Development of Regression Model for Prediction of Corrosion Level in Polypropylene Fiber Reinforced Concrete Using Response Surface Methodology
摘要
Corrosion stands as the primary cause behind the diminished service life of reinforced concrete structures, particularly in environments such as ports, harbors, bridges, and other offshore and near-shore locations where chloride-induced corrosion poses a significant threat. This study investigates the efficacy of three key parameters polypropylene fiber ratio ( \(F_{R}\) ), concrete cover ( \(C_{C}\) ), and bar diameter ( \(\emptyset\) )—in minimizing corrosion ( \(C_{L}\) ) in reinforced concrete structures. Central Composite Design (CCD) of Response Surface Methodology (RSM) is employed to determine the optimal conditions for these parameters. The number of samples for Impressed Current (IC) testing is determined through this methodology. Initial analysis utilizing the full quadratic model yields a Predicted \(R^{2}\) value of 60.77%. However, employing backward elimination enhances the predictive capability, resulting in an improved \(R^{2}\) value of 87.53%. Sensitivity analysis utilizing the coded units of the RSM model reveals that the polypropylene fiber ratio exerts the most significant impact on corrosion levels, with a sensitivity value of -4.932. Consequently, optimization efforts are focused on this parameter, leading to the identification of an optimized value of 1.17% for \(F_{R}\) , which results in minimal corrosion. This research underscores the effectiveness of employing RSM techniques in optimizing corrosion mitigation strategies in reinforced concrete structures, with \(F_{R}\) emerging as a critical determinant in achieving corrosion resistance.