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Data-mining and atmospheric corrosion resistance evaluation of Sn-and Sb-additional low alloy steel based on big data technology 被引量:8
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作者 Xiaojia Yang Jike Yang +4 位作者 Ying Yang Qing Li Di Xu Xuequn Cheng Xiaogang Li 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2022年第4期825-835,共11页
Machine-learning and big data are among the latest approaches in corrosion research.The biggest challenge in corrosion research is to accurately predict how materials will degrade in a given environment.Corrosion big ... Machine-learning and big data are among the latest approaches in corrosion research.The biggest challenge in corrosion research is to accurately predict how materials will degrade in a given environment.Corrosion big data is the application of mathematical methods to huge amounts of data to find correlations and infer probabilities.It is possible to use corrosion big data method to distinguish the influence of the minimal changes of alloying elements and small differences in microstructure on corrosion resistance of low alloy steels.In this research,corrosion big data evaluation methods and machine learning were used to study the effect of Sb and Sn,as well as environmental factors on the corrosion behavior of low alloy steels.Results depict corrosion big data method can accurately identify the influence of various factors on corrosion resistance of low alloy and is an effective and promising way in corrosion research. 展开更多
关键词 MACHINE-LEARNING corrosion big data low alloy steels corrosion resistance
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