9:15 AM - 9:30 AM
[21001-05-04] A GAN-based Prediction for Corrosion Progress of Paint-coated Steel with Different Defects (Proceedings of Symposium on Applied Mechanics)
Keywords:Paint-coated steel, Corrosion, Deep learning, GAN
A series of experiments and numerical analyses were conducted for proposing a prediction method for the corrosion progress of paint-coated steel. Two types and different sizes of defects were artificially created on the paint-coating on SS400 steel to simulate the corrosion after the coating was damaged. The corrosion tests were carried out under the accelerated corrosion test ISO 16539 Method B. A generative adversarial network (GAN) based prediction model was used to simulate the corrosion progression at the coating defects. The proposed model could predict the corrosion at the final stage around the coating defects on the steel plate surface.