Study the effect of seawater environments and surface roughness on uniform corrosion rate of carbon steel using neural network modeling

Abstract EN

In this research, the effect of seawater environments and surface roughness on uniform corrosion rate of carbon steel (A516 grade 65) was studied depending on the experimental work and artificial neural network modeling.

The experimental work involves chemical composition, samples machining, and roughness measurements (for carbon steel specimens), conductivity and salinity measurements (for seawater), and uniform corrosion test.

Weight loss technique was employed in determining the uniform corrosion rate in carbon steel material.

Also, artificial neural network (ANN) model was built to predict the values of uniform corrosion rate (mpy) at different values of conductivity, salinity for seawater and roughness factor for carbon steel depending on the experimental results which were used train and test the ANN.

The results obtained of uniform corrosion rate by ANN predictions are shown to be agreed well against experimental values.

i.e.

correlation coefficient, R = 0.9974.