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Progress on statistical models of evaluating inclusions in clean steels |
Zheng Wang1, Yue-hui Guan2, Hai-wen Luo1 |
1 School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China 2 Jiang Yin Xing Cheng Alloy Material Co., Ltd., Jiangyin 214432, Jiangsu, China |
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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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Cite this article: |
Zheng Wang,Yue-hui Guan,Hai-wen Luo. Progress on statistical models of evaluating inclusions in clean steels[J]. Journal of Iron and Steel Research International, 2022, 29(08): 1153-1163.
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