Szczegóły publikacji
Opis bibliograficzny
Modelling the high-temperature deformation characteristics of S355 steel using artificial neural networks / Izabela OLEJARCZYK-WOŻEŃSKA, Barbara MRZYGŁÓD, Marcin HOJNY // Archives of Civil and Mechanical Engineering / Polish Academy of Sciences. Wrocław Branch, Wrocław University of Technology ; ISSN 1644-9665. — 2023 — vol. 23 iss. 1 art. no. 1, s. 1-11. — Bibliogr. s. 11, Abstr. — Publikacja dostępna online od: 2022-10-10
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 143102 |
|---|---|
| Data dodania do BaDAP | 2022-10-17 |
| Tekst źródłowy | URL |
| DOI | 10.1007/s43452-022-00538-x |
| Rok publikacji | 2023 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Archives of Civil and Mechanical Engineering |
Abstract
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.