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Tytuł artykułu

Strategy for the selection of the best phase transformation model for simulation of metals processing

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Warianty tytułu
PL
Strategia wyboru najlepszego modelu przemian fazowych w symulacjach przetwórstwa metali
Języki publikacji
EN
Abstrakty
EN
Connection of the finite element program with phase transformation models is often needed when prediction of distribution of phase composition in the product is of interest. Depending on the type of the phase transformation model this connection may involve long computing times. Moreover, when the optimization task has to be formulated and solved, the computing costs may radically increase. It is particularly troublesome when the objective function is composed of advanced microstructural parameters or product properties, evaluation of which requires an application of multiscale modelling techniques. In the present paper the possibilities of decreasing of the computing costs for optimization of metals processing were explored. Several case studies, which require connection of the FE code with phase transformation models, were analysed and computing times were compared. Efficiency of modelling depending on the complexity of the macro scale FE mesh was evaluated.
PL
Połączenie programu z metody elementów skończonych (MES) z modelem przemian fazowych jest niezbędne, kiedy potrzebna jest informacja o rozkładzie składu fazowego w wyrobie gotowym. W zależności od rodzaju modelu przemian fazowych takie połączenie może pociągać za sobą bardzo długie czasy obliczeń. Ponadto, kiedy dodatkowo musi zostać sformułowane i rozwiązane zadanie optymalizacyjne, koszty obliczeń mogą jeszcze radykalnie wzrosnąć. Jest to szczególnie kłopotliwe, kiedy funkcja celu zawiera zaawansowane parametry mikrostruktury lub własności wyrobu, których obliczenie wymaga zastosowania modelowania wieloskalowego. W niniejszej pracy analizowano możliwości skrócenia czasów obliczeń związanych z optymalizacją procesów przetwórstwa metali. Porównano czasy obliczeń dla symulacji różnych procesów, w których potrzebne jest połączenie MES z modelami przemian fazowych. Oceniono efektywność modelowania w zależności od złożoności siatki MES w skali makro.
Wydawca
Rocznik
Strony
224--237
Opis fizyczny
Bibliogr. 35 poz., rys.
Twórcy
autor
  • AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków
autor
  • AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków
  • AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków
autor
  • AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków
autor
  • AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków
autor
  • AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków
Bibliografia
  • Aboauf, M, Chenot, J.-L., Marcelin, J.-L., 1983, A two- dimensional finile-element idealization for thermoelastic deflection in beams. International Journal for Numerical Methods in Engineering, 19, 1453-1465.
  • Bachniak, D., Rauch, L., Król, I)., Słota, R., Kitowski, J., Pietrzyk, M„ 2016, Massively parallel approach to sensitivity analysis on HPC architectures with Scalarm platform, Concurrency and Computation: Practice and Experience, Published online in Wiley Online Library (wileyonlinelibrary.com). 1)01: 10.1002/cpe.4025.
  • Behrens, B.-A., Denkena, B., Charlin, F., Dannenberg, M., 2011, Model based optimization of forging process chains by the use of a Genetic Algorithm, 10th Int. Conf. on Technology of Plasticity ICTP, eds, Hirt, G., Tekkaya, A.E., Aachen, 25.-30.
  • Haider, C., Madej, L., Pietrzyk, M., 2014, Discrete micro-scale cellular automata model for modelling phase transformation during heating of dual phase steels. Archives of Civil and Mechanical Engineering, 14, 96-103. 361.
  • Gołąb, R., Madej, Ł., Pietrzyk, M„ 2014, The complex computer system based on Cellular Automata method designed to support modelling of laminar cooling processes, Journal of Machine Engineering, 14, 63-73.
  • Król, D., Słota, R., Kitowski, J„ Rauch, L., Bzowski, K., Pietrzyk, M„ 2016, Model-based approach to study hot rolling mills with data farming, Proceedings of 30th European Conference on Modelling and Simulation, 2016, CD-ROM.
  • Kuziak, R., Pietrzyk, M., 2011, Physical and numerical simulation of the manufacturing chain for the DP steel strips. Steel Research International, special edition conf. ICTP, Aachen, 756-761.
  • Kuziak, R., Zygmunt, T„ 2013, A new method of rail head hardening of standard gauge rails for improved wear and damage resistance, Steel Research International, 84, 13-19.
  • Leblond, J.B., Devaux, .1., 1984, A new kinetic model for anisothermal metallurgical transformations in steel including effect of austenite grain size, Acta Metallurgica, 32, 137- 146.
  • Lee, C.H., Kobayashi, S., 1973, New solution to rigid plastic deformation problems, ASME, Journal of Engineering for Industry, 95, 865-873.
  • Lenard, J.G., Pietrzyk, M„ Cser, L., 1999, Mathematical and physical simulation of the properties of hot rolled products, Elsevier, Amsterdam.
  • Milenin, A., Pietrzyk, M., Kuziak, R., 2013, Mathematical model of residual stresses in hot-rolled strips for laser cutting. Proc. Conf ROLLING 2013, Venice, CD ROM.
  • Milenin, A., Rec, T„ Walczyk, W., Pietrzyk, M., 2016a, Model of curvature of crankshaft blank during heat treatment, ac-counting for phase transformations, Steel Research Inter¬national, 86, 519-528.
  • Milenin, A., Kuziak, R., Lech-Grega, M., Chochorowski, A., Witek, S., Pietrzyk, M„ 2016b, Numerical modeling and experimental identification of residual stresses in hot- rolled strips, Archives of Civil and Mechanical Engineering, 16, 125-134.
  • Milenin, I., Pernach, M., Pietrzyk, M„ 2015, Application of the control theory for modelling austenite-ferrite phase trans-formation in steels. Computer Methods in Materials Sci¬ence, 15,327-335.
  • Pereira, 11.A., Cupertino, A.F., Teodorescu, R., Silva, R.S., 2014, 11igh performance reduced order models for wind turbines with full-scale converters applied on grid interconnection studies. Energies, 7, 7694-7716.
  • Pernach, M., Pietrzyk, M„ 2008, Numerical solution of the diffusion equation with moving boundary applied to modeling of the austenite-ferrite phase transformation, Computational Materials Science, 44, 783-791.
  • Pernach, M., Bzowski, K„ Pietrzyk, M., 2014, Numerical modelling of phase transformation in DP steel after hot rolling and laminar cooling, International Journal for Multiscale Computational Engineering, 12, 397-410.
  • Pernach, M., 2014, Application of the diffusion equation to modeling phase transformation during cooling of pearlitic steel. Computer Methods in Materials Science, 14, 228- 238.
  • Perzyński, K„ Madej, L„ Szajding, A., Raga, K., Kubiak, K., Niechajowicz, A., Jaskiewicz, K., Gronostajski, Z.., Pietrzyk, M., 2016, Numerical model of heat treatment of gear rings used in airplanes, Journal of Machine Engineering, 18-26.
  • Pietrzyk, M., 2000, Finite element simulation of large plastic deformation, Journal of Materials Processing Technology, 106,223-229.
  • Pietrzyk, M., Madej, L., Węglarczyk, S., 2008, Tool for optimal design of manufacturing chain based on metal forming. Annals of the CIRP, 57, 309-312.
  • Pietrzyk, M., Kuziak, R., 2012, Modelling phase transformations in steel. Microstructure evolution in metal forming processes, eds, Lin, J., Balint, D., Pietrzyk, M„ Woodhead Publishing, Oxford, 145-179.
  • Pietrzyk, M., Kusiak, J., Kuziak, R., Madej, L., Szeliga, D„ Golab, R., 2014, Conventional and multiscale modelling of microstructure evolution during laminar cooling of DP Steel strips, Metallurgical and Materials Transactions B, 46B, 497-506.
  • Pietrzyk, M., Madej, L., Rauch, L., Szeliga, D., 2015, Computational Materials Engineering: Achieving high accuracy and efficiency in metals processing simulations, Elsevier, Amsterdam.
  • Pietrzyk, M., Kusiak, J., Szeliga, D., Rauch, L., Sztangret, L., Górecki, G., 2016, Application of Metamodels to Identifi¬cation of Metallic Materials Models, Advances in Materials Science and Engineering, DOI: doi: 10.1155/2016/2357534.
  • Quarteroni, A., Rozza, G., (eds), 2014, Reduced order methods for modeling and computational reduction, Springer.
  • Rauch, L„ Kuziak, R„ Pietrzyk, M„ 2014, From high accuracy to high efficiency in simulations of processing of Dual-Phase steels. Metallurgical and Materials Transactions B, 45B, 497-506.
  • Schroeder, J., Balzani, D., Brands, D., 2011, Approximation of random microstructures by periodic statistically similar representative volume elements based on lineal-path func¬tions, Archives of Applied Mechanics, 81, 975-997.
  • Sellars, C. M., 1980, The Physical Metallurgy of Hot Working,I lot Working and Forming Processes, Hot Working and Forming Processes, (eds), Sellars, C.M., Davies, G.J., The Metals Soc., London, 3-15.
  • Skora, M., Pietrzyk, M., 2014, Proper assembly and geometrical parameters as a criterion for the computer aided design of manufacturing cyclc for screws. Computer Methods in Materials Science, 14, 75-85.
  • Szeliga, D., Kuziak, R., Kopp, R., Smyk, G., Pietrzyk, M„ 2015, Accounting for the inhomogeneity of deformation in identification of microstructure evolution model, Archives of Metallurgy and Materials, 60, 3087-3094.
  • Sztangret, L., Milenin, A., Sztangret, M„ Walczyk, W., Pictrzyk, M., Kusiak, J., 2011, Computer aided design of the best TR forging technology for crank shafts, Computer Meth¬ods in Materials Science, 11, 237-242.
  • Wang, X., Yang, Q., He, A., 2008, Calculation of thermal stress affecting strip flatness change during run-out table cooling in hot steel strip rolling, Journal of Materials Processing Technology, 207, 130-146.
  • Zienkiewicz, O.C., Taylor, R.L., Zhu, J.Z., 2005, The finite ele¬ment method: its basis and fundamentals, Elsevier Bulterworth-Heinemann.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2bcc2d4f-16ff-4ac0-90e4-c7a44b7f3e8f
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