Empirical Model for Predicting Corrosion Under Insulation Considering the Effects of Temperature, Salinity, and Water Content

Abstract

Corrosion under insulation (CUI) is one of the increasing issues in industries such as oil refineries and petrochemical plants. For preventing accident and reducing the inspection load caused by CUI, the prediction model for CUI has attracted increasing attention. In this study, to construct a prediction model for the corrosion rate of CUI (CUI rate), the effects of water content in the insulation material, salinity, and temperature on the CUI rate were evaluated with a corrosion test simulating a CUI environment. Analysis of the atmospheric corrosion monitoring sensor current showed that the CUI rate increased as the water content increased, promoting the formation of the water-thin film at the interface of insulation and carbon steel. Maxima of the CUI rate were observed for salinity and temperature. Salinity increased the electrical conductivity of the water-thin film and promoted the corrosion reaction, and over a certain salinity, the water-thin film became thicker and the CUI rate decreased due to the rate-determining step in oxygen diffusion. Over a certain temperature, the CUI rate decreased due to the evaporation of the water-thin film and a decrease in dissolved oxygen. We constructed the prediction model for the CUI rate with a coefficient of determination of 0.87 by multiple regression analysis using the obtained test data.