PREMΛP: Exploring the Design Space for Continuous Casting of Steel

Kumar, Prabhash; Goyal, Sharad; Singh, Amarendra K.; Allen, Janet K.; Panchal, Jitesh H.; Mistree, Farrokh

doi:10.1007/978-81-322-1050-4_60

Cited by 5 publications

(3 citation statements)

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“…Different types of quality criteria and indices have also been derived to assess defect formation and product quality in continuous casting. [14][15][16][17][18][19][20][21][22][23][24][25] Some of these criteria originate from thermo mechanical modeling, [14][15][16][17][18] in which the developed indices are commonly based on total strain and its thresholds. These criteria can indeed be beneficial in finding the fundamental causes of cracking, but they often lack practicality because of the high number of different steel grades with varying compositions and the difficulties in measuring stresses during continuous casting.…”

Section: Introductionmentioning

confidence: 99%

“…[3] Other criteria for assessing the quality or predicting the formation of defects have also been developed. [19][20][21][22][23][24][25] For example, internal and surface cracking tendencies have previously been predicted by computing indices based on a combination of measurements, casting abnormalities, casting parameters, and steel compositions. [19,24,25] The combined effects of segregation phenomena and empirically computed oscillation mark depth have also been considered in the form of a quality index to assess defect formation.…”

Section: Introductionmentioning

confidence: 99%

“…[19,24,25] The combined effects of segregation phenomena and empirically computed oscillation mark depth have also been considered in the form of a quality index to assess defect formation. [22] While such indices can indeed be applied as criteria for successfully predicting defects such as cracks, they can be highly specific to the steelmaking plant in question and the mechanisms of defect formation remain unknown. Quality criteria derived from fundamental models can provide a solution for this issue while also being applicable as features in predictive modeling and rule-based decision-making.…”

Section: Introductionmentioning

confidence: 99%

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Assessing the Effects of Steel Composition on Surface Cracks in Continuous Casting with Solidification Simulations and Phenomenological Quality Criteria for Quality Prediction Applications

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Louhenkilpi

Visuri

et al. 2023

steel research int.

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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.

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