Parametric modeling and evolutionary method for predictive maintenance of marine reinforced concrete structures

The absence of an efficient maintenance method has incurred substantial additional costs, emerging as the primary impediment to the advancement of marine reinforced concrete (RC) structures. This paper proposes a parametric modeling and evolutionary optimization method to improve the cost-effectiveness ratio of structural maintenance. The deterioration risk distribution of the entire structural system is established through parametric modeling. An evolutionary optimization method grounded in genetic algorithm (GA) is utilized to determine the optimal maintenance sizes, followed by the space-time-dependent survival probability route (STSPR) method to refine the maintenance times for each specific maintenance size. The Hangzhou Bay cross-sea Bridge in China is used to illustrate the practicality of the proposed method. The results indicate a cost-effectiveness ratio reduction of 63.3 %, 58.1 %, and 3.1 % and a lifetime extension of 9.1 %, 24.7 %, and 1.7 % for bridge piers, bridge wet joints, and bridge caps, respectively, compared to the sequential failure limit method.