A soft-computing approach to seismic retrofitting of existing RC structures

This paper proposes a soft-computing approach intended at supporting engineering judgement on seismic retrofitting of existing Reinforced Concrete (RC) frames. It formulates a genetic algorithm aimed at selecting the “fittest” retrofitting solution by combining “member-level” and “structural-level” techniques. In the proposed approach, each “individual’s phenotype” includes a set of member-level interventions, described by the number of Fiber Reinforced Polymers (FRP) layers confining the single columns of the frame, and structure-level information, reporting the profiles possibly adopted in the various bays for realizing a concentric steel bracing system. Hence, a genotypic representation is obtained by adopting conven tional binary coding. The proposed genetic algorithm is capable to handle the three main genetic operators (namely, selection, crossover and mutation) that simulate the driving mechanisms of the evolution of species, as figured out by Charles Darwin, and resulting in the “survival of the fittest” rule. In this case, a fitness function based on initial costs and taking into account the technical effectiveness of the retrofitting interventions is considered with the aim to select the most cost-effective solution among the technically sound ones. Finally, a simple application of the proposed procedure is presented.