| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Pohjonen, Aarne
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (8/8 displayed)
- 2023Gradient boosted regression trees for modelling onset of austenite decomposition during cooling of steelscitations
- 2023Evaluation of a processing route and microstructural characteristics for the development of ultrafine bainite in low-temperature ausformed medium-carbon steelscitations
- 2022Virtual rolling automation and setup calculations for six stands FEM finishing millcitations
- 2022Analysis of grain size distribution evolution of steel during recrystallization and grain growthcitations
- 2021Optimization of the CCT curves for steels containing Al, Cu and Bcitations
- 2020Towards industrial applicability of (medium C) nanostructured bainitic steels (TIANOBAIN)
- 2019Optimization of CCT equations using calculated grain boundary soluble compositions for the simulation of austenite decomposition of steelscitations
- 2018Analytical approximations and simulation tools for water cooling of hot rolled steel stripcitations
Places of action
| Organizations | Location | People |
|---|
article
Analysis of grain size distribution evolution of steel during recrystallization and grain growth
Abstract
ontrolling the hot rolling process requires a deep understanding of the underlying metallurgical phenomena. Quantitative methods are of paramount importance for achieving the capability of controlling microstructural evolution. Since the final mechanical properties of steel result from microstructural evolution in the whole process, analysis of the microstructure provides an important input for numerical simulations that can be used for tailoring the mechanical properties of steel. The evolution of grain size distribution of a low-carbon CrNiMnB ultrahigh-steel in austenitic state is studied in hot forming and annealing using experimental data obtained with the Gleeble 3800 thermo-mechanical simulator. A general method is described that can be utilized to systematically compare the grain size distributions obtained from the experimental studies. The experimental data has been obtained from laser scanning confocal microscopy images using the mean linear intercept method. A custom-made semi-automatic software has been utilized to process the data rapidly and reliably.