Table of Contents
ISRN Metallurgy
Volume 2012, Article ID 487351, 6 pages
http://dx.doi.org/10.5402/2012/487351
Research Article

Modeling to Study the Effect of Environmental Parameters on Corrosion of Mild Steel in Seawater Using Neural Network

Department of Metallurgical and Material Engineering, Jadavpur University, Kolkata 700032, India

Received 15 December 2011; Accepted 4 January 2012

Academic Editors: J. Eckert and J. M. Rodriguez-Ibabe

Copyright © 2012 Subir Paul. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

The following is the list of published articles that have cited the current article.

  • Subir Paul, “Modeling unpredictable failures of 304 construction material in seawater by pitting corrosion and simulate chloride ion distribution by finite element method,” Multidiscipline Modeling in Materials and Structures, vol. 12, no. 3, pp. 543–557, 2016. View at Publisher · View at Google Scholar
  • Subir Paul, and Shibasish Bhattacharjee, “Modeling and computation by artificial neural network of fracture toughness of low alloy steel to study the effect of alloy composition,” International Journal of Modeling, Simulation, and Scientific Computing, pp. 1850051, 2018. View at Publisher · View at Google Scholar
  • R. Nevshupa, I. Martinez, S. Ramos, and A. Arredondo, “The effect of environmental variables on early corrosion of high–strength low–alloy mooring steel immersed in seawater,” Marine Structures, vol. 60, pp. 226–240, 2018. View at Publisher · View at Google Scholar