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Progress on statistical models of evaluating inclusions in clean steels

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Abstract

Non-metallic inclusions are critical for the fatigue failure of clean steels in service; especially, the large and hard inclusions are detrimental. Since it is not possible to measure all the inclusions in the large-volume clean steels, statistical models have been developed to evaluate inclusions, aiming at predicting the maximum inclusion size in the large volume from the data of inclusions, which are derived from the limited observations on small-volume specimens. Different statistical models were reviewed together with their supporting theories. In particular, the block maxima and the threshold types of models were discussed through a thorough comparison as they are both widely used and based on the extreme value theory. The predicted results not only are used to distinguish the different cleanliness levels of steels, but also help to estimate fatigue strength. Finally, future research is proposed to focus on tackling the present difficulties encountered by statistical models, including the sufficient credibility of obtained results and the robustness of models for applications.

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Acknowledgements

Prof. H.W. Luo acknowledges the financial support from the National Natural Science Foundation of China (No. 51831002) and Fundamental Research Funds for the Central Universities (No. FRF-TP-18-002C2).

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Authors and Affiliations

  1. School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Zheng Wang & Hai-wen Luo

  2. Jiang Yin Xing Cheng Alloy Material Co., Ltd., Jiangyin, 214432, Jiangsu, China

    Yue-hui Guan

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Wang, Z., Guan, Yh. & Luo, Hw. Progress on statistical models of evaluating inclusions in clean steels. J. Iron Steel Res. Int. 29, 1153–1163 (2022). https://doi.org/10.1007/s42243-022-00773-9

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