Significance
Carbon macro/semi-macro segregation in steel is a phenomenon that affects the uniformity of carbon distribution within billets during the continuous casting process. The macro/semi-macro segregation can lead to variations in the mechanical properties of the billets obviously, which cannot be rectified through subsequent heat treatments or rolling processes. The hereditary nature of carbon segregation, where the segregation patterns are inherited by the rolled products from the billets, underscores the importance of developing a quantitative understanding of this process to enhance the quality and utilization rate of the final products. To address these challenges posed by carbon segregation, new research led by Professor Zibing Hou and his team (Dongwei Guo, Kunhui Guo, Zhiqiang Peng, and Fuli Zhang) at Chongqing University developed an innovative quantitative model based on grayscale analysis to analyze the distribution of carbon elements within billets and rolled products. By inventing and employing the new method of Metal Macrostructure Grayscale Analysis (MGA) , the team was able to calculate the carbon content across the longitudinal sections of the billets and rolled products in large regions, facilitating a detailed examination of carbon distribution characteristics. This method proved advantageous over traditional techniques, such as drilling sampling and electron probe analysis, by allowing for a comprehensive and quantitative analysis across the entire area of the longitudinal sections, thus providing a more accurate reflection of the hereditary behavior of carbon segregation. The study is now published in Steel Research International. The team selected cold-heading steel billets along with wire rod samples of different specifications and cold-heading bolt samples as their research objects. The chemical composition of cold-heading steel primarily included carbon, silicon, manganese, phosphorus, sulfur, chromium, molybdenum, and iron. The authors standardized the different continuous casting process parameters, such as specific water amount, casting speed, and superheat of molten steel in the tundish and also applied electromagnetic stirring to enhance the uniformity of the solidification process. Moreover, the researchers, established a methodological framework to convert macrostructure images of billets and rolled products into grayscale images using the software. This conversion allowed for the quantitative analysis of carbon content based on the grayscale values. Furthermore, they used the correlation between macrostructure grayscale values and carbon content, deriving a formula to calculate the carbon content at each pixel position within the images of the longitudinal sections of the samples. Additionally, the team examined the hereditary behavior of carbon segregation by analyzing the carbon content and distribution characteristics at geometrically similar positions across the selected samples, focusing on longitudinal carbon fluctuation and transverse carbon uniformity.
The authors’ analysis revealed that the distribution characteristics of the carbon element content and the carbon variation coefficient on the longitudinal sections of the selected samples were approximately consistent, enabling a quantitative reflection of the hereditary behavior of carbon segregation. They also successfully fitted hereditary equations for carbon element content, longitudinal carbon fluctuation, and transverse carbon uniformity during the rolling process. These equations quantitatively describe the evolution of carbon content and its distribution from billets to rolled products. One of the key contributions of the study is the establishment of a central segregation index, which quantitatively represents the transverse carbon uniformity in the billets and rolled products. This index serves as a critical parameter for controlling the quality of the billets and enhancing the uniformity of the rolled products.
The authors proposed a control requirement for the internal quality of billets based on the hereditary equation of the central segregation index. It was suggested that to produce rolled products with uniform quality and mechanical properties, the central segregation index of the corresponding billet should be controlled below a certain threshold. The implications of Professor Zibing Hou and his colleagues research extend beyond the academic sphere, offering practical solutions for the steel industry. By providing a quantitative model to predict and analyze the hereditary behavior of carbon segregation, this study paves the way for the development of targeted strategies to minimize carbon segregation and improve the internal quality of continuous casting billets. This, in turn, can lead to an increase in the utilization rate of finished products, reducing material waste and enhancing the efficiency of the steel production process. In conclusion, the development of a quantitative model based on grayscale analysis by Professor Zibing Hou and his team offers a new tool for the steel industry to improve product quality and efficiency. The work also provides a foundation for future research aimed at addressing the challenges associated with element segregations in different kinds of steels and other alloys production. Moreover, the new method of MGA should be very effective way to quantitatively characterize the multiscale segregation extent in large regions, which is very meaningful for fine control of quality and intelligent manufacturing.
The authors’ analysis revealed that the distribution characteristics of the carbon element content and the carbon variation coefficient on the longitudinal sections of the selected samples were approximately consistent, enabling a quantitative reflection of the hereditary behavior of carbon segregation. They also successfully fitted hereditary equations for carbon element content, longitudinal carbon fluctuation, and transverse carbon uniformity during the rolling process. These equations quantitatively describe the evolution of carbon content and its distribution from billets to rolled products. One of the key contributions of the study is the establishment of a central segregation index, which quantitatively represents the transverse carbon uniformity in the billets and rolled products. This index serves as a critical parameter for controlling the quality of the billets and enhancing the uniformity of the rolled products.
The authors proposed a control requirement for the internal quality of billets based on the hereditary equation of the central segregation index. It was suggested that to produce rolled products with uniform quality and mechanical properties, the central segregation index of the corresponding billet should be controlled below a certain threshold. The implications of Professor Zibing Hou and his colleagues research extend beyond the academic sphere, offering practical solutions for the steel industry. By providing a quantitative model to predict and analyze the hereditary behavior of carbon segregation, this study paves the way for the development of targeted strategies to minimize carbon segregation and improve the internal quality of continuous casting billets. This, in turn, can lead to an increase in the utilization rate of finished products, reducing material waste and enhancing the efficiency of the steel production process. In conclusion, the development of a quantitative model based on grayscale analysis by Professor Zibing Hou and his team offers a new tool for the steel industry to improve product quality and efficiency. The work also provides a foundation for future research aimed at addressing the challenges associated with element segregations in different kinds of steels and other alloys production. Moreover, the new method of MGA should be very effective way to quantitatively characterize the multiscale segregation extent in large regions, which is very meaningful for fine control of quality and intelligent manufacturing.
About the author
Prof. Zibing Hou
Professor Hou received a PhD degree in University Science and Technology Beijing, now is in Metallurgical Engineering Department, College of Materials Science and Engineering, Chongqing University, China. He is serving as a member of the Scrap Steel Branch of the Chinese Metal Society, and vice chairman of the Sichuan Metal Society for electric furnace steelmaking, and spent one year as a visiting scholar in the Engineering Department of the University of Leicester in UK. His current research interests include efficient continuous casting and intelligent manufacturing, multi-dimensional and multi-scale characterization of solidified structure, automatic detection of structure and performance prediction, mold powder for continuous casting, low carbon metallurgy, etc.
Professor Hou received a PhD degree in University Science and Technology Beijing, now is in Metallurgical Engineering Department, College of Materials Science and Engineering, Chongqing University, China. He is serving as a member of the Scrap Steel Branch of the Chinese Metal Society, and vice chairman of the Sichuan Metal Society for electric furnace steelmaking, and spent one year as a visiting scholar in the Engineering Department of the University of Leicester in UK. His current research interests include efficient continuous casting and intelligent manufacturing, multi-dimensional and multi-scale characterization of solidified structure, automatic detection of structure and performance prediction, mold powder for continuous casting, low carbon metallurgy, etc.
Reference
Dongwei Guo, Zibing Hou,* Kunhui Guo, Zhiqiang Peng, and Fuli Zhang. Quantitative Model of Hereditary Behavior for Carbon Segregation in Continuous Casting Billets Based on Grayscale Analysis. Steel Research International 2023, 94, 2200782.
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