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Tytuł artykułu

Methodology of integrated modeling of high-temperature steel processing in the aspect of supporting the design of new technologies

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article presents main assumptions of the methodology of integrated modeling of hightemperature steel processing in the aspect of supporting the design of new technologies. The developed solution uses a methodological research capability of modern Gleeble thermomechanical simulators to simulate physical processes, and the benefits of numerical modeling. This allows for restricting the number of expensive experimental tests to the minimum, e.g. by selecting a suitable heating schedule to achieve the desired temperature at the sample section, or getting additional information about the process, eg. estimating the zones with diversified grain growth dynamics, information on local cooling rates at any point within the volume of the sample tested. Mathematical models are original solutions of the developed methodology, such as the thermomechanical model of steel deformation in the semi-solid state, and the multi-scale model of resistance heating coupled with grain growth modelling in the micro scale. The work is supplemented with the main assumptions of the developed mathematical models together with examples of their practical use to support physical simulations.
Rocznik
Strony
361--371
Opis fizyczny
Bibliogr. 23 poz., rys.
Twórcy
autor
  • AGH University of Science and Technology, Faculty of Metals Engineering and Industrial Computer Science, Cracow, Poland;
  • AGH University of Science and Technology, Faculty of Metals Engineering and Industrial Computer Science, Cracow, Poland;
Bibliografia
  • 1. Álvarez Hostos J.C., Bencomo A.D., Puchi Cabrera E.S., Guérin J.-D., Dubar L., 2018,Modeling the viscoplastic flow behavior of a 20MnCr5 steel grade deformed under hot-working conditions, employing a meshless technique, International Journal of Plasticity, 103, 119-142.
  • 2. Bald W., 2000, Innovative technologies for strip production, Steel Times International, 24, 16-19.
  • 3. Barciewicz M., Ryniewicz A., 2018, The application of computed tomography in the automotive world – how industrial CT works, Technical Transactions, 9, 181-188.
  • 4. Hojny M., 2014, Designing Dedicated Simulation Systems of Steel Deformation in the Semi-Solid State (in Polish), Wzorek, Kraków.
  • 5. Hojny M., 2018, Modeling of Steel Deformation in the Semi-Solid State, Springer, Switzerland.
  • 6. Hojny M., Głowacki M., Bała P., Bednarczyk W., Zalecki W., 2019, A multiscale model of heating- remelting-cooling in the Gleeble 3800 thermomechanical simulator system, Archives of Metallurgy and Materials, 64, 1, 401-412.
  • 7. http://www.gleeble.com (access 10.01.2020).
  • 8. http://www.ansys.com (access 30.10.2019).
  • 9. http://www.adina.com (access 30.10.2019).
  • 10. Jiang R., Jáuregui D.V., White K.R., 2008, Close-range photogrammetry applications in bridge measurement: Literature review, Measurement, 41, 823-834.
  • 11. Jin Seol D., Oh K.H., Cho J.W., Lee J.-E., Yoon U.-S., 2002, Phase-field modelling of the thermomechanical properties of carbon steels, Acta Materialia, 50, 2259-2268.
  • 12. Jing Y.L., Sumio S., Jun Y., 2005, Microstructural evolution and flow stress of semi-solid type 304 stainless steel, Journal of Materials Processing Technology, 161, 396-406.
  • 13. Kang C.G., Yoon J.H., 1997, A finite-element analysis on the upsetting process of semi-solid aluminum material, Journal of Materials Processing Technology, 66, 76-84.
  • 14. Koç M., Vazques V., Witulski T., Altan T., 1996, Application of the finite element method to predict material flow and defects in the semi-solid forging of A356 aluminum alloys, Journal of Materials Processing Technology, 59, 106-112.
  • 15. Kopp R., Choi J., Neudenberger D., 2003, Simple compression test and simulation of an Sn-15%Pb alloy in the semi-solid state, Journal of Materials Processing Technology, 135, 317-323.
  • 16. Kumar V., 2016, Thermo-mechanical simulation using Gleeble system – advantages and limitations, Journal of Metallurgy and Materials Science, 58, 1, 81-88.
  • 17. Modigell M., Hufschmidt M., Petera J., 2004, Two-phase simulations as a development tool for thixoforming processes, Steel Research International, 75, 513-518.
  • 18. Modigell M., Pape L., Hufschmidt M., 2004, The rheological behaviour of metallic suspensions, Steel Research International, 75, 506-512.
  • 19. Pieja T., Malinowski T., Hojny M., Trzepieciński T., Nowotyńska I., 2017, Numerical analysis of cooling system in warm metal forming process, Proceedings of 26th International Conference on Metallurgy and Materials, 261-266.
  • 20. Rai M., Maity T., Yadav R.K., 2017, Thermal imaging system and its real time applications: a survey, Journal of Engineering Technology, 6, 2, 290-303.
  • 21. Shimahara H., Baadjou R., Kopp R., Hirt G., 2006, Investigation of flow behaviour and microstructure on X210CrW12 steel in semi-solid state, Splid State Phenomena, 116, 189-192.
  • 22. Sommerville I., 2011, Software Engineering, Addison-Wesley, Boston.
  • 23. Watari H., Davey K., Rasgado M.T., 2004, Semi-solid manufacturing process of magnesium alloys by twin-roll casting, Journal of Materials Processing Technology, 156, 1662-1667.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-01298e23-b10f-404c-b30c-1d2a5bea71f0
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