DATA DRIVEN APPROACH TO FACTOR ANALYSIS FOR SURFACE CHLORIDE CONCENTRATON OF RC STRUCTURES IN MARINE ENVIRONMENT

Abstract

Reinforced concrete (RC) structures should be designed with considering the effect of the surface chloride ion concentration (C₀). RC structures for port and harbor facilities are especially affected by C₀, and the value of C₀ for their design is estimated by the equation which is the linear regression of measured C₀ data with only the distance from the high water level in Japan. However, the equation is not sufficiently reproducible for all measurement data, and thus this study aimed to develop a new regression model by using machine learning technique, which is a powerful data driven approach. From the environmental factors, the variables contribute to the improvement of regression performance were extracted and the model was constructed by learning these data. The performance of the model was investigated and the result showed that “significant wave height” is useful for predicting C₀, for especially near the sea level.