Data mining to effect of key alloying elements on corrosion resistance of low alloy steels in Sanya seawater environmentAlloying Elements

被引：17
作者：
Xin Wei [1 ]
Dongmei Fu [1 ,2 ]
Mindong Chen [3 ]
Wei Wu [4 ]
Dequan Wu [4 ]
Chao Liu [4 ]
机构：
[1] School of Automation and Electrical Engineering, University of Science and Technology Beijing
[2] Beijing Engineering Research Center of Industrial Spectrum Imaging, University of Science and Technology Beijing
[3] SINOPEC Research Institute of Safety Engineering
[4] Beijing Advanced Innovation Center for Materials Genome Engineering, Institute for Advanced Materials and Technology, University of Science and Technology Beijing
来源：
JournalofMaterialsScience&Technology | 2021年 / 64卷 / 05期
基金：
中国国家自然科学基金;
关键词：
D O I：
暂无
中图分类号：
TG142.33 [合金钢];
学科分类号：
080502 ;
摘要：
In this paper, the relationship model between seawater environment, chemical composition and corrosion potential of low alloy steel is established and the distribution of corrosion potential of low alloy steel with changes in key alloying elements is excavated. The research was carried out with the following steps: Firstly, the relationship model between corrosion potential of low alloy steel and its influencing factors was established by data dimension reduction and artificial neural network(ANN). Secondly, key alloying elements of experimental steels were selected out by Pearson correlation analysis, then the corrosion resistance element model was visualized to show the effect of key alloying elements on corrosion potential of low alloy steel. Finally, corrosion potential of low alloy steel with the change of key alloying elements was classified and visualized by classification method. The mining results can reflect the validity of the proposed mining methods to a certain extent and provide an intuitive data basis for the development of high-quality and low-cost low alloy steels.
引用
收藏
页码：222 / 232
页数：11
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