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Coatings 2017, 7(10), 160; https://doi.org/10.3390/coatings7100160

Prediction of the Corrosion Current Density in Reinforced Concrete Using a Self-Organizing Feature Map

1
Young Researchers and Elite Club, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
2
Faculty of Civil Engineering, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, Wroclaw 50-370, Poland
3
SAMA Technical and Vocational Training College, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
*
Author to whom correspondence should be addressed.
Received: 28 July 2017 / Revised: 15 September 2017 / Accepted: 26 September 2017 / Published: 29 September 2017
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Abstract

A disadvantage of using linear polarization resistance (LPR) in the measurement of corrosion current density is the need to partially destroy a concrete cover. In this article, a new technique of predicting the corrosion current density in reinforced concrete using a self-organizing feature map (SOFM) is presented. For this purpose, air temperature, and also the parameters determined by the resistivity four-probe method and galvanostatic resistivity measurements, were employed as input variables. The corrosion current density, predicted by the destructive LPR method, was employed as the output variable. The weights of the SOFM were optimized using the genetic algorithm (GA). To evaluate the accuracy of the SOFM, a comparison with the radial basis function (RBF) and linear regression (LR) was performed. The results indicate that the SOFM–GA model has a higher ability, flexibility, and accuracy than the RBF and LR. View Full-Text
Keywords: corrosion; resistivity; concrete; steel reinforcement; self-organizing feature map corrosion; resistivity; concrete; steel reinforcement; self-organizing feature map
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Nikoo, M.; Sadowski, Ł.; Nikoo, M. Prediction of the Corrosion Current Density in Reinforced Concrete Using a Self-Organizing Feature Map. Coatings 2017, 7, 160.

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