4.5 Article

Modification for prediction model of austenite grain size at surface of microalloyed steel slabs based on in situ observation

Journal

JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL
Volume 28, Issue 9, Pages 1133-1140

Publisher

SPRINGER
DOI: 10.1007/s42243-020-00513-x

Keywords

In situ observation; Microalloyed steel; Austenite grain size; Prediction model; Oscillation mark depth

Funding

  1. Joint Fund of Iron and Steel Research of the National Natural Science Foundation of China
  2. Baowu Group Corporation [U1760103]

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The study successfully established a newly modified model for predicting the austenite grain size in microalloyed steels during the initial solidification process, and verified the accuracy and practicality of the model through experimentation.
The initial solidification process of microalloyed steels was simulated using a confocal scanning laser microscope, and the growth behavior of austenite grain was observed in situ. The method for measuring the initial austenite grain size was studied, and the M0* (the parameter to describe the grain boundary migration) values at different cooling rates were then calculated using the initial austenite grain size and the final grain size. Next, a newly modified model for predicting the austenite grain size was established by introducing the relationship between M0* and the cooling rate, and the value calculated from the modified model closely corresponds to the measured value, with average relative error being less than 5%. Further, the relationship between T-gamma (the starting temperature for austenite grain growth) and equivalent carbon content C-P (C-P > 0.18%) was obtained by in situ observation, and it was introduced into the modified model, which expanded the application scope of the model. Taking the continuous casting slab produced by a steel plant as the experimental object, the modified austenite grain size prediction model was used to predict the austenite grain size at different depths of oscillation mark on the surface of slab, and the predicted value was in good agreement with the actual measured value.

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