Predictive model for determination of pitting corrosion in stainless steel pipes

Due to the existence of a host of different parameters as well as a large number of variables in the behavior of pitting in stainless steel pipes, it is rather important, and at times inevitable, to utilize statistical predictive models of pitting. In this regard, based on the acquired outcomes, logical models have gained ground enormously in recent years (Johnsen and Hilfer, 1997; Hawn, 1977, Leifer et al., 1999). The main objective of this research was to develop a predictive model for the determination of pitting corrosion in stainless steel pipes based on three parameters: chloride ion, temperature and potential. The model was developed based on these parameters and a statistical analysis of experimental data was gathered. A logical regression model was constructed and presented herein, coupled with two methods of predicting values as well as probability of pitting to provide a comparison of the obtained results.