Modelling the high‑temperature deformation characteristics of S355 steel using artificial neural networks

• Autorzy: Olejarczyk-Wożeńska, Izabela , Mrzygłód, Barbara , Hojny, Marcin
• Języki publikacji: EN

Abstrakty

EN

In this study, artificial neural networks were used to predict the plastic flow behaviour of S355 steel in the process of high-temperature deformation. The aim of the studies was to develop a model of changes in stress as a function of strain, strain rate and temperature, necessary to build an advanced numerical model of the soft-reduction process. The high-temperature characteristics of the tested steel were determined with a Gleeble 3800 thermo-mechanical simulator. Tests were carried out in the temperature range of 400-1450 °C for two strain rates, i.e. 0.05 and 1 s^-1. The test results were next used to develop and verify a rheological model based on artificial neural networks (ANNs). The conducted studies show that the selected models offer high accuracy in predicting the high-temperature flow behaviour of S355 steel and can be successfully used in numerical modelling of the soft-reduction process.

Słowa kluczowe

PL

stal S355; sztuczna sieć neuronowa; model reologiczny

EN

plastic flow behaviour; S355 steel; artificial neural network; rheological model; soft reduction process

• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2023
• Tom: Vol. 23, no. 1
• Strony: art. no. e1, 2023
• Opis fizyczny: Bibliogr. 13 poz., rys., tab., wykr.

Twórcy

autor

Olejarczyk-Wożeńska, Izabela

• Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, Al. Adama Mickiewicza 30, 30‑059 Krakow, Poland

autor

Mrzygłód, Barbara

• Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, Al. Adama Mickiewicza 30, 30‑059 Krakow, Poland,

autor

Hojny, Marcin

• Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, Al. Adama Mickiewicza 30, 30‑059 Krakow, Poland

Bibliografia

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• 11. Yonghua D, Lishi M, Huarong Q, Runyue L, Ping L. Developed constitutive models, processing maps and microstructural evolution of Pb-Mg-10Al-0.5B alloy. Mater Charact. 2017;129:353-66.
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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)

Identyfikatory

DOI

10.1007/s43452-022-00538-x