| 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 |
|
Alatarvas, Tuomas
University of Oulu
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (8/8 displayed)
- 2024Coupling of Solidification and Heat Transfer Simulations with Interpretable Machine Learning Algorithms to Predict Transverse Cracks in Continuous Casting of Steelcitations
- 2023Modeling the precipitation of aluminum nitride inclusions during solidification of high‐aluminum steelscitations
- 2023Assessing the Effects of Steel Composition on Surface Cracks in Continuous Casting with Solidification Simulations and Phenomenological Quality Criteria for Quality Prediction Applicationscitations
- 2022Uncovering temperature-tempted coordination of inclusions within ultra-high-strength-steel via in-situ spectro-microscopycitations
- 2022A kinetic model for precipitation of TiN inclusions from both homogeneous and heterogeneous nucleation during solidification of steelcitations
- 2021Unveiling interactions of non-metallic inclusions within advanced ultra-high-strength steel: A spectro-microscopic determination and first-principles elucidation
- 2021Modelling the nucleation, growth and agglomeration of alumina inclusions in molten steel by combining Kampmann–Wagner numerical model with particle size grouping methodcitations
- 2020Model for inclusion precipitation kinetics during solidification of steel applications in MnS and TiN inclusionscitations
Places of action
| Organizations | Location | People |
|---|
article
Assessing the Effects of Steel Composition on Surface Cracks in Continuous Casting with Solidification Simulations and Phenomenological Quality Criteria for Quality Prediction Applications
Abstract
<jats:sec><jats:label /><jats:p>Crack formation is an issue that significantly undermines the quality and productivity of steel production. In previous studies, a solidification and microstructure model known as InterDendritic Solidification (IDS) has been developed and implemented in various slab casters in Finland. Numerous quality criteria have been derived from the model outputs to identify the general phenomena which increase the risks of defect formation in different steel grades. The aim of this study is to study the feasibility of these criteria in providing input data for predicting quality in a group of defect‐prone steel grades with rule‐based decision‐making and machine learning algorithms. To this end, three steel grades are studied by utilizing measured compositions and comparing the quality criteria with plant data regarding reported defects. The computations are carried out by coupling IDS with a fundamental model for simulating heat transfer (Tempsimu) in continuous casting. The results indicate that for the studied steel grades, phenomenological quality criteria can be applied to predict the formation of cracks and other defects. Trends contributing to increased risks of defect formation are identified for all the studied steel grades, and possibilities for avoiding defects by changes in the compositions of these steel grades are also proposed.</jats:p></jats:sec>