Data mining to effect of key alloying elements on corrosion resistance of low alloy steels in Sanya seawater environmentAlloying Elements. (20th February 2021)

• Record Type: Journal Article
• Authors: Wei, Xin; Fu, Dongmei; Chen, Mindong; Wu, Wei; Wu, Dequan; Liu, Chao
• Is Part Of: Journal of materials science & technology. Volume 64(2021)
• Page Start: 222
• Page End: 232
• Publication Date: 2021-02-20
• Subjects: Low alloy steel -- Corrosion potential -- Key alloying elements -- Corrosion-resistant alloy -- Artificial neural network -- Data-driven model; Metals -- Periodicals; Materials science -- Periodicals; Materials science; Metals; Periodicals; 620.1105
• DOI: 10.1016/j.jmst.2020.01.040
• Languages: English
• ISSNs: 1005-0302

Abstract

Abstract: 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.