Predictive mapping and analysis of aging severity for acrylic resin coatings in global marine environments

The aging failure process of acrylic resin (AR) coatings widely used in ship anti-corrosion systems is highly complex. Currently, there are no established models or methods for predicting the aging of AR coatings in different marine environments. Therefore, this study proposes a framework for predicting the aging of AR coatings in marine environment based on short-term indoor accelerated tests. Initially, a comprehensive aging evaluation method for AR coatings is developed by integrating three commonly used coating performance evaluation indicators (gloss, color difference, and electrochemical impedance) based on the Technique for Order Preference by Similarity to Ideal Solution. Subsequently, an aging severity index is defined to quantify the impact of different environments on the coating aging process. Following this, 14 sets of indoor accelerated aging tests for AR coatings under various environmental conditions are conducted. Based on the test results, a comparative analysis of the predictive performance of three environmental effect models, namely multiple linear regression model, generalized Eyring model, and genetic algorithm-back-propagation model, is performed. Finally, utilizing the environmental effect models and global marine environmental data, the aging severity index of AR coatings in global marine environments is predicted and extrapolated.