Multi-objective seismic design of BRBs-reinforced concrete buildings using genetic algorithms

In this study, the optimal seismic design of traditional and buckling-restrained braces (BRBs) 3D-reinforced concrete (R/C) buildings is compared. The optimal buildings are obtained through the non-dominated sorting genetic algorithm (NSGA-II) multi-objective technique. Unlike most of this type of studies, the complete design of the 3D frames will be obtained considering the slabs, beams, columns, and braces as variables of the algorithm that are used to calculate dead and seismic loads. For this aim, two objective functions are established: (1) the first objective function is the cost of the structural building that includes materials and construction; (2) the second is the ratio between the maximum inter-story drift and the allowable drift, which is the most common structural performance parameter used by the earthquake building codes. For the purpose of this study, several R/C buildings are designed in accordance with the Mexico City Building Code (MCBC) using NSGA-II. The results demonstrate that as the height of the R/C buildings tend to increase, the frames with BRBs are more economical having similar level of structural performance in comparison with traditional moment resisting R/C framed buildings. In addition, the application of the evolutionary technique based on genetic algorithms for structural design improves considerably the structural performance and is able to reduce the total structural cost of the buildings.

Automated summary

This study compares the optimal seismic design of traditional and buckling-restrained braces (BRBs) 3D-reinforced concrete (R/C) buildings using the non-dominated sorting genetic algorithm (NSGA-II) multi-objective technique. The results show that as the height of R/C buildings tend to increase, frames with BRBs are more economical and have similar level of structural performance compared to traditional moment resisting R/C framed buildings. Additionally, the application of genetic algorithms for structural design significantly improves structural performance and reduces the total structural cost of the buildings.