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Analysis of Corrosion Behavior of Steel 3 in Chloride Solutions by Using Neural Networks V. D. Kiselev, S. M. Ukhlovtsev, A. N. Podobaev, and I. I. Reformatskaya Federal State Unitary Enterprise “Karpov Research Institute of Physical Chemistry,”
ul. Vorontsovo Pole 10, Moscow, 103064 Russia e-mail:
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Received May 9, 2005 Abstract — The method of neural-network analysis of experimental data is applied to the corrosion system for the first time. The neural-network simulation enables one to predict adequately the response of steel 3-chloridecontaining solution system to the external effects: the variations in the pH value and in the concentration of chloride ions. Trained neural network uniquely determines the characteristic potentials of corrosion system (the free-corrosion, passivation, and repassivation potentials) from the data on the chemical composition of corrosive medium and, based on these potentials, predicts the type of corrosion: active dissolution, passivity, or passivity with probable pitting. PACS numbers: 81.65.Rv, 82.45.Bb DOI: 10.1134/S0033173206050031
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