4.7 Article

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

Journal

JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
Volume 64, Issue -, Pages 222-232

Publisher

JOURNAL MATER SCI TECHNOL
DOI: 10.1016/j.jmst.2020.01.040

Keywords

Low alloy steel; Corrosion potential; Key alloying elements; Corrosion-resistant alloy; Artificial neural network; Data-driven model

Funding

  1. National Environmental Corrosion Platform of China
  2. National Key Research and Development Program of China [2017YFB0702100]
  3. National Natural Science Foundation of China [51871024]

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This paper establishes a relationship model between seawater environment, chemical composition, and corrosion potential of low alloy steel, and explores the distribution of corrosion potential with changes in key alloying elements. Through data dimension reduction, correlation analysis, and classification methods, the research provides an intuitive data basis for the development of high-quality low alloy steels.
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. (c) 2020 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.

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