TY - CONF

T1 - Selected metallurgical models for computationally efficient prediction of quality-related issues in continuous slab casting of steel

AU - Bernhard, Michael Christian

AU - Presoly, Peter

AU - Hahn, Susanne

AU - Ilie, Sergiu

AU - Bernhard, Christian

PY - 2022/5

Y1 - 2022/5

N2 - Continuous casting is the most dominating process in modern steelmaking, with more than 95 % of the annual world steel production. Currently, great effort is made to develop online-capable quality prediction systems based on fundamental metallurgical concepts with fast runtimes. The essential part of so-called “quality index” strategies is, of course, their industrial verification but also their further improvement using high-fidelity offline software tools. The present work introduces a 2D offline heat transfer model as a development platform for continuous slab casting. The calculated temperature fields are critically verified with temperature measurements performed during the casting process in the first part. Then, simulation results of two quality indicators are presented, describing (i) the phenomenon of non-uniform heat withdrawal during initial solidification in the casting mold caused by the volume contraction during the peritectic transition and (ii) the risk of internal hot tear segregation formation with particular respect to transversal half-way cracks. The consideration of the actual chemical composition of the steel grade leads to a reasonable agreement between the calculated peritectic indicator and local temperature fluctuations in the mold recorded by permanently installed thermocouples. Based on systematic quality analysis after casting, the hot tear criterion can be successfully applied to reduce the risk of the formation of transverse half-way cracks by adjusting the casting parameters. Finally, a slight modification of the peritectic indicator is implemented into the online capable system “DynaQI” running at the industry partner’s slab caster. Despite the rapid calculation procedure of DynaQI the results show even more improved performance in quality prediction and confirm the approach of offline/online coupled development of quality indices.

AB - Continuous casting is the most dominating process in modern steelmaking, with more than 95 % of the annual world steel production. Currently, great effort is made to develop online-capable quality prediction systems based on fundamental metallurgical concepts with fast runtimes. The essential part of so-called “quality index” strategies is, of course, their industrial verification but also their further improvement using high-fidelity offline software tools. The present work introduces a 2D offline heat transfer model as a development platform for continuous slab casting. The calculated temperature fields are critically verified with temperature measurements performed during the casting process in the first part. Then, simulation results of two quality indicators are presented, describing (i) the phenomenon of non-uniform heat withdrawal during initial solidification in the casting mold caused by the volume contraction during the peritectic transition and (ii) the risk of internal hot tear segregation formation with particular respect to transversal half-way cracks. The consideration of the actual chemical composition of the steel grade leads to a reasonable agreement between the calculated peritectic indicator and local temperature fluctuations in the mold recorded by permanently installed thermocouples. Based on systematic quality analysis after casting, the hot tear criterion can be successfully applied to reduce the risk of the formation of transverse half-way cracks by adjusting the casting parameters. Finally, a slight modification of the peritectic indicator is implemented into the online capable system “DynaQI” running at the industry partner’s slab caster. Despite the rapid calculation procedure of DynaQI the results show even more improved performance in quality prediction and confirm the approach of offline/online coupled development of quality indices.

M3 - Poster

T2 - Integrated Computational Materials, Process and Product Engineering 2022

Y2 - 5 May 2022 through 6 May 2022

ER -