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.
Highlights
Corrosion of steel reinforcements has recently become a major problem in civil engineering [1,2,3].the attention of researchers is nowadays devoted to the protection of concrete and steel reinforcements against corrosion [4,5,6,7]
A direct method of providing an evaluation of the corrosion rate based on a corrosion current density measurement is linear polarization resistance (LPR)
The results indicate that linear regression (LR) 3 model is more accurate than the other models
Summary
Corrosion of steel reinforcements has recently become a major problem in civil engineering [1,2,3]. The MLP has a satisfactory performance for reinforced concrete slabs with a high conventional multilayer perceptron (MLP) were established [33] These models have a theoretical corrosion rate (R = 0.9436 for training and R2 = 0.9843 for testing), while the observed performance value as they can predict the corrosion current density without the Considering the above, the article presents a new technique of predicting the corrosion current density in reinforced concrete using a SOFM For this purpose, air temperature and parameters determined by the resistivity four-probe method and galvanostatic resistivity measurements were employed as inputs. Structural model of the SOFM [45]
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