Design Optimization of Corroded Reinforced Concrete Frame using Genetic Algorithm

In this study, a simplified approach is proposed for design optimization of the reinforced concrete frame considering the effects of chloride-induced corrosion. The objective function is to minimize the frame weight, and optimization will be conducted utilizing the genetic algorithm. The constraints of the optimization problem are set in a manner that bending moment of beams and axial force of columns are not exceeding the respective resistant values, and the maximum drift of the frame is not exceeding the code-defined allowable drift. In order to examine the corrosion effects, a 5-story reinforced concrete frame is optimized in two different time points 0 and 50 years in its service life. The zero time point indicates the sound uncorroded frame. Monte Carlo sampling method in Rt software is utilized to estimate the corrosion initiation time incorporating the involved uncertainties. At time point of 50 years, a cross-sectional area of steel bars in beam and column sections is reduced due to the corrosion effects. The proposed framework for the frame optimization is implemented in MATLAB software; and for computing the structural response during the optimization process, the linear static analysis of the structure in OpenSees software is conducted. Results indicate an ability of the proposed framework for design optimization of reinforced concrete frames considering the corrosion effects in their service life.