The use of artificial neural networks for modelling pitting corrosion behaviour of EN 1.4404 stainless steel in marine environment: data analysis and new developments

Abstract

Abstract Stainless steel has proved to be an important material to be used in a wide range of applications. For this reason, ensuring the durability of this alloy is essential. In this work, pitting corrosion behaviour of EN 1.4404 stainless steel is evaluated in marine environment in order to develop a model capable of predicting its pitting corrosion status by an automatic way. Although electrochemical techniques and microscopic analysis have been shown to be very useful tools for corrosion studies, these techniques may present some limitationus. With the aim to solve these drawbacks, a three-step model based on Artificial Neural Networks (ANNs) is proposed. The results reveal that the model can be used to predict pitting corrosion status of this alloy with satisfactory sensitivity and specificity with no need to resort to electrochemical tests or microscopic analysis. Therefore, the proposed model becomes a useful tool to predict the behaviour of the material against pitting corrosion in saline environment automatically.