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18.
Artificial Neural Network As A Prediction Tool For Mild Steel
Corrosion
P.
Neelamegam a* R. Vasumathi b
a
Department of Electronic and Instrumentation Engineering, SASTRA
University, Tanjore, Tamilnadu, India -613503.
b PG and Research Department of Physics, AVVM Sri Pushpam College,
Poondi, Tanjore, Tamilnadu, India -613503.
Abstract:
Mild steel is one of the major construction materials, which is
widely used in Chemical industries for the handling of acid and
alkali solutions. The corrosion behavior of Mild Steel in Hydro
Chloric Acid is investigated by Mass Loss measurements method.
The Rate of Corrosion for mild steel at various aqueous
environments by varying Chloride ion concentration (0.1N to 0.75
N), pH (0.12 to 1) and Temperature (290K to 333K) is modeled by
means of Artificial Neural Network. Fifty values of Rate of
Corrosion with 3 neurons at the input are used to model the
corrosion behavior of Mild Steel, using Back Propagation
Algorithm Neural Network approach. The applicability of the
developed Model is verified by comparing the computed results
and the experimental results obtained in this study. It is found
that the empirical model developed by using Neural Network
seemed to have a high prediction capability of the Rate of
Corrosion.
Key words: Mild Steel, Rate of Corrosion, Neural Network, pH,
Temperature, Chloride Concentration.
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