Quantitative estimation of corrosion rate in 3C steels under seawater environment

Lee, Sedong and Narayana, P.L. and Seok, Bang Won and Panigrahi, B.B. and Lim, Su-Gun and S. Reddy, N. (2021) Quantitative estimation of corrosion rate in 3C steels under seawater environment. Journal of Materials Research and Technology, 11. pp. 681-686. ISSN 22387854

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An artificial neural network method is proposed to correlate the relationship between the corrosion rate of 3C steels with seawater environment factors. The predictions with the unseen test data are in good agreement with experimental values. Further, the developed model used to simulate the combined effect of environmental factors (temperature, dissolved oxygen, salinity, pH values, and oxidation-reduction potential) on the corrosion rate. 3D mappings remarkably reveal the complex interrelationship between the input environmental parameters on the output corrosion rate. The quantitative estimation of corrosion by virtual addition/subtraction of environmental factors individually to a hypothetical system helps to understand the impact of each parameter.

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IITH Creators:
IITH CreatorsORCiD
Panigrahi, Bharat BhooshanUNSPECIFIED
Item Type: Article
Uncontrolled Keywords: 3c steel; Artificial neural network methods; Elsevier; Environment factors; Environmental factors; Neural-networks; Quantitative estimation; Seawater corrosion rate; Seawater environment; Virtual seawater environment
Subjects: Others > Metallurgy Metallurgical Engineering
Materials Engineering > Materials engineering
Divisions: Department of Material Science Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 27 Jul 2021 04:42
Last Modified: 27 Jul 2021 04:42
URI: http://raiith.iith.ac.in/id/eprint/8534
Publisher URL: http://doi.org/10.1016/j.jmrt.2021.01.039
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