Optimal design of steel exoskeleton for the retrofitting of RC buildings via genetic algorithm

In recent decades, steel exoskeletons have gathered significant attention as a seismic retrofitting technique for existing structures. The design methods proposed so far are focused on the identification of the system's overall parameters through simplified models. Although these methodologies provide helpful guidance at the preliminary design stage, they do not consider aspects such as the distribution of the exoskeletons and sizing of their components. To overcome these limitations, an optimization process based on the Genetic Algorithm is proposed in this paper to identify the optimal exoskeleton number and spatial arrangement, and to determine the optimal size of their constituent elements. The algorithm aims to minimize the weight of the retrofit solution while keeping the whole existing structure in the elastic field and ensuring the structural verification of the exoskeleton's elements. The analyses have been conducted using a finite-element code with an Open Application Programming Interface, which allows the models to be handled through automatic routines. The proposed optimization tool has been applied to several case studies, considering two different layouts for the exoskeletons. Finally, the effectiveness of the retrofit method has been demonstrated, and the proposed optimization tool has been able to significantly reduce the weight and cost of the intervention.