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Abstrakty
With the aim of developing dual phase (DP) microstructure using a continuous annealing process, four steels with different chemical compositions were investigated in the axisymmetrical plastometric tests and during the cold rolling process. The rheological model for these steels was developed using the results of the plastometric tests and application of the inverse analysis. Load–displacement curves were used to identify parameters of the rheological model, which was incorporated into the finite element code for rolling. First, the model was validated with experiments realized on the laboratory cold rolling mill. Calculated loads were compared with experimental data and good agreement was obtained. Beyond this, metallographic analysis was performed and deformation of the ferritic–pearlitic microstructure during rolling was investigated. Finally, the generated results were combined in the form of the multi-scale numerical model based on the digital material representation approach capable of investigating local microstructural inhomogeneities.
Czasopismo
Rocznik
Tom
Strony
885--896
Opis fizyczny
Bibliogr. 21 poz., rys., tab., wykr.
Twórcy
autor
- AGH University of Science and Technology, Kraków, Poland
autor
- Institute for Ferrous Metallurgy, Gliwice, Poland
autor
- AGH University of Science and Technology, Kraków, Poland
autor
- AGH University of Science and Technology, Kraków, Poland
autor
- AGH University of Science and Technology, Kraków, Poland
autor
- AGH University of Science and Technology, Kraków, Poland
Bibliografia
- [1] H. Hofmann, D. Mattissen, T.W. Schaumann, Advanced cold rolled steels for automotive applications, Steel Research International 80 (2009) 22–28.
- [2] D.K. Matlock, J.G. Speer, Third Generation of AHSS: Microstructure Design Concepts, Springer, 2009185–205.
- [3] H. Beladi, Y. Adachi, I. Timokhina, P.D. Hodgson, Crystallographic analysis of nanobainitic steels, Scripta Materialia 60 (2009) 455–458.
- [4] S. Krajewski, J. Nowacki, Dual-phase steels microstructure and properties consideration based on artificial intelligence techniques, Archives of Civil and Mechanical Engineering 14 (2014) 278–286.
- [5] I. Sabirov, Y. Estrin, M.R. Barnett, I. Timokhina, P.D. Hodgson, Tensile deformation of an ultrafine-grained aluminium alloy: micro shear banding and grain boundary sliding, Acta Materialia 56 (2008) 2223–2230.
- [6] K. Muszka, P.D. Hodgson, J. Majta, A physical based modeling approach for the dynamic behavior of ultrafine grained structures, Journal of Materials Processing Technology 177 (2006) 456–460.
- [7] A. Bayram, A. Uguz, M. Ula, Effects of microstructure and notches on the mechanical properties of dual-phase steels, Materials Characterization 43 (1999) 259–269.
- [8] D. Szeliga, J. Gawąd, 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.
- [9] 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 76 (2005) 131–137.
- [10] D. Szeliga, M. Pietrzyk, Identification of rheological models and boundary conditions in metal forming, International Journal of Materials & Product Technology 39 (2010) 388–405.
- [11] S. Kobayashi, S.I. Oh, T. Altan, Metal Forming and the Finite Element Method, Oxford University Press, New York, Oxford, 1989.
- [12] J.G. Lenard, M. Pietrzyk, L. Cser, Mathematical and Physical Simulation of the Properties of Hot Rolled Products, Elsevier, Amsterdam, 1999.
- [13] M. Bernacki, H. Resk, T. Coupez, R.E. Loge, 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.
- [14] L. Madej, L. Sieradzki, M. Sitko, K. Perzynski, K. Radwański, R. Kuziak, Multi scale cellular automata and finite element based model for cold deformation and annealing of a ferritic– pearlitic microstructure, Computational Materials Science 77 (2013) 172–181.
- [15] P.R. Dawson, M.P. Miller, The Digital Material – An Environment for Collaborative Material Design, 2009 Project poster available at: http://anisotropy.mae.cornell.edu (last accessed: 18 December).
- [16] 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.
- [17] 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.
- [18] A.D. Rollett, 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.), Proc. Conf. Numiform, Columbus, (2004), pp. 71–77.
- [19] K. Perzyński, 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.
- [20] L. Madej, F. Kruzel, P. Cybulka, K. Perzynski, K. Banas, Generation of dedicated finite element meshes for multiscale applications with Delaunay triangulation and adaptive finite element – cellular automata algorithms, Computer Methods in Materials Science 12 (2012) 85–96.
- [21] W. Wajda, L. Madej, H. Paul, Application of crystal plasticity model for simulation of polycrystalline aluminum sample behavior during plain strain compression test, Archives of Metallurgy and Materials 58 (2013) 493–496.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4b4374d6-13a8-47ec-8665-180c19284e11