational Material Science 35 (2006) 339–407.
  • [14] M. Bernacki, Y. Chastel, H. Digonnet, H. Resk, T. Coupez, R.E. Logé, Development of numerical tools for the multiscale modelling of recrystallisation in metals, based on a digital material framework, Computer Methods in Material Science 7 (2007) 142–149.
  • [15] M. Bernacki, H. Resk, T. Coupez, R.E. Logé, Finite element model of primary recrystallization in polycrystalline aggregates using a level set framework, Modelling and Simulation in Materials Science and Engineering 17 (2009) 064006.
  • [16] A. Brahme, M.H. Alvi, D. Saylor, J. Frify, A.D. Rollet, 3D reconstruction of microstructure in a commercial purity aluminium, Scripta Materialia 55 (2006) 75–80.
  • [17] M.A. Groeber, M.D. Uchic, D.M. Dimiduk, Y. Bhandari, S. Ghosh, A framework for automated 3D microstructure analysis & representation, Journal of Computer-Aided Material Design 14 (2008) 63–74.
  • [18] L. Delannay, P.J. Jacques, S.R. Kalidini, Finte element modeling of crystal plasticity with grains shaped as trunced octahedrons, International Journal of Plasticity 22 (2006) 1879–1898.
  • [19] J.H. Beynon, S. Das, I.C. Howard, E.J. Palmier, A. Shterenlikht, The combination of cellular automata and finite elements for the study of fracture; the CAFE model of fracture, in: A. Neimitz, I.V. Rokach, D. Kocańda, K. Gołoś, Kraków (Eds.), Proc. Conf., ECF14, 2000, 241–248.
  • [20] P. Blikstein, A.P. Tschiptschin, Monte Carlo simulation of grain growth, Materials Research 2 (1999) 133–137.
  • [21] C.H.J. Davies, Growth of nuclei in a cellular automaton simulation of recrystalization, Scripta Materialia 36 (1997) 35–40.
  • [22] D. Raabe, R.C. Becker, Coupling of a crystal plasticity finite- element model with a probabilistic cellular automaton for simulating primary static recrystallization in aluminium, Modelling and Simulation in Materials Science and Engineering 8 (2000) 445–462.
  • [23] D. Raabe, R.C. Becker, Recrystallization Simulation by Coupling of a Crystal Plasticity FEM with a Cellular Automaton Method, Technical Report, Max-Planck Institute, 2007.
  • [24] Q. Yu, S.K. Esche, A multi-scale approach for microstructure prediction in thermo-mechanical processing of metals, Journal of Materials Processing Technology 169 (2005) 493–502.
  • [25] A.C. Lewis, A.B. Geltmacher, Image-based modeling of the response of experimental 3D microstructures to mechanical loading, Scripta Materialia 55 (2006) 81–85.
  • [26] W. Li, N. Zabaras, A virtual environment or the interrogation of 3D polycrystalline microstructures including grain size effect, Computational Material Science 44 (2009) 1163–1177.
  • [27] R. Tadeusiewicz, P. Korochoda, Komputerowa analiza i przetwarzanie obrazów, Wydawnictwo Fundacji Postępu Telekomunikacji, Kraków, 1997.
  • [28] L. Rauch, L. Madej, J. Kusiak, Modelling of microstructure deformation based on the Digital Material Representation integrated with the watershed image segmentation algorithm, Steel Research International 81 (2010) 1446–1449.
  • [29] L. Rauch, L. Madej, Deformation of the dual phase material on the basis of digital representation of microstructure, Steel Research International 79 (2008) 579–586.
  • [30] K. Perzynski, L. Madej, J. Wang, R. Kuziak, P.D. Hodgson, Numerical investigation of influence of the martensite volume fraction on DP steels fracture behavior on the basis of digital material representation model, Metallurgical and Materials Transactions A 45 (2014) 5852–5865.
  • [31] T.J. Turner, P.A. Shade, J.V. Bernier, S. Li, J.C. Schuren, J. Lind, U. Lienert, P. Kenesei, R.M. Suter, B. Blank, J. Almer, Combined near- and far-field high-energy diffraction microscopy dataset for Ti-7Al tensile specimen elastically loaded in situ, Integrating Materials and Manufacturing Innovation (2016), http://dx.doi.org/10.1186/s40192-016-0048-1.
  • [32] E.Y. Guo, N. Chawla, T. Jing, S. Torquato, Y. Jiao, Accurate modeling and reconstruction of three-dimensional percolating filamentary microstructures from two-dimensional micrographs via dilation-erosion method, Materials Characterization 89 (2014) 33–42.
  • [33] J.E. Spowart, H.E. Mullens, B.T. Puchala, Collecting and analyzing microstructures in three dimensions: a fully automated approach, JOM (2010) 35–37. http://www. springerlink.com/content/1047-4838/55/10/.
  • [34] J.E. Spowart, Automated serial sectioning for 3-D analysis of microstructures, Scripta Materialia 55 (2006) 5–10.
  • [35] J. Alkemper, P.W. Voorhees, Quantitative serial sectioning analysis, Journal of Microscopy 201 (2001) 388–394.
  • [36] M. Echlin, A. Mottura, T. Pollock, The Tri-Beam system: femtosecond laser based tomography in a dual-beam FIB, in: Proc. Conf. Microscopy and Microanalysis, Nashville, Tennessee, USA, 2011.
  • [37] M. Gorantla, RoboMet.3D: a fully automated, serial sectioning system for 3D microstructural investigations, in: Proc. Conf. 2013 TMS Annual Meeting & Exhibition, San Antonio, TX, 2013.
  • [38] W. Xu, M. Ferry, N. Mateescu, J.M. Cairney, F.J. Humphreys, Techniques for generating 3-D EBSD microstructures by FIB tomography, Materials Characterization 58 (2007) 961–967.
  • [39] S. Zaefferer, S.I. Wright, Three-dimensional orientation microscopy by serial sectioning and EBSD-based orientation mapping in a FIB-SEM, in: A.J. Schwartz, M. Kumar, B.L. Adams, D.P. Field (Eds.), Electron Backscatter Diffraction in Materials Science, 2nd ed., Springer, 2009 109–122 (Chapter 8).
  • [40] S. Zaefferer, S.I. Wright, D. Raabe, Three-dimensional orientation microscopy in a focused ion beam–scanning electron microscope: a new dimension of microstructure characterization, Metallurgical and Materials Transactions A 39 (2008) 374–389.
  • [41] G. Spanos, D.J. Rowenhorst, A.C. Lewis, A.B. Geltmacher, Combining serial sectioning, EBSD analysis, and image-based finite element modeling, MRS Bulletin (2008) 597–602.
  • [42] P. Bobrowski, M. Faryna, K. Głowiński, Evaluation of grain boundary plane distribution in yttria stabilized polycrystalline zirconia based on 3D EBSD analysis, Materials Characterization 122 (2016) 137–141.
  • [43] J. Guyon, N. Gey, D. Goran, S. Chalal, F. Pérez-Willard, Advancing FIB assisted 3D EBSD using a static sample setup, Ultramicroscopy 161 (2016) 161–167.
  • [44] X. Zhonga, D.J. Rowenhorst, H. Beladi, G.S. Rohrer, The five-parameter grain boundary curvature distribution in an austenitic and ferritic steel, Acta Materialia 123 (2017) 136– 145.
  • [45] M. Doroszko, A. Seweryn, Numerical modeling of the tensile deformation process of sintered 316L based on microtomography of porous mesostructures, Materials & Design 88 (2015) 493–504.
  • [46] P. Bala, K. Tsyrulin, H. Jaksch, M. Stepien, 3D reconstruction and characterization of carbides in Ni-based high carbon alloy in a FIB-SEM system, International Journal of Materials Research 106 (2015) 764–770.
  • [47] T. Hara, Recent improvement of a FIB-SEM serial-sectioning method for precise 3D image reconstruction – application of the orthogonally-arranged FIB-SEM, Microscopy (Oxf) 63 (2014) 5.
  • [48] S.R. Claves, Evolution of AlFeSi intermetallic interfaces in 6063 aluminum alloys as a function of heat treatment, (PHD dissertation), Lehigh University, Bethlehem, PA, 2005.
  • [49] L. Madej, M. Mojzeszko, J. Chraponski, S. Roskosz, J. Cwajna, Digital material representation model of porous microstructure based on 3D reconstruction algorithm, Archives of Metalurgy and Materials (2016) (in press).
  • [50] M. De Berg, M. Van Kreveld, M. Overmars, O. Schwarzkopf, Computational Geometry Algorithms and Applications, Springer-Verlag, 2000.
  • [51] F. Aurenhammer, Voronoi diagrams – a survey of a fundamental geometric data structures, ACM Computing Surveys 23 (1991) 245–405.
  • [52] L. Madej, L. Rauch, K. Perzyński, P. Cybułka, Digital material representation as an efficient tool for strain inhomogeneities analysis at the micro scale level, Archives of Civil and Mechanical Engineering 11 (2011) 661–679.
  • [53] Z. Fan, Y. Wu, X. Zhao, Y. Lu, Simulation of polycrystalline structure with Voronoi diagram in Laguerre geometry based on random closed packing of spheres, Computational Materials Science 29 (2004) 301–308.
  • [54] P. Zhang, D. Balint, L. Jianguo, Controlled Poisson–Voronoi tessellation for virtual grain structure generation: a statistical evaluation, Philosophical Magazine 91 (2011) 4555–4573.
  • [55] C. Lautensack, T. Sych, 3D analysis of open foams using random tesselations, Image Analysis and Stereology 25 (2006) 87–93.
  • [56] L. Madej, M. Sitko, K. Radwanski, R. Kuziak, Validation and predictions of coupled finite element and cellular automata model: influence of the degree of deformation on static recrystallization kinetics case study, Materials Chemistry and Physics 179 (2016) 282–294.
  • [57] L. Madej, M. Sitko, M. Pietrzyk, Perceptive comparison of mean and full field dynamic recrystallization models, Archives of Civil and Mechanical Engineering 16 (2016) 569– 589.
  • [58] E.A. Holm, C.C. Battaile, The computer simulation of microstructural evolution, JOM 53 (2001) 20–23.
  • [59] A.D. Rollett, P. Manohar, The Monte Carlo method, in: D. Raabe, F. Roters, F. Barlat, L.-Q. Chen (Eds.), Continuum Scale Simulation of Engineering Materials: Fundamentals – Microstructures – Process Applications, Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, FRG, 2005.
  • [60] S. Plimpton, C. Battaile, M. Chandross, L. Holm, A. Thompson, V. Tikare, G. Wagner, E. Webb, X. Zhou, C. Garcia Cardona, A. Slepoy, Crossing the Mesoscale No-Man's Land via Parallel Kinetic Monte Carlo, Sandia Report SAND2009-6226, 2009.
  • [61] Y. Liu, L. Cheng, Q. Zeng, Z. Feng, L. Zhang, PCLab – a software with interactive graphical user interface for Monte Carlo and finite element analysis of microstructure-based layered composites, Advances in Engineering Software 90 (2015) 53–62.
  • [62] L. Madej, M. Sitko, Parallelization of the Monte Carlo static recrystallization model, Lecture Notes in Computer Science 8500 (2014) 445–458.
  • [63] A. Asgari, C.H. Yang, P.D. Hodgson, B.F. Rolfe, Modeling of advanced high strength steels with the realistic microstructure–strength relationships, Computational Materials Science 45 (2009) 860–866.
  • [64] T. Wejrzanowski, J. Skibiński, L. Madej, K.J. Kurzydłowski, Modeling structures of cellular materials for application at various length-scales, Computer Methods in Materials Science 13 (2013) 493–500.
  • [65] C.F. Cornwell, R.W. Noack, E.J. Abed, Three-Dimensional Digital Microstructures, Project Report Documentation, High Performance Technologies, Inc., Aberdeen Proving Ground, MD, 2006. p. 21005.
  • [66] A.D. Rollet, D. Saylor, J. Frid, B.S. El-Dasher, A. Barhme, S.B. Lee, C. Cornwell, R. Noack, Modelling polycrystalline microstructures in 3D, in: S. Ghosh, J.C. Castro, J.K. Lee (Eds.), Conf. Proc. Numiform 2004, Columbus, Ohio, (2004) 71– 77.
  • [67] D.M. Saylor, J. Fridy, S. El-Dasher, J. Kee-Youing, A.D. Rollet, Statistically representative three-dimensional microstructures based on orthogonal observation sections, Metallurgical Transaction and Materials Transaction A 35A (2004) 1969–1979.
  • [68] M.A. Groeber, M.A. Jackson, DREAM.3D: a digital representation environment for the analysis of microstructure in 3D, Integrating Materials and Manufacturing Innovation 3 (5) (2014) 1–17.
  • [69] R.E. Logé, M. Bernacki, H. Resk, L. Delannay, H. Digonnet, Y. Chastel, T. Coupez, Linking plastic deformation to recrystallization in metals, using digital microstructures, Philosophical Magazine 88 (2008) 3691–3712.
  • [70] B. Scholtes, M. Shakoor, A. Settefrati, P.O. Bouchard, N. Bozzolo, M. Bernacki, New finite element developments for the full field modeling of microstructural evolutions using the level-set method, Computational Materials Science 109 (2015) 388–398.
  • [71] P.R. Dawson, Computational crystal plasticity, International Journal of Solids and Structures 37 (2000) 115–130.
  • [72] J. Cao, J. Lin, Development of a VGRAIN system for CPFE analysis in micro-forming applications, International Journal of Advanced Manufacturing Technology 47 (2010) 981–991.
  • [73] L. Madej, J. Szyndler, K. Pasternak, M. Przenzak, L. Rauch, Tools for generation of digital material representations, in: Mat. Konf. MS&T, Columbus, Ohio, CD, 2011.
  • [74] D. Ilin, M. Bernacki, Advancing layer algorithm of dense ellipse packing for generating statistically equivalent polygonal structures, Granular Matter 18 (2016) 1–15.
  • [75] C. Uhler, S.J. Wright, Packing ellipsoids with overlap, SIAM Review 55 (2013) 671–706.
  • [76] H. Altendor, F. Latourte, D. Jeulin, M. Faessel, L. Saintoyant, 3D reconstruction of a multiscale microstructure by anisotropic tessellation models, Image Analysis & Stereology 33 (2014) 121–130.
  • [77] M.A. Tschopp, 3-D Synthetic microstructure generation with ellipsoid particles, Technical Note, US Army Research Laboratory, 2016.
  • [78] L. Madej, K. Pasternak, J. Szyndler, W. Wajda, Development of the modified cellular automata sphere growth model for creation of the digital material representations, Key Engineering Materials 611–612 (2014) 489–496.
  • [79] W. Wajda, L. Madej, H. Paul, R. Gołąb, M. Miszczyk, Validation of texture evolution model for polycrystalline aluminum on the basis of 3D Digital Microstructures, Steel Research International Special Edition, 2012, pp. 1111–1114.
  • [80] Z. Zhang, T.-S. Jun, T.B. Britton, F.P.E. Dunne, Determination of Ti-6242 a and b slip properties using micro-pillar test and computational crystal plasticity, Journal of the Mechanics and Physics of Solids 95 (2016) 393–410.
  • [81] X. Hernot, C. Moussa, O. Bartier, Study of the concept of representative strain and conastraint factor introduced by Vickers indentation, Mechanics of Materials 68 (2014) 1–14.
  • [82] J. Wang, C. Yang, P.D. Hodgson, Extrinsic size effect in microcompression of polycrystalline Cu/Fe multilayers, Scripta Materialia 69 (2013) 626–629.
  • [83] H. Ghassemi-Armaki, R. Maaß, S.P. Bhat, S. Sriram, J.R. Greer, K.S. Kumar, Deformation response of ferrite and martensite in a dual-phase steel, Acta Materialia 62 (2014) 197–211.
  • [84] L. Madej, J. Wang, K. Perzynski, P.D. Hodgson, Numerical modelling of dual phase microstructure behavior under deformation conditions on the basis of digital material representation, Computational Material Science 95 (2014) 651–662.
  • [85] D. Raabe, D. Ma, F. Roters, Effects of initial orientation, sample geometry and friction on anisotropy and crystallographic orientation changes in single crystal microcompression deformation: a crystal plasticity finite element, Acta Materialia 55 (2007) 4567–4583.
  • [86] Q. Liu, A. Roy, V.V. Silberschmidt, Size-dependent crystal plasticity: from micro-pillar compression to bending, Mechanics of Materials 100 (2016) 31–40.
  • [87] F. Kruzel, L. Madej, K. Perzynski, K. Banas, Development of 3D adaptive mesh generation for multi scale applications, International Journal for Multiscale Computational Engineering 12 (2014) 257–269.
  • [88] S. Dancette, A. Browet, G. Martin, M. Willemet, L. Delannay, Automatic processing of an orientation map into a finite element mesh that conforms to grain boundaries, Modelling and Simulation in Materials Science and Engineering 24 (2016), 055014 1–14.
  • [89] E.I. Barker, K.S. Choi, X. Sun, E. Deda, J. Allison, M. Li, J. Forsmark, J. Zinde, L. Godlewskic, Microstructure based modeling of b phase influence on mechanical response of cast AM series Mg alloys, Computational Materials Science 92 (2014) 353–361.
  • [90] J. Szyndler, L. Madej, Numerical analysis of the influence of number of grains, FE mesh density and friction coefficient on representativeness aspects of the polycrystalline Digital Material Representation – plane strain deformation case study, Computational Material Science 96 (2015) 200–213.
  • [91] M. Rosiak, The results of consolidation of sinters being deformed under complex loading condition, Archives of Metallurgy and Materials 58 (2013) 1197–1206.
  • [92] J. Majta, K. Perzynski, K. Muszka, P. Graca, L. Madej, Modeling of grain refinement and mechanical response of microalloyed steel wires severely deformed by combined forming process, International Journal of Advanced Manufacturing Technology 89 (2017) 1159–1574.
  • [93] J. Majta, L. Madej, D. Svyetlichnyy, K. Muszka, K. Perzynski, M. Kwiecień, Modeling of the inhomogeneity of grain refinement during combined metal forming process by finite element and cellular automata methods, Materials Science & Engineering A 671 (2016) 204–213.
  • [94] K. Perzynski, L. Madej, Fracture modelling in dual phase steel grades based on the discrete/continuum random cellular automata finite element RCAFE approach, Simulation 92 (2016) 195–207.
  • [95] K. Perzyński, A. Wrożyna, R. Kuziak, A. Legwand, L. Madej, Development and validation of multi scale failure model for dual phase steels, Finite Elements in Analysis and Design 124 (2017) 7–21.
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